ACTA » AGRICULTURAE SLOVENICA Biotehniška fakulteta Univerze v Ljubljani Biotechnical Faculty University of Ljubljana Acta agriculturae Slovenica • ISSN 1581-9175 • 105 - 2 • Ljubljana, september 2015 Acta agriculturae Slovenica Volume / Letnik 105 • Number / Številka 2 • 2015 VSEBINA / CONTENTS Članki / Articles Roghieh HAJIBOLAND, Noushin SADEGHZADEH, Nashmin EBRAHIMI, Behzad SADEGHZADEH, Seyed Abolgasem MOHAMMADI 175 Influence of selenium in drought-stressed wheat plants under greenhouse and field conditions Vpliv selena na pšenico v sušnem stresu v rastlinjaku in na polju Hamideh BAKHSHAYESHAN-AGDAM, Seyed Yahya SALEHI-LISAR, Rouhollah MOTAFAKKERAZAD, Amirhosein TALEBPOUR, Nader FARSAD 193 Allelopathic effects of redroot pigweed (Amaranthus retroflexus L.) on germination & growth of cucumber, alfalfa, common bean and bread wheat Alelopatični učinek navadnega ščira (Amaranthus retroflexus L.) na kalitev in rast kumar, lucerne, navadnega fižola in krušne pšenice Fariborz SHEKARI, Seyyed-Hamid MUSTAFAVI, Amin ABBASI 203 Sonication of seeds increase germination performance of sesame under low temperature stress Sonifikacija semen sezama z ultrazvokom poveča njihovo kalitev v razmerah hladnega stresa Bahram SALEHI, Hashem AMINPANAH 213 Effects of phosphorus fertilizer rate and Pseudomonasfluorescens strain on field pea (Pisum sativum subsp. arvense (L.) Asch.) growth and yield Učinki gnojenja s fosforjem in dodatkov sevov bakterije Pseudomonas fluorescens na rast in pridelek poljskega graha (P. sativum subsp. arvense (L.) Asch.) Kazem GHASSEMI-GOLEZANI, Javad BAKHSHI, Bahareh DALIL 225 Rate and duration of seed filling and yield of soybean affected by water and radiation deficits Pomanjkanje vode in svetlobe vplivata na hitrost in trajanje polnenja semen in pridelek soje Homa MAHMOODZADEH, Mohsen GHASEMI, Hasan ZANGANEH 233 Allelopathic effect of medicinal plant Cannabis sativa L. on Lactuca sativa L. seed germination Alelopatičen učinek konoplje (Cannabis sativa L.) na kalitev semen vrtne solate (Lactuca sativa L.) Saeed FIROUZI 241 Grain, milling, and head rice yields as affected by nitrogen rate and bio-fertilizer application Vpliv gnojenja z različnimi odmerki dušikovih gnojil in bio-gnojil na pridelek zrnja in mlevske lastnost riža Maryam GOLABADI, Pooran GOLKAR, Mohammad Reza SHAHSAVARI 249 Genetic analysis of agro-morphological traits in promising hybrids of sunflower (Helianthus annuus L.) Genetska analiza agro-morfoloških lastnosti pri obetajočih križancih navadne sončnice (Helianthus annuus L.) Billal NIA, Naama FRAH, Imane AZOUI 261 Insecticidal activity of three plants extracts against Myzuspersicae (Sulzer, 1776) and their phytochemical screening Insekticidno delovanje izvlečkov treh rastlin na listno uš Myzus persicae (Sulzer, 1776) in njihova fitokemična analiza Vajihe AMINI, Faezeh ZAEFARIAN, Mohammad REZVANI 269 Effect of pre-chilling and environmental factors on breaking seed dormancy and germination of three foxtail species Učinki hladnega predtretiranja in okoljskih dejavnikov na prekinitev dormance in kalitev treh vrst muhvičev Tjaša POGAČAR, Lučka KAJFEŽ-BOGATAJ 279 Simulation of herbage yield and growth components of Cock's foot (Dactylisglomerata L.) in Jablje using the calibrated LINGRA-N model Simulacija pridelka zelinja in komponet rasti navadne pasje trave (Dactylis glomerata L.) v Jabljah z umerjenim modelom LINGRA-N Hamid SALEHIAN, Maryam NAJAFIAN 293 Study of relationship between soybean (Glycine max (L.) Merr.)planting spatial arrangements and velvetleaf (Abutilon theophrasti L.) population dynamic Preučevanje razmerja med prostorsko ureditvijo setve soje (Glycine max (L.) Merr.) in populacijsko dinamiko bržunastega oslezovca (Abutilon theophrasti L.) Judita BYSTRICKÄ, Petra KAVALCOVÄ, Janette MUSILOVÄ, Alena VOLLMANNOVÄ, Tomaš TÓTH, Marianna LENKOVÄ 303 Carrot (Daucus carota L. ssp. sativus (Hoffm.) Arcang.) as source of antioxidants Korenje (Daucus carota L. ssp. sativus (Hoffm.) Arcang.) kot vir antioksidantov G. R. MOHAMMADI, S. CHATRNOUR, S. JALALI, D. KAHRIZI 313 The effects of planting arrangement and phosphate biofertilizer on soybean under different weed interference periods Učinki načinov setve in uporabe fosforjevih bio-gnojil na pridelek soje od časovno različnih zatiranj plevelov Tanja BOHINC, Stefan SCHMIDT, Juan Carlos MONJE, Stanislav TRDAN 323 Prva najdba parazitoidne ose Trichogramma brassicae Bezdenko, 1968 (Hymenoptera, Trichogrammatidae) v Sloveniji First record of parasitic wasp Trichogramma brassicae Bezdenko, 1968 (Hymenoptera, Trichogrammatidae) in Slovenia Žiga LAZNIK, Stanislav TRDAN 329 Možnosti okoljsko sprejemljivega zatiranja ameriškega škržatka (Scaphoideus titanus Ball, 1932) Possibilities of environmentally acceptable control methods of American Grapevine Leafhopper (Scaphoideus titanus Ball, 1932) Maja PODGORNIK, Dunja BANDELJ 337 Deficitni princip namakanja oljčnih nasadov v Slovenski Istri Deficit irrigation principles applied to olive orchard in Slovene Istria Zlata LUTHAR 345 Namerno sproščanje gensko spremenjenih rastlin v okolje v Sloveniji Deliberate release of genetically modified plants into the environment in Slovenia Tomaž BARTOL, Karmen STOPAR 355 Content analysis of the papers in the Acta agriculturae Slovenica Vsebinska obdelava prispevkov v Acta agriculturae Slovenica let. 105 št. 2 359 Navodila avtorjem Notes for authors COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.01 Agrovoc descriptors: drought stress, drought, photosynthesis, slenium, water supply, wheats, organic compounds, pigments, field experimentation, protected cultivation Agris category code: f06,f60 Influence of selenium in drought-stressed wheat plants under greenhouse and field conditions Roghieh HAJIBOLAND1, Noushin SADEGHZADEH2, Nashmin EBRAHIMI2, Behzad SADEGHZADEH3 and Seyed Abolgasem MOHAMMADI4 Received February 08, 2015; accepted May 19, 2015. Delo je prispelo 08. februarja 2015, sprejeto 19. maja 2015. ABSTRACT Effects of selenium (Na2SeO4) was studied in two wheat genotypes under well-watered and drought conditions in greenhouse (15 ^g Se L-1) and field (20-60 60 g ha-1) experiments. Application of Se improved dry matter and grain yield under both well-watered and drought conditions. Se increased leaf concentration of pigments and photosynthesis rate under both well-watered and drought conditions. Our results indicated that Se alleviates drought stress via increased photosynthesis rate, protection of leaf photochemical events, accumulation of organic osmolytes and improvement of water use efficiency. Under well-watered condition, Se-mediated growth improvement was associated with higher photosynthesis rate and water use efficiency, greater root length and diameter, and higher leaf water content. Key words: Drought, Organic osmolytes, Photosynthesis rate, Selenium, Water relations, Wheat IZVLEČEK VPLIV SELENA NA PŠENICO V SUŠNEM STRESU V RASTLINJAKU IN NA POLJU Raziskovan je bil vpliv selena (Na2SeO4) na rastline dveh genotipov navadne pšenice, v sušnih razmerah oziroma pri dobri oskrbi z vodo, v rastlinjaku (15 ^g Se L-1) in na polju (20-60 60 g ha-1). Dodatek Se je povečal sušino rastlin in pridelek zrnja pri obeh načinih oskrbe z vodo. Se je vplival na povečano koncentracijo pigmentov in na povečanje fotosinteze listov pri obeh oskrbah z vodo. Rezultati kažejo, da dodatek Se omili vpliv sušnega stresa s povečanjem fotosinteze, zaščito lista s fotokemičnimi procesi, akumulacijo organskih ozmotikov in povečano učinkovitostjo porabe vode. V razmerah dobre oskrbe z vodo je bila povečana rast, omogočena z dostopnostjo selena, povezana z intenzivnejšo fotosintezo in večjo učinkovitostjo uporabo vode, daljšimi in debelejšimi koreninami in večjo vsebnostjo vode. Ključne besede: suša, organski ozmotiki, fotosinteza, selen, vodna oskrba, pšenica 1 INTRODUCTION Plants often encounter unfavorable conditions, which interrupts their growth and productivity. Among the various abiotic stresses, drought is the major factor that limits crop productivity worldwide (Tardieu et al., 2014). Inadequate water availability during the life cycle of a crop species restricts the expression of its full genetic potential. Most of the crops are sensitive to water deficits, particularly during flowering to seed development stages. Even drought-tolerant crops are adversely 1 Associate Professor of Plant Physiology, Plant Science Department, University of Tabriz, 51666-14779 Tabriz, Iran 2 M.Sc. of Plant Physiology, Plant Science Department, University of Tabriz, 51666-14779 Tabriz, Iran 3 Assistant Professor of Crop Molecular Breeding, Dryland Agricultural Research Institute (DARI), Maragheh, P.O. Box 119, Iran 4 Professor of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Tabriz, 51666-14779 Tabriz, Iran This paper is a part of the PhD thesis of N.E. under supervision of R.H. affected by water scarcity at reproductive stage (Mitra, 2001). One of the initial responses to water deficiency is stomatal closure that depresses in turn photosynthesis and ability of plants for dry matter production (Chaves et al., 2009; Farooq et al., 2009). Drought-induced reduction of photosynthetic activity, however, is linked also to non-stomatal mechanisms, i.e. reduction of enzyme activities (Chaves et al., 2009). Down-regulation of photosynthetic carbon metabolism leads, in turn, to generation of excess excitation energy and formation of reactive oxygen species that induce damages to photosy stems (Hajiboland, 2014). The relative contribution of stomatal and non-stomatal limitations of photosynthesis depends on the severity of water stress and plants susceptibility to desiccation (Chaves et al., 2009). Plants respond and adapt to water deficit by the accumulation of osmolytes and proteins specifically involved in stress tolerance (Krasensky and Jonak, 2012). These molecules are accumulated in plant cells in response to drought stress and act as osmotic balancing agents. In addition of roles in osmotic homeostasis, these organic solutes are free radical scavengers and protect cell structures and membranes against desiccation damages (Krasensky and Jonak, 2012). Synthesis of osmoprotectants, osmolytes or compatible solutes including amino acids particularly proline and soluble carbohydrates is one of the mechanisms for adaptation to water deficit (Verbruggen and Hermans, 2008). Stress tolerance are controlled also by developmental and morphological traits such as root thickness, the ability of roots to penetrate compacted soil layers, and root depth and mass (Valliyodan and Nguyen, 2006). To improve production efficiency of crop plants under drought conditions, development of more tolerant genotypes using breeding strategies are necessary (Mitra, 2001; Valliyodan and Nguyen, 2006). Alternatively, exogenous application of various growth regulators (jasmonate and salicylate) and some osmoprotectants (e.g. glycine betaine) has proven worldwide in inducing drought tolerance at various growth stages (Farooq et al., 2009). Among mineral compounds, application of silicon (Liang et al., 2007) and selenium (Se) (Feng et al., 2013) attracted much more attention. Influence of low concentrations of Se in the amelioration of various abiotic stresses such as salt, UV radiation and drought stresses has been reported for various plant species (Hajiboland, 2012; Feng et al., 2013). Mechanisms for alleviating effect of Se on drought have mainly focused on the Se-mediated activation of antioxidative defense (Wang, 2011; Hasanuzzaman and Fujita, 2011; Hajiboland, 2012; Feng et al., 2013). However, Se-mediated changes in water relation parameters, accumulation of osmoticums and water uptake capacity under drought remain largely unknown and the obtained results are contradictory. Se application was reported to increase the accumulation of proline (Yao et al., 2009) while did not affect water uptake capacity (Habibi, 2013) and did not influence plant biomass under drought (Yao et al., 2009; Habibi, 2013). Wheat (Triticum aestivum L.) is one of the most important staple food crops and its productivity is adversely affected by drought particularly in arid and semi arid regions of the world. It has been estimated that about 50 % of the 237 million ha area in the world under wheat cultivation is affected by periodic drought (Ashraf, 2010). Effect of Se on the mitigation of drought stress in wheat plants has not been studied under field conditions. On the other hand, considering Se as a necessary element for animals and humans, fortification of grains with Se may contribute to an increase in Se intake for humans particularly in the countries where soil Se is low (Lyons et al., 2003). This work was aimed at studying the effect of Se application on the amelioration of drought stress in wheat genotypes. Some physiological parameters such as gas exchange, water relations and osmolyte accumulation were studied in this crop species in the pot and field experiments in order to compare Se effect as related to growth conditions and developmental stages. 2 MATERIALS AND METHODS 2.1 Plants materials Two common winter wheat (Triticum aestivum L.) genotypes 'Homa' (drought-tolerant) and 'Sara-BW-F6-06-85-86-29-1' (drought-sensitive) were used in both pot experiment and field study. Seeds were provided by Dryland Agricultural Research Institute (DARI) (Maragheh, Iran). 2.2 Pot experiment Seeds were surface-sterilized and germinated on perlite. Five-days-old seedlings were transferred into 1.5 L pots (40 plants per pot) filled with acid-washed perilte irrigated with 200 ml week-1 of 50 % wheat nutrient solution (Hajiboland et al., 2003). Se and irrigation treatments were started 9 days after transplanting, treatments were assigned randomly to the pots. Se treatments at two levels including without and with (15 ^g L-1) Se (as Na2SeO4) were applied gradually during 4 weeks. Simultaneously, irrigation treatments included well-watered (irrigation at field capacity) and drought stress (irrigation at 20 % FC) were started by omitting watering from drought treatments. One week after withholding watering, pots reached the 20 % FC. Throughout the experiment, pots were irrigated daily after weighing with nutrient solution or water as interval. Control and water-stressed plants received the same amount of nutrient solution and the respective FC was achieved by different volumes of water. Plants were grown under greenhouse conditions with a day/night temperature regime of 25-28/15-17°C, a relative humidity of 70/80 % and a photoperiod of 17/7 h at a photon flux density of about 300 ^mol m"2s_1 provided by natural light supplemented with fluorescent lamps. Eight weeks after starting Se treatments (7 weeks after reaching the respective FC, 10 weeks after sowing) plants were harvested. Shoot and roots were separated, roots were washed with distilled water and blotted dry on filter paper and their fresh weight (FW) were determined. Plants dry weight (DW) was determined after drying in 70°C for 48 h. Subsamples from leaves and roots were taken for biochemical analyses before drying. Change in the root morphology in Se-treated plants was visually observed at harvest. For its quantification, the root system of each pot was spread out in a tray filled with distilled water. Thereafter, root length was determined according to the line intersect method (Tennant, 1975) and the root diameter was determined using a micrometer in 50 randomly-selected parts of root system of each replicate pot and the average of obtained data was calculated. 2.3 Field experiment Field experiment was conducted during the 20122013 growing season at the Research Station of Faculty of Agriculture, University of Tabriz. At the beginning of the season (fall of 2012), the experimental area was prepared and soil samples were taken at a depth of 30 cm and analyzed for main soil properties. Soil properties before planting were 76 % sand, 18 % silt, and 6 % clay; 2.1 % organic matter; pH 8.7, EC 33.3 (soil:water, 1:1); 5.0 NO3-N, 36 P and 480 K in mg kg-1 soil. Plot dimensions were 1.5 m*3.0 m containing 5 rows. Seeds of two genotypes were planted by hand in rows and covered with soil. Approximately 60 seeds per row and 300 seeds per plot were planted on 20 October 2012. Weeds were controlled by hand as required. Nitrogen was added at a rate of 60 kg N ha-1 as urea in 08 April 2013. Control and drought-exposed plots were grown under rainfed conditions and supplemental irrigation applied for three times: one day and two weeks after planting and on 08 April 2013. Thereafter, drought was imposed by water withholding while control plots were irrigated weekly up to two weeks before harvest. Soil humidity (%) was estimated in samples collected weekly from drought-imposed plots at 10 cm simultaneous with irrigation of control plots. Soil relative humidity was 12.79±1.2 at the start of withholding irrigation and decreased to 3.52±0.21 at two weeks before harvest without significant difference among plots. Selenium (as Na2SeO4) was sprayed on the leaves at the concentrations of 1 and 3 ^g L-1 with the final amounts of 20 ^g ha-1 (Sei) and 60 ^g ha-1 (Se2) respectively, in the mornings before sunrise. Control plots (-Se) were sprayed with distilled water. The first foliar Se treatment was applied 6 weeks after planting. In spring, four subsequent Se treatments each with 3 weeks interval starting on 09 April 2013 were applied. At maturity (15 July 2013), plants of each experimental plot were harvested. The harvested material was sun-dried, threshed manually, and weighed for total biomass, grain yield and elemental analyses. Yield components (heads per plant, grains per head, and grain weight) were measured on ten plants that were sampled randomly from the two middle rows of each plot at maturity and added to the total. For determination of K, Ca and P, oven dried leaf samples were ashed in a muffle furnace at 550°C for 8 h, resolved in HCl, and made up to volume by distilled water. Concentrations of K and Ca were determined by flame photometry (PFP7, Jenway, UK) and P by a spectrophotometer (Specord 200, Analytical Jena, Germany) (Jaiswal, 2004). 2.4 Measurement of chlorophyll fluorescence and gas exchange parameters Chlorophyll (Chl) fluorescence parameters were measured in the pot experiment at harvest using a portable fluorometer (OSF1, ADC Bioscientific Ltd., UK). Leaves were acclimated to dark for 30 min using leaf clips before taking the measurements for dark-adapted leaves. Maximum quantum yield of PSII (Fv/Fm) was calculated using initial (F0), maximum (Fm) and variable (Fv=Fm— F0) fluorescence parameters. Calculations for light-adapted leaves were undertaken using initial (Ft), steady-state (Fs), maximum (F'm), variable (F'v=F'm-Ft), OPSn (F'm Ft/F'm) and F'0 [F'0=F0/(Fv/Fm)+(F0/F'm)] fluorescence for excitation capture efficiency of open PSII (F'v/F'm), photochemical quenching (qP) [(F'm—Fs)/(F'm— F'0)], non-photochemical quenching (qN) [1- (F'm— F'0)/(Fm-F0)] OPSII (F'm—Ft/F'm) and electron transport rate (ETR) [OPSIIxPFDx0.84x0.5] (Krall and Edwards, 1992). Gas exchange parameters were measured with a calibrated portable gas exchange system (LCA-4, ADC Bioscientific Ltd., UK) between 10:00 and 13:00. Measurements in the field experiment were undertaken one day after the last Se application (28 May 2013) in the young and flag leaves. In the greenhouse experiment, gas exchange parameters were measured at three time intervals: 4, 6 and 8 weeks after starting treatments. The measurements were conducted with photosynthetically active radiation (PAR) intensity at the leaf surface of 300400 ^mol m-2 s-1 in the pot experiment and 800900 ^mol m-2 s-1 in the field experiment. The net photosynthetic rate by unit of leaf area (A, ^mol CO2 m-2 s-1), transpiration rate (E, mmol H2O m-2 sand the stomatal conductance to water vapor (gs, mol m-2 s-1) were calculated using the values of CO2 and humidity variation inside the chamber, both measured by the infrared gas analyzer of the photosynthesis system. Instant water use efficiency (iWUE) was calculated as the ratio of photosynthesis: transpiration (^mol mmol-1). 2.5 Determination of osmotic potential and relative water content Osmotic potential was determined in the leaf and root samples using an osmometer (Heman Roebling Messtechnik, Germany). Relative water content (RWC%) was measured in the leaves and calculated according to the formula: (FW-DW)/(TW-DW)x100. For determination of turgid weight (TW), leaf disks (5mm diameter) were submerged for 18 h in distilled water, thereafter, they were blotted dry gently on a paper towel and weighed. 2.6 Biochemical determinations Leaf concentration of Chl a, b and carotenoids (Car) were determined according to Lichtenthaler and Wellburn (1985). Determination of anthocyanins was performed using a pH differential method at pH 1 and pH 4.5 in the methanol/HCl (98:2, v/v) extract and was expressed as mg of cyanidine-3-glucoside g-1 FW (Giusti and Wrolstad, 2001). Total flavonoids content was determined in the methanol extract of leaves using AlCl3-metanol (2 %, w/v) as indicator at 510 nm and quercetin (Sigma) as standard (Grayer, 1989). For determination of non-structural carbohydrates, samples were homogenized in 100 mM phosphate buffer (pH 7.5) at 4 oC, after centrifugation at 12000 g for 15 min, supernatant was used for determination of total soluble sugars whereas the pellets were kept for starch analysis (Yemm and Willism, 1954). Total soluble proteins were determined using a commercial reagent (Bradford reagent, Sigma) and bovine albumin serum (BSA) as standard. Content of total free a-amino acids was assayed using a ninhydrin colorimetric method (Yemm and Cocking, 1955). Glycine was used for standard curve. For determination of proline, samples were homogenized with 3% sulfosalicylic acid and the homogenate was centrifuged at 3000 g for 20 min. The supernatant was treated with acetic acid and acid ninhydrin, boiled for 1 h, and then absorbance at 520 nm was determined. Proline (Sigma) was used for production of a standard curve (Bates et al., 1973). 2.7 Experimental design and statistical analyses Pot experiment was undertaken in randomized block design with four replications as four independent pots. Field experiment was arranged in a split-plot-factorial design with four replicates. Watering treatments were the main-plots with Se treatments (-Se, Se1 and Se2) and genotypes combinations as sub-plots. Differences between the means were detected according to Tukey's test (p<0.05) using Sigma Stat 2.03 software. 3 RESULTS Plants fresh and dry matter production was adversely affected by drought under greenhouse conditions (Table 1). Reduction of shoot and root dry weight was 50 % and 29 % in drought tolerant variety 'Homa' and 68 % and 17 % in drought sensitive line 'Sara', respectively. Root length and diameter were also lower in drought-stressed plants. Se application improved all the growth parameters in control plants of both genotypes. In drought-stressed plants, however, effect of Se was significant only for shoot DW and root diameter in 'Homa'. Contrastingly, Se-treated plants tended to have slightly lower root length under drought conditions in both genotypes (Table 1). Under field conditions, drought stress declined all yield components. Reduction of whole shoot and straw biomass under drought was 40% and 44% in 'Homa', respectively, whereas it was more in 'Sara' (53 % and 56 %, respectively). For reproductive plant parts, yield depression was 23 % and 39 % for spike and seed in 'Homa' respectively, whereas the corresponding values for 'Sara' were 51 % and 54 % (Table 2). Se treatment increased plants growth parameters mainly under well-watered conditions without significant difference between two levels of applied Se. However, these effects were mainly in tendency, and significant changes were observed only for whole shoot and straw weight in 'Homa' (Table 2). Table 1: Fresh and dry weight (mg plant-1) of shoot and root, root length (mm plant-1) and diameter (mm) in two wheat genotypes grown under control (100 % FC) and drought (20 % FC) conditions in the absence (-Se) or presence (+Se) of Se (15 ^g Se L-1 as Na2SeO4) for 10 weeks in greenhouse. Treatments Shoot FW Shoot DW Root FW Root DW Root length Root diameter 'Homa' Control -Se 539±19b 119±7b 299±36b 52±6ab 6.07±0.58 b 0.21±0.009b +Se 592±28a 132±6a 346±18a 60±4a 7.50±0.72 a 0.30±0.003 a Drought -Se 155±10c 60±5 d 89±12c 37±9c 2.65±0.57 c 0.13±0.006c +Se 163±22c 73±3 c 93±11c 39±8bc 2.57±0.21 c 0.21±0.005b 'Sara' Control -Se 566±53b 151±15a 322±47b 69±8ab 7.49±0.42 b 0.18±0.005c +Se 663±42a 168±13a 456±14a 81±9a 7.79±0.34 a 0.33±0.006a Drought -Se 126±15c 49±12b 123±25c 57±5b 2.69±0.39 c 0.14±0.002d +Se 153±26c 60±8 b 136±24c 63±5b 2.10±0.28 c 0.28±0.001b Data of each column within each genotype indicated by the same letter are not statistically different (P<0.05) Table 2: Various growth parameters including yield of whole shoot, straw, spike and seed (g plant-1) and weight of 1000 seeds (g) in two wheat genotypes grown under control (well-watered) and drought stress conditions without (-Se) or with two levels of foliar-applied Se (Se1: 20 g ha-1 and Se2: 60 g ha-1) (as Na2SeO4) under field conditions. Treatments Whole shoot Straw Spike Seed 1000 seeds 'Homa' -Se 19.7±1.6 c 8.9±1.0b 1.07±0.07a 7.62±0.72a 48.08±3.97a Control Se1 21.5±1.7 ab 9.9±0.4ab 1.15±0.13a 8.28±0.68a 50.38±4.68a Se2 23.7±1.9 a 12.8±1.2a 1.09±0.16a 8.08±0.75a 44.71±3.82a -Se 11.8±1.1 d 5.0±1.0c 0.68±0.11b 4.63±0.39b 35.97±2.29b Drought Se1 12.9±0.7 d 5.4±0.4c 0.74±0.04b 5.14±0.25b 36.37±2.27b Se2 13.0±1.2 d 5.5±1.1c 0.75±0.21b 4.92±2.10b 37.68±3.31b 'Sara' -Se 22.8±2.7 a 8.4±1.2ab 1.44±0.16a 10.68±0.61 a 37.57±1.94a Control Se1 25.7±2.4 a 10.4±2.3 a 1.53±0.13a 11.20±0.97 a 38.93±2.42a Se2 23.2±2.8 a 11.7±3.9a 1.14±0.18a 9.70±0.94a 38.06±2.21a -Se 10.7±1.8 b 3.7±1.1c 0.70±0.11a 4.89±0.71b 27.41±3.18b Drought Se1 13.2±1.5 b 5.4±0.7bc 0.77±0.08a 5.16±0.56b 28.67±3.40b Se2 13.2±1.3 b 5.5±1.0bc 0.77±0.13a 4.76±0.96b 27.30±1.38b Data of each column within each genotype indicated by the same letter are not statistically different (P<0.05) In general, leaf Chl a, b and Car concentrations were higher in drought-stressed plants being significant for Chl a and b in 'Homa'. In contrast, concentrations of anthocyanins were declined by drought treatment in both genotypes and that of flavonoids in 'Homa' (Table 3). Se treatment increased consistently concentrations of all leaf pigments. Compared with -Se treatment, the effect of Se application was much more pronouncedly observed for leaf anthocyanins under both well-watered and drought conditions being about 2.2 and 3.5 folds higher in 'Homa' and 'Sara', respectively. Se affected also significantly Chl a, b in 'Homa' and flavonoids in 'Sara' (Table 3). Leaf Chl fluorescence parameters were affected by drought condition particularly in 'Homa' (Table 4). Maximum (Fv/Fm) and actual (F'^/F'n) efficiency of PSII and electron transport rate (ETR) were significantly lowered by drought stress in 'Homa'. Se treatment increased significantly Fv/Fm and ETR as well as non-photochemical quenching (qN) in 'Homa' under drought stress (Table 4). Table 3: Concentration of leaf pigments (mg g-1 FW) in two wheat genotypes grown under control (100 % FC) and drought (20 % FC) conditions in the absence (-Se) or presence (+Se) of Se (15 ^g Se L-1 as Na2SeO4) for 10 weeks in greenhouse. Treatments Chl a Chl b Car Anthocyanins Flavonoids 'Homa' Control -Se +Se 1.66±0.32 b 2.29±0.30 a 0.81±0.05b 0.94±0.05a 0.50±0.08a 0.52±0.07a 7.98±1.46ab 9.78±2.75a 5.65±0.44a 5.87±0.34a Drought -Se +Se 2.31±0.11 a 2.53±0.18 a 0.98±0.07a 1.05±0.06a 0.57±0.03a 0.60±0.05a 2.30±1.30c 5.28±1.28bc 3.78±0.08c 4.88±0.24b 'Sara' Control -Se +Se 2.06±0.30 b 2.13±0.19 ab 0.88±0.05a 0.93±0.02a 0.46±0.08a 0.49±0.04a 9.35±2.83bc 18.0±2.53a 3.10±0.14c 4.51±0.24b Drought -Se +Se 2.25±0.21 ab 2.55±0.17 a 0.90±0.07a 0.98±0.08a 0.53±0.06a 0.57±0.05a 4.01±1.35c 13.89±3.74 ab 4.21±0.33b 5.50±0.07a Data of each column within each genotype indicated by the same letter are not statistically different (P<0.05) Table 4: Chlorophyll fluorescence parameters: Fv/Fm (maximum quantum efficiency of PSII), F'JF'm (excitation energy capture of PSII), qP (photochemical quenching), qN (non-photochemical quenching) and ETR (electron transport rate) in two wheat genotypes grown under control (100 % FC) and drought (20 % FC) conditions in the absence (-Se) or presence (+Se) of Se (15 ^g Se L-1 as Na2SeO4) for 10 weeks in greenhouse. Treatments Fv/Fm F v/F m qP qN ETR 'Homa' Control -Se +Se 0.86±0.00 a 0.86±0.00 a 0.75±0.00a 0.76±0.01a 0.99±0.02a 0.98±0.03 a 0.07±0.04 b 0.09±0.02 b 124±3a 125±2a Drought -Se +Se 0.84±0.01 b 0.86±0.01 a 0.72±0.02b 0.72±0.01b 0.99±0.01a 0.98±0.01a 0.12±0.08 b 0.25±0.05 a 117±3b 120±3a 'Sara' Control -Se +Se 0.86±0.01 a 0.87±0.01 a 0.73±0.01a 0.74±0.01a 0.98±0.02a 0.95±0.03 a 0.15±0.03 a 0.20±0.02 a 122±2a 118±5 ab Drought -Se +Se 0.85±0.02 a 0.85±0.02 a 0.72±0.01a 0.72±0.01a 0.95±0.02a 0.98±0.01a 0.16±0.03 a 0.21±0.04 a 117±2 ab 115±2b Data of each column within each genotype indicated by the same letter are not statistically different (P<0.05) Four weeks after starting treatments, a significant reduction of stomatal conductance was observed only in 'Homa'. Expectedly, transpiration rate was also lowered by drought stress but these changes were not statistically significant. In contrast, reduction of net photosynthesis rate by drought stress was significant in both genotypes (Table 5). Se treatment in well-watered plants increased stomatal conductance, transpiration and photosynthesis rates in 'Homa' while decreased the latter parameter in 'Sara'. In drought-stressed plants Se application caused reduction of net assimilation rate in both genotypes (Table 5). Under long-term (6 and 8 weeks) drought stress, however, stomatal conductance and transpiration rates were significantly lowered in both genotypes. Se application increased all gas exchange parameters slightly or significantly in both genotypes. Eight weeks after starting treatments, leaf photosynthesis rate was increased by Se up to 23 % and 120 % in drought-stressed 'Homa' and 'Sara', respectively (Table 5). Gas exchange parameters under field conditions responded in the same way as observed in the pot experiment (Table 6). Stomatal conductance was significantly lowered by drought stress in both young and flag leaves. A significant reduction of transpiration rate under drought stress, however, was observed only in the young and flag leaves of 'Sara'. Se-treated plants had higher stomatal opening and transpiration rate particularly in the flag leaves and two application levels of Se did not differ in this regard. Net assimilation rate was affected by both drought and Se treatments more pronouncedly than other two parameters. Both young and flag leaves had lower photosynthesis rate under drought irrespective to the level of Se treatments. In turn, Se application resulted in significantly higher photosynthesis under both watering treatments and in both genotypes. In contrast to stomatal conductance and transpiration rate, effect of higher Se concentration (60 g ha-1) on the elevation of photosynthesis was greater than that of lower Se concentration (20 g ha-1) (Table 6). Furthermore, the extent of Se effect on the increases in leaf photosynthesis of drought-stressed plants was higher under field conditions and reached up to 162 % and 179 % in the young leaves and 191 % and 202 % in the flag leaves of 'Homa' and 'Sara', respectively. Table 5: Gas exchange parameters including net assimilation rate (A, ^mol m-2 s-1), transpiration rate (E, mmol m-2 s-1) and stomatal conductance (gs, mol m-2 s-1) in two wheat genotypes grown under control (100 % FC) and drought (20 % FC) conditions in the absence (-Se) or presence (+Se) of Se (15 ^g Se L-1 as Na2SeO4) at three measurement intervals in greenhouse. A E A E gs Treatments 'Homa' 'Sara' 4 weeks after starting treatments Control -Se 13.71±0.91 b 2.08±0.70b 0.50±0.09a 15.09±0.02a 1.42±0.09 b 0.23±0.16b +Se 15.80±0.45 a 4.70±0.26a 0.58±0.13a 12.81±0.30b 2.58±0.14 a 0.70±0.18a Drought -Se 11.96±0.32 c 1.42±0.27bc 0.26±0.05b 11.06±0.33c 1.43±0.63 b 0.14±0.05b +Se 7.79±0.18bc 0.81±0.22c 0.10±0.04b 9.08±0.56d 1.16±0.40 b 0.21±0.08b 8 weeks after starting treatments Control -Se 15.69±0.18 b 1.58±0.11a 1.33±0.05a 10.33±0.30c 1.19±0.11 b 1.77±0.24a +Se 18.04±0.45 a 1.60±0.15a 1.41±0.17a 12.52±0.24a 1.57±0.06 a 1.91±0.12a Drought -Se 8.61±0.49d 0.93±0.05b 0.90±0.21b 9.91±0.48c 0.86±0.02 c 0.38±0.09b +Se 10.75±0.69 c 0.98±0.05ab 1.24±0.19ab 11.24±0.52b 0.91±0.04 c 0.57±0.08b 10 weeks after starting treatments Control -Se 16.70±0.54 b 1.52±0.34ab 1.49±0.14ab 8.85±0.13b 1.43±0.36 ab 1.94±0.68a +Se 19.02±0.36 a 1.72±0.48a 2.06±0.18a 13.01±0.45a 1.99±0.33 a 2.44±0.56b Drought -Se 5.86±0.13d 0.92±0.04b 0.67±0.14b 2.14±0.20d 0.78±0.11 c 0.10±0.03c +Se 7.20±0.44 c 0.97±0.06b 0.91±0.17b 4.71±0.44c 0.93±0.19 bc 0.11±0.06bc Data of each column within each measurement intervals indicated by the same letter are not statistically different (P<0.05) Table 6: Gas exchange parameters including net assimilation rate (A, ^mol m-2 s-1), transpiration rate (E, mmol m-2 s-1) and stomatal conductance (gs, mol m-2 s-1) in the young and flag leaves in two wheat genotypes grown under control (well-watered) and drought stress conditions without (-Se) or with two levels of foliar-applied Se (Se1: 20 g ha-1 and Se2: 60 g ha-1) (as Na2SeO4) under field conditions. A E gs A E gs Treatments 'Homa' 'Sara' Young leaf -Se 8.43±0.39c 1.55±0.90ab 0.35±0.04a 8.48±0.36c 1.21±0.17 ab 0.42±0.15ab Control Se1 11.95±0.38 b 1.86±0.37a 0.55±0.17a 13.14±0.72b 1.51±0.62 a 0.61±0.10a Se2 15.27±0.82 a 1.51±0.66ab 0.42±0.15a 15.98±0.66a 1.04±0.12 abc 0.43±0.13ab -Se 1.62±0.32f 0.39±0.07b 0.07±0.01 b 1.88±0.06e 0.44±0.10 c 0.23±0.15b Drought Se1 2.61±0.17e 0.81±0.41ab 0.09±0.04b 2.97±0.38e 0.53±0.09 c 0.30±0.19ab Se2 4.25±0.25d 0.84±0.48ab 0.14±0.02b 5.24±0.80d 0.68±0.09 bc 0.22±0.09b Flag leaf -Se 9.75±0.19c 0.71±0.06b 0.19±0.01bc 9.95±0.17c 0.65±0.09 b 0.24±0.05b Control Se1 12.0±0.12b 1.08±0.24ab 0.31±0.12ab 15.6±0.21b 0.94±0.08 a 0.49±0.16a Se2 14.9±0.54a 1.15±0.25a 0.34±0.08a 17.3±0.11a 0.91±0.09 a 0.48±0.14a -Se 1.51±0.17f 0.77±0.20b 0.06±0.03 c 1.75±0.15f 0.26±0.00 c 0.06±0.01b Drought Se1 3.55±0.22e 1.13±0.39ab 0.09±0.02c 4.40±0.05e 0.54±0.08 b 0.14±0.03b Se2 4.41±0.31d 1.56±0.11a 0.12±0.02c 5.28±0.42d 0.70±0.07 b 0.24±0.05b Data of each column within each type of leaf indicated by the same letter are not statistically different (P<0.05) Soluble protein concentration in the shoot was decreased slightly by drought treatment in 'Homa' while increased significantly in 'Sara' (Fig. 1A). In the roots, both genotypes had higher soluble proteins under drought conditions. Se treatment increased consistently soluble protein concentrations in the shoot and roots of both genotypes being significant in 'Homa' under drought and in 'Sara' under well-watered conditions (Fig. 1A). Similar with soluble proteins, shoot concentration of free amino acids decreased upon drought treatment in 'Homa' while increased significantly in 'Sara' (Fig. 1B). In the roots of both genotypes higher free a-amino acids concentration was found in drought-stressed plants compared with well-watered ones. Effect of Se treatment depended on the plant organ, it resulted in slightly lower free amino acids concentration in the shoot while the opposite was observed in the roots that was significant in drought-stressed plants (Fig. 1B). Expectedly, concentration of free proline was higher in the plants exposed to drought stress (Fig. 1C). This effect was more pronouncedly observed in 'Homa' compared with 'Sara' in both shoot and roots. Se effect on the shoot proline concentration of drought-stressed plants, however, differed between two genotypes. It decreased proline concentration of drought-stressed plants in 'Homa' whereas increased it in 'Sara'. In the roots, in contrast, both genotypes responded similarly to Se application as slightly or significantly lower proline concentration (Fig. 1C). Figure 1: Concentration of soluble proteins (A) (mg g-1 FW), total free a-amino acids (B) (^mol g-1 FW) and proline (C) (nmol g-1 FW) in the leaves (above of the horizontal lines) and roots (below of the horizontal lines) of two wheat genotypes grown under control (100 % FC) and drought (20 % FC) conditions in the absence (-Se, open bars) or presence (+Se, closed bars) of Se (15 ^g Se L-1 as Na2SeO4) for 10 weeks in greenhouse. Data of each column within each genotype indicated by the same letter are not statistically different (P<0.05) Concentration of soluble carbohydrates increased consistently by both drought stress and Se treatments in both genotypes in the shoot and roots (Fig. 2A). This led to the highest amount of soluble sugars in drought-stressed plants supplemented with Se. Root's concentration of starch showed the same pattern of changes in the soluble sugars concentration in response to the treatments. In the shoot, however, starch concentration was not affected by drought in both genotypes and increased by Se application only in 'Homa' under well-watered conditions. Figure 2: Concentration (mg g-1 FW) of soluble sugars (A) and starch (B) in the leaves (above of the horizontal lines) and roots (below of the horizontal lines) of two wheat genotypes grown under control (100 % FC) and drought (20 % FC) conditions in the absence (-Se, open bars) or presence (+Se, closed bars) of Se (15 ^g Se L-1 as Na2SeO4) for 10 weeks in greenhouse. Data of each column within each genotype indicated by the same letter are not statistically different (P<0.05). Expectedly, leaf and root osmotic potentials decreased by drought stress in both genotypes (Fig. 3A). Effect of drought on reduction of roots osmotic potential was more pronounced in 'Homa' than 'Sara'. Se-treated plants had consistently higher leaf osmotic potential that was significant in 'Homa' under drought and in 'Sara' under well- watered conditions. Surprisingly, Se effect on the root osmotic potential was the opposite of that observed for the shoot. A significant effect of Se on declining root osmotic potential was observed in 'Homa' grown under drought conditions (Fig. 3B). Figure 3: Leaf (A) and root (B) osmotic potentials (MPa) in two wheat genotypes grown under control (100 % FC) and drought (20 % FC) conditions in the absence (-Se, open bars) or presence (+Se, closed bars) of Se (15 ^g Se L-1 as Na2SeO4) for 10 weeks in greenhouse. Data of each column within each genotype indicated by the same letter are not statistically different (P<0.05) Leaf RWC increased significantly by Se application in 'Homa' under well-watered conditions and in 'Sara' under drought stress. Instant WUE declined under drought conditions in both genotypes and in greenhouse and field experiments. Se treatment, however, increased this parameter slightly or significantly, under both watering treatments (Table 7). Leaf concentration of K was lower in drought-stressed plants while that of Ca increased under these conditions in both genotypes. However, effect of drought on K concentration was not significant in 'Sara' (Table 8). Se application did not change K and Ca concentration in the leaves. In contrast to K and Ca, concentration of P in 'Homa' did not respond to drought while it was higher at higher Se application level (60 g ha-1) under both watering regimes. In 'Sara', however, Se did not affect significantly P concentration of leaves while it was slightly lower in drought-stressed plants compared with well-watered ones (Table 8). Table 7: Relative water content (RWC%) and instant water use efficiency (WUE, photosynthesis rate: transpiration rate) in two wheat genotypes grown under control or drought conditions in the absence (-Se) or presence (+Se) of added Se. Treatments RWC* WUE* WUE** RWC* WUE* WUE** 'Homa' 'Sara' Control -Se +Se 78.9±1.53 b 10.67±1.25ab 6.49±1.52b 84.7±1.35a 6.24±0.98 a 7.07±0.76b 89.6±1.94 a n.n±1.98a 11.59±2.67a 86.1±1.09a 6.61±0.42 a 15.47±1.77a Drought -+SSee 75.1±0.74 c 6.31±0.98c 4.18±0.18b 70.9±1.61c 2.71±0.81 b 4.53±1.45b 77.0±1.92 bc 7.41±1.82bc 6.02±1.21b 75.0±1.94b 5.11±0.70 a 7.86±1.78b Data of each column indicated by the same letter are not statistically different (P<0.05) * Measured or calculated for plants grown in greenhouse 10 weeks after starting treatments ** Calculated for young leaves of plants grown in field at Se level of 60 ^g ha-1 Table 8: Concentration (mg g-1 DW) of K, Ca and P in the leaves of two wheat genotypes grown under control (well-watered) and drought conditions without (-Se) or with two levels of foliar-applied Se (Se1 : 20 g ha-1 and Se2: 60 g ha-1) (as Na2SeO4) under field conditions. Treatments K Ca P K Ca P 'Homa' 'Sara' Control -Se Se1 Se2 165±12a 165±13a 178±19a 4.82±0.53b 4.96±0.89b 4.91±0.52b 0.56±0.24b 0.58±0.10b 1.08±0.33a 195±16a 181±10ab 183±12ab 5.33±0.98 d 7.39±0.86 cd 5.52±0.80 d 0.78±0.20a 0.65±0.13ab 0.65±0.08ab Drought -Se Se1 Se2 128±18b 128±15b 132±2b 8.37±1.31a 9.48±1.92a 7.82±1.76a 0.35±0.03 b 0.37±0.08 b 1.16±0.11 a 171±11ab 163±17b 167±4b 10.6±1.73 bc 12.8±1.25 b 17.2±2.58 a 0.41±0.08b 0.43±0.11b 0.49±0.04b Data of each column indicated by the same letter are not statistically different (P<0.05) 4 DISCUSSION 4.1 Effect of drought and Se application on plants biomass Plants biomass was significantly influenced by drought stress under both greenhouse and field conditions. The comparison of two genotypes showed that 'Sara' was more susceptible to drought stress compared with 'Homa' considering vegetative and reproductive stages. It was consistent with the instruction of providing institute on the ranking of drought tolerance in these genotypes. Beside the loss of cell turgor and reduction of cell expansion, the main mechanism reduce crop yield under drought conditions is lowered canopy absorption of photosynthetically active radiation following prolonged stomatal closing (Farooq et al., 2009). Reduction of seed yield and weight under drought, in turn, is related to both source and sink limitations. Apart from source limitation due to reduction of photosynthesis and limited sucrose export to the reproductive sinks, lower capacity of developing seeds to utilize the incoming assimilates and enhanced endogenous abscisic acid concentration are potential factors contributing to reduction of seed yield and weight under drought (Farooq et al., 2009). Under well-watered conditions, Se application increased vegetative biomass of both genotypes in greenhouse. Effect of Se under field conditions, however, was significant only in 'Homa' and for vegetative but not reproductive growth parameters. Se at 20 g ha-1 could be regarded as optimum concentration because higher level (60 g ha-1) did not improve significantly the vegetative growth and reduced slightly reproductive growth parameters. Root diameter was significantly higher in Se-treated plants under well-watered and drought conditions. It has been demonstrated that larger diameter roots would confer drought resistance because they have greater xylem vessel radii and lower axial resistance to water flux, with great penetration ability (Gowda et al., 2011). Higher P (and partly K) concentration at higher Se application level (60 g ha-1) resulted likely from Se-mediated changes in the root morphology (length and diameter) that improved uptake of nutrients particularly those with higher dependency to spatial availability. 4.2 Effect of drought and Se application on leaf pigments, photochemistry and gas exchange Leaf concentrations of Chl (significantly) and Car (slightly) was higher in drought-stressed plants obviously because of a concentration effect following higher reduction of leaf weight and area but less destruction of Chl and Car. Reduction of leaf Chl concentration and damages to chloroplasts occur under drought stress when particularly associated with higher light intensity (Hajiboland, 2014). In our greenhouse experiment, drought stress in the absence of higher light intensity, was likely not effective for a high generation rate of reactive oxygen species, chloroplasts damages and Chl destruction. Nevertheless, anthocyanins and flavonoids concentrtaions rather decreased under water deficiency conditions. It implies that effect of leaf desiccation on the anthocyanins and flavonoids synthesis was much more than that for Chl and Car. The most prominent effect of Se on leaf pigments was observed for anthocynainns and flavonoids. Accumulation of anthocyanins is believed to protect the cellular structures from oxidative damage (Wahid and Ghazanfar, 2006). Plant tissues containing anthocyanins are usually tolerant to drought (Ichikawa et al., 2001). This protection is related to the superoxide radical scavenging activity of anthocyanins (Ichikawa et al., 2001) and their ability to stabilize the water potential (Chalker-Scott, 2002). The contribution of flavonoids to the antioxidant defense capacity of plants and its relevance in plant responses to drought have been widely accepted (Fini et al., 2011). Evidences showed that flavonoids constitute a secondary free radicals-scavenging system in plants exposed to severe and prolonged stress conditions (Fini et al., 2011). In contrast to growth parameters, leaf photochemical parameters were affected adversely by drought in 'Homa' but not in 'Sara'. The preservation of Chl fluorescence parameters in 'Sara' under drought conditions indicated that photochemical events conserved their normal activities in this genotype. Reduction of optimal photochemical efficiency of PSII in dark-adapted leaves (Fv/Fm) and excitation capture efficiency of light-adapted leaves (F'v/F'm) both indicated occurrence of photoinhibition and damage to PSII in 'Homa'. Environmental stresses such as drought and salinity reduce the activity of the Calvin cycle directly or indirectly, and result in a decline of NADP+ regeneration, thus, over-reduction of the electron transport chain and photoinhibition and dames to the photosystems (Hajiboland, 2014; Noctor et al., 2014). Amounts of F/Fm, F'v/F'm and ETR under drought conditions was completely returned by Se application to its control levels in 'Homa'. In addition, higher non-photochemical quenching (qN) in drought-stressed plants due to Se application observed in this study implied elevation of capacity for dissipation of excess absorbed energy as heat and thus more protection of photosynthetic apparatus (Müller et al., 2001). Stomatal conductance was decreased significantly 4 weeks after imposing drought in 'Homa' leading to lower transpiration rate in this genotype. This effect, however, was less pronouncedly observed in 'Sara' without reduction of transpiration rate. In the two following measurement intervals in greenhouse and field experiment, however, both genotypes showed similar reduction of stomatal conductance and transpirational water loss. Stomatal closure is a fast response of plants to water deficit allowing reduction of the transpiration rate and conservation of relative water content (Zhou et al., 2013). Reduction of stomatal conductance under drought decreased net assimilation rate that was significant at all measurement intervals in the greenhouse experiment and in both leaf types in the field experiment. In addition, reduction of CO2 availability for photosynthetic dark reactions may result in generation of excess excitation energy under drought conditions and causes damages to photosynthetic apparatus (Hajiboland, 2014) that was also reflected in Chl fluorescence parameters in this work. Se treatment influenced gas exchange parameters more prominently than photochemical events. In general, stomatal conductance, transpiration rate and particularly net assimilation rates were higher in Se-treated plants compared with plants without Se under both watering regimes. A significant elevation of net assimilation rate may explain growth improvement by Se not only under drought but also under well-watered conditions. Higher ability for CO2 fixation increases plants capability for dry matter production under well-watered and for osmolytes accumulation under drought conditions. However, significantly higher photosynthesis rate at 60 g ha-1 compared with application of lower Se (20 g ha-1) in well-watered plants was not associated with higher vegetative or reproductive growth parameters. Similarly, an elevated photosynthetic rate up to 3 fold did not result in significantly higher biomass in drought-stressed plants. Lack of a close relationship between photosynthesis rate and plants growth under both watering regimes suggested that there were some limiting factors e.g. low nutrients availability, which prevent maximum response of dry matter production to added Se. Mechanisms for Se-mediated increase in photosynthesis rate have not been studied in detail. Possible effect of Se on the H+-pumping and K+ currents in stomatal cells has not been characterized so far. In addition, non-stomatal mechanisms are also likely involved in the Se effect on photosynthesis. Through proteomic analysis, it was revealed that primary metabolism, photosynthesis and redox homeostasis are the most highly affected biological processes by Se treatments (Wang et al., 2012). Effect of Se on the activation of fructose 1,6 bisphosphatase in alfalfa (Owusu-Sekyere et al., 2013) and a concomitant activation of NO3- and CO2 assimilation rate in wheat (Hajiboland and Sadeghzadeh, 2014) have been previously reported. 4.3 Effect of Se application and drought on the organic osmolytes Increases in soluble proteins in both leaves and roots of Se-treated plants under both watering regimes that was associated with lower free a-amino acids in the leaves (but not in the roots) may imply depletion of amino acids pool following elevated protein synthesis by Se in the leaves. Lack of such depletion in the roots may be attributed to higher nitrate uptake and assimilation exceeding the requirement for protein synthesis in this organ. Our previous study showed that Se-treated plants have higher nitrate uptake and nitrate reductase activity being much more pronounced in the roots compared with the leaves (Hajiboland and Sadeghzadeh, 2014). Higher concentrations of soluble proteins and free amino acids under drought observed here may confer higher osmotic adjustment capacity and protect cell structures against desiccation (Krasensky and Jonak, 2012). Proline concentration was expectedly higher in drought-stressed plants whereas Se effect depended on plants organ and genotype. In the roots of both genotypes, Se treatment did not cause accumulation of proline despite lower root osmotic potential. It has been stated that, lower proline accumulation is mainly a reflection of an increased salt resistance in plants, i.e. less injury (Lutts et al., 1999). Here lower proline content of Se-treated plants under drought suggests that they were less strained due to some ameliorating mechanisms. In the leaves genotypic difference was observed in proline accumulation in response to Se. In another study, drought-stressed wheat had higher leaf proline concentration when exposed to Se (Yao et al., 2009). Desiccation-induced accumulation of soluble sugars observed in this work is a well-known response that is either the result of increased partitioning of photoassimilates to the synthesis of free sugars and/or enhanced starch degradation (Lee et al., 2008). Free soluble carbohydrates are effective compounds in osmotic homeostasis, protection of membranes and cell structures against dehydration and have free radicals scavenging activity (Niedzwiedz-Siegien et al., 2004). Se-mediated accumulation of soluble sugars and starch has previously been reported in lettuce (Pennanen et al., 2002) and potato (Turakainen et al., 2004). However, effect of Se application on this parameter under different water supply level and its role in drought tolerance has not been investigated so far. In this work, Se treatment increased concentration of soluble sugars in both leaves and roots of well-watered and drought-stressed plants. It may be primarily attributed to the higher photosynthesis and CO2 assimilation. This suggestion is confirmed by concomitantly higher starch concentration of Se-treated plants that in turn, excludes the contribution of starch degradation to the increased concentration of soluble sugars upon Se application. 4.4 Effect of Se application and drought on water relation parameters Se treatment increased leaf osmotic potentials while decreased it in the roots. Such differential effect of Se on leaf and root osmotic potentials may be resulted from higher root-shoot water transport that could be related in turn, to higher root hydraulic conductivity in Se-treated plants. Root-to-leaf conductance declines during drought and have the greater influence under transpirational conditions compared with soil-to-root component of water pathway (Sperry, 2000). Much of the decline in root-to-shoot hydraulic conductance could be explained by xylem cavitation under drought (Sperry, 2000). Regarding changes in the root morphology and increase in the ratio of thick roots in the wheat plants of this study under Se treatment it could be speculated that hydraulic conductivity of whole root system was higher in Se-treated plants likely because of higher diameter of xylem conduits in the thick roots as was observed in the tick roots of rice (Gowda et al., 2011). To our best knowledge, there is no published work on the changes in water relation parameters as affected by Se in drought-stressed plants. Thus, comparison of our results with other works was not possible. Regardless of mechanism, elevation of leaf osmotic potential upon Se treatment may contribute significantly to the maintenance of biochemical reactions under drought. Lower root osmotic potential, in turn, may allow plants to take up water more efficiently from dry substrate. This parameter together with greater root diameter plays likely important roles for improvement of water uptake capacity in Se-treated plants. 5 REFERENCES Ashraf, M. 2010 Inducing drought tolerance in plants: Recent advances. Biotechnol. Adv. 28: 169-183, DOI: 10.1016/j.biotechadv.2009.11.005 Bates, L.S., Waldren, R.P., Teare, I.D. 1973. Rapid determination of free proline for water-stress studies. Plant Soil 39: 205-207, DOI: 10.1007/BF00018060 Chalker-Scott. L. 2002. Do anthocyanins function as osmoregulators in leaf tissues? Adv. Bot. Res. 37: 103-106, DOI: 10.1016/S0065-2296(02)37046-0 Chaves, M.M., Flexas, J., Pinheiro, C. 2009. Photosynthesis under drought and salt stress: regulation mechanisms from whole plant to cell. Ann. Bot. 103: 551-560.DOI: 10.1093/aob/mcn125 Farooq, M., Wahid, A., Kobayashi, N., Fuj ita, D., Basra, S.M.A. 2009. Plant drought stress: effects, mechanisms and management. Agron. Sustain. Dev. 29: 185-212, DOI: 10.1051/agro:2008021 Feng, R., Wei, C., Tu, S. 2013. The roles of selenium in protecting plants against abiotic stresses. Environ. Exp. Bot. 87: 58-68, DOI: 10.1016/j.envexpbot.2012.09.002 Fini, A., Brunetti, C., Di Ferdinando, M., Ferrini, F., Tattini, M. 2011. Stress-induced flavonoid biosynthesis and the antioxidant machinery of plants. Plant Signal. Behav. 6: 709-711, DOI: 10.4161/psb.6.5.15069 Giusti, M.M., Wrolstad, R.E. 2001. Characterization and measurement of anthocyanins by UV-Visible spectroscopy. In: Current Protocols in Food Analytical Chemistry. Wrolstad, R.E., Acree, T.E., An, H., Decker, E.A., Pennere, M.H., Reid, D.S., Schwartz, S.J., Shoemaker, C.F., Sporns, P. (eds.). New York, John Wiley: F1.2.1-F1.2.13, DOI: 10.1002/0471142913.faf0102s00 Gowda, V.R.P., Henry, A., Yamauchi, A., Shashidhar, H.E., Serraj, R. 2011. Root biology and genetic improvement for drought avoidance in rice. Field Crops Res. 122: 1-13, DOI: 10.1016/j.fcr.2011.03.001 Grayer, R.J. 1989. Flavonoids. In: Methods in Plant Biochemistry, Vol. 1, Plant Phenolics. Dey, P.M., Harborne, J.B. (eds.) London, academic Press: 283323. Habibi, G. 2013. Effect of drought stress and selenium spraying on photosynthesis and antioxidant activity of spring barley. Acta Agric. Slov. 101: 31-39, DOI: 10.2478/acas-2013-0004 Hajiboland, R. 2012. Effect of micronutrient deficiencies on plant stress responses. In: Abiotic Stress Responses in Plants. Ahmad, P., Prasad, M.N.V. (eds.). New York, Springer: 283-329, DOI: 10.1007/978-1-4614-0634-1_16 Hajiboland, R. 2014. Reactive oxygen species and photosynthesis. In: Oxidative Damage to Plants, Antioxidant Networks and Signaling. Ahmad, P. (ed.). New York, Springer: 1-63, 10.1016/B978-0-12-799963-0.00001-0 Hajiboland, R., Sadeghzadeh, N. 2014. Effect of selenium supplementation on CO2 and NO3-assimilation under low and adequate N supply in wheat (Triticum aestivum L.) plants. Photosynthetica, DOI: 10.1007/s11099-014-0058-1. Hajiboland, R., Yang, X.E., Römheld, V. 2003. Effects of bicarbonate and high pH on growth of Zn-efficient and Zn-inefficient genotypes of rice, wheat and rye. Plant Soil 250: 349-357, DOI: 10.1023/A: 1022862125282 Hasanuzzaman, M., Fujita, M. 2011. Selenium pretreatment upregulates the antioxidant defense and methylglyoxal detoxification system and confers enhanced tolerance to drought stress in rapeseed seedlings. Biol. Trace Element Res. 143: 1758-1776, DOI: 10.1007/s12011-011-8998-9 Ichikawa, H., Ichiyanagi, T., Xu, B., Yoshii, Y., Nakajima, M., Konishi, T. 2001. Antioxidant activity of anthocyanin extract from purple black rice. J. Med. Food 4: 211-218, DOI: 10.1089/10966200152744481 Jaiswal, P.C. 2004. Soil, plant and water analysis. New Delhi, Kalyani Publishers. Krall, J.P., Edwards, G.E. 1992. Relationship between photosystem II activity and CO2 fixation in leaves. Physiol. Plant. 86: 180-187, DOI: 10.1111/j.1399-3054.1992.tb01328.x Krasensky, J., Jonak, C. 2012. Drought, salt, and temperature stress-induced metabolic rearrangements and regulatory networks. J. Exp. Bot. 63: 1593-1608, DOI: 10.1093/jxb/err460 Lee, B.R., Jin, Y.L., Jung, W.J., Avice, J.C., Morvan-Bertrand, A., Ourrt, A., Park, C.W., Kim, T.H. 2008. Water deficit accumulates sugars by starch degradation-not by de novo synthesis-in white clover leaves (Trifolium repens). Physiol. Plant. 134: 403-411, DOI: 10.1111/j. 1399-3054.2008.01156.x Liang, Y.C., Sun, W., Zhu, Y-G., Christie, P. 2007. Mechanisms of silicon-mediated alleviation of abiotic stresses in higher plants: a review. Environ. Pollut 147: 422-428, DOI: 10.1016/j.envpol.2006.06.008 Lichtenthaler, H.K., Wellburn, A.R. 1985. Determination of total carotenoids and chlorophylls a and b of leaf in different solvents. Biol. Soc. Trans. 11: 591-592, DOI: 10.1042/bst0110591 Lutts, S., Majerus, V., Kinet, J.M. 1999. NaCl effects on proline metabolism in rice (Oryza sativa) seedlings. Physiol. Plant. 105: 450-458, DOI: 10.1034/j.1399-3054.1999.105309.x Lyons, G., Stangoulis, J., Graham, R. 2003. High-selenium wheat: biofortification for better health. Nutr. Res. Rev. 16: 45-60, DOI: 10.1079/NRR200255 Mitra, J. 2001. Genetics and genetic improvement of drought resistance in crop plants. Curr. Sci. 80: 758-763 Müller, P., Li, X.P., Niyogi, K.K. 2001. Non-photochemical quenching. A response to excess light energy. Plant Physiol. 125: 1558-1566, DOI: 10.1104/pp.125.4.1558 Niedzwiedz-Siegien, I., Bogatek-Leszczynska, R., Come, D., Corbineau, F. 2004. Effects of drying rate on dehydration sensitivity of excised wheat seedling shoots as related to sucrose metabolism and antioxidant enzyme activities. Plant Sci. 167: 879-888, DOI: 10.1016/j.plantsci.2004.05.042 Noctor, G., Mhamdi, A., Foyer, C.H.A. 2014. The roles of reactive oxygen metabolism in drought: not so cut and dried. Plant Physiol. 164: 1636-1648, DOI: 10.1104/pp.113.233478 Owusu-Sekyere, A., Kontturi, J., Hajiboland, R., Rahmat, S., Aliasgharzad, N., Hartikainen, H., Seppänen, M.M. 2013. Influence of selenium (Se) on carbohydrate metabolism, nodulation and growth in alfalfa (Medicago sativa L.). Plant Soil 373: 541-552, DOI: 10.1007/s11104-013-1815-9 Pennanen, A., Xue, T., Hartikainen, H. 2002. Protective role of selenium in plant subjected to severe UV irradiation stress. J. Appl. Bot. 76: 66-76 Sperry, J.S. 2000. Hydraulic constraints on plant gas exchange. Agric. Forest Meteorol. 104: 13-23, DOI: 10.1016/S0168-1923(00)00144-1 Tardieu, F., Parent, B., Caldeira, C.F., Welcker, C. 2014. Genetic and physiological controls of growth under water deficit. Plant Physiol. DOI:10.1104/pp.113.233353. Tennant, D. 1975. A test of modified line intersect method of estimating root length. J. Ecol. 63: 9951001, DOI: 10.2307/2258617 Turakainen, M., Hartikainen, H., Seppänen, M.M. 2004. Effects of selenium treatments on patato (Solanum tuberosum L.) growth and concentrations of soluble sugars and starch. J. Agric. Food Chem. 52: 53785382, DOI: 10.1021/jf040077x Valliyodan, B., Nguyen, H.T. 2006. Understanding regulatory networks and engineering for enhanced drought tolerance in plants. Curr. Opin. Plant Biol. 9: 1-7, DOI: 10.1016/j.pbi.2006.01.019 Verbruggen, N., Hermans, C. 2008. Proline accumulation in plants: a review. Amino Acids 35: 753-759, DOI: 10.1007/s00726-008-0061-6 Wahid, A., Ghazanfar, A. 2006. Possible involvement of some secondary metabolites in salt tolerance of sugarcane. J. Plant Physiol. 163: 723-730, DOI: 10.1016/j.jplph.2005.07.007 Wang, C.Q. 2011. Water-stress mitigation by selenium in Trifolium repens L. J. Plant Nutr. Soil Sci. 174: 276-282, DOI: 10.1002/jpln.200900011 Wang, Y.D., Wang, X., Wong, Y.S. 2012. Proteomics analysis reveals multiple regulatory mechanisms in response to selenium in rice. J. Proteomics 75: 1849-1866, DOI: 10.1016/j.jprot.2011.12.030 Yao, X.Q., Chu, J.Z., Wang, G.Y. 2009. Effects of drought stress and selenium supply on growth and physiological characteristics of wheat seedlings. Acta Physiol. Plant. 31: 1031-1036., DOI: 10.1007/s11738-009-0322-3 Yemm, E.W., Cocking, E.C. 1955. The determination of amino acids with ninhydrin. Analyst 80: 209-213, DOI: 10.1039/an9558000209 Yemm, E.W., Willism, A.J. 1954. The estimation of carbohydrates extracts by anthrone. Biochem. J. 57: 508-514, DOI: 10.1042/bj0570508 Zhou, S., Duursma, R.A., Medlyn, B.E., Kelly, J.W.G., Prentice, I.C. 2013 How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress. Agric. Forest Meteorol. 182/183: 204-114, DOI: 10.1016/j.agrformet.2013.05.009 COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.02 Agrovoc descriptors: allelopathy, amaranthaceae, weeds, biological competition, crops, tolerance, resistance to injurious factors, germination, growth Agris category code: f62, f40, h60 Allelopathic effects of redroot pigweed (Amaranthus retroflexus L.) on germination & growth of cucumber, alfalfa, common bean and bread wheat Hamideh BAKHSHAYESHAN-AGDAM1, Seyed Yahya SALEHI-LISAR1*, Rouhollah MOTAFAKKERAZAD1, Amirhosein TALEBPOUR2 and Nader FARSAD1 Received March 09, 2015; accepted July 27, 2015. Delo je prispelo 09. marca 2015, sprejeto 27. julija 2015. ABSTRACT IZVLEČEK Allelopathy is one of the important interactions among plants. Weeds can reduce crops productions in farms by their allelopathic effects. Redroot pigweed (Amaranthus retroflexus L.) is the most common weed in Iran with well-known allelopathic potential. In the presented experiment, the allelopathic effects of redroot pigweed on germination and growth of four important crop species including cucumber (Cucumis sativus L.), alfalfa (Medicago sativa L.), common bean (Phaseulus vulgaris L.) and bread wheat (Triticum aestivum L.) was studied. The effect of different concentrations of redroot pigweed leachate on seed germination and seedlings growth parameters of tested plants was significant, but not same in all studied species. Bread wheat and cucumber were more resistance in seed germination stage in comparison to common bean and alfalfa. Except alfalfa, all plant species showed certain rate of resistance in the most measured parameters. According to the obtained results, bread wheat and common bean were the most resistant species, cucumber was resistant at low concentration but sensitive at high concentration, and alfalfa was the most sensitive species to the redroot pigweed leachate treatments. Therefore, the cultivation of resistant plant species (such as bread wheat and common bean plants) in the regions with redroot pigweed's invasion is appropriate way in management of the farms. Key words: allelopathy, redroot pigweed, resistance, crop species, leachate concentration ALELOPATIČNI UČINEK NAVADNEGA SČIRA (Amaranthus retroflexus L.) NA KALITEV IN RAST KUMAR, LUCERNE, NAVADNEGA FIŽOLA IN KRUSNE PSENICE Alelopatija je ena izmed najpomembnejših interakcij med rastlinami. Pleveli lahko zmanjšajo pridelek zaradi njihovih alelopatičnih učinkov. Navadni ščir (Amaranthus retroflexus L.) je v Iranu najpogostejši plevel z dobro znanim alelopatičnim učinkom. V tej raziskavi smo preučevali alelopatski učinek navadnega ščira na kalitev in rast štirih pomembnih kulturnih rastlin in sicer kumar (Cucumis sativus L.), lucerne (Medicago sativa L.), navadnega fižola (Phaseulus vulgaris L.) in krušne pšenice (Triticum aestivum L.). Učinek različnih koncentracij izvlečka navadnega ščira na kalitev in rastne parameter preiskuševanih rastlin je bil značilen toda ne enak pri vseh rastlinah. Krušna pšenica in kumare so bile bolj odporne na stopnji kalitve v primerjavi s fižolom in lucerno. Z izjemo lucerne so vse preiskušene vrste pokazale določeno odpornost pri vseh merjenih parametrih. Glede na rezultate te raziskave sta se krušna pšenica in navadni fižol izkaza kot najbolj odporna, kumare so bile pri manjših koncentracijah ekstrakta navadnega ščira odporne, a občutljive pri velikih koncentracijah. Lucerna je bila najbolj občutljiva na izločke navadnega ščira pri vseh obravnavanjih. Na osnovi dobljenih rezultatov priporočamo kmetovalcem na območjih z večjim pojavljanjem navadnega ščira gojenje nanj odpornih rastlin kot sta krušna pšenica in navadni fižol. Ključne besede: alelopatija, kmetijske izvlečkov navadni ščir, odpornost, rastlines, koncentracije 1 Department of Plant Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz-5166616471, Iran; * Corresponding author: y_salehi@tabrizu. ac.ir Agricultural and Natural Resources Research Center of East Azerbaijan, Tabriz- 5716964455, Iran 2 1 INTRODUCTION Farmers have realized long-time ago that in addition to cultivated crop species, specific plants are growing in agricultural land called weeds (Dhole et al., 2011; Salehian and Eshaghi, 2012; Modhej et al., 2013). In addition to reduction of resources available to crop species (competition), allelochemical compounds produced by weed may also affect plants growth (allelopathy) (Shahrokhi et al., 2011; Modhej et al., 2013; Konstantinović et al., 2014). Allelopathy is one of the most important interactions between plants (Amini et al., 2012; Amini, 2013; Konstantinović et al., 2014), which occurs via production of certain compounds called allelochemicals, mainly a subset of secondary metabolites (Khan et al., 2010; Amini et al., 2012; Soltys et al., 2013). Plants can release these compounds into the environment by different ways such as leaching the allelopathic materials from the shoot by rainfall, releasing volatile phytotoxic compounds from plant's green parts, releasing phytotoxic compounds from decomposed plant material and eventually, releasing phytotoxic compounds by the root exudates (Weir et al., 2004; Terji, 2008; Amini et al., 2012; Soltys et al., 2013). Almost 250 weed species that have invaded farms have been identified which have the potential to produce allelopathic compounds (Shahrokhi et al., 2011). Although many species from the genus Amaranthus are weeds, the redroot pigweed (Amaranthus retroflexus L.) is the most famous with the well-known allelopathic effects (Costea et al., 2004; Shahrokhi et al., 2011; Shahrokhi et al., 2012; Konstantinović et al., 2014). Moreover redroot pigweed is a common weed in Iran and can be seen frequently on agricultural lands (Shahrokhi et al., 2011; Shahrokhi et al., 2012). This plant is one of the main components of desert and semi-desert's flora (Lamonico, 2010; Duretto and Morris, 2011) and expansion from Iran in the desert belt of the world could be the reason of its high distribution in this country. Redroot pigweed is summer annual C4 species with high biological potential and can produce a lot of seeds (Lamonico, 2010; Duretto and Morris, 2011; Amini et al., 2012; Shahrokhi et al., 2012). It is one of the few resistant plants to several herbicides, including atrazine, simazine, imazethapyr, thifensulfuron, and linuron (Costea et al., 2004; Sarabi et al., 2011). Many researchers have reported the allelopathic effects of redroot pigweed on different crops (Shahrokhi et al., 2011; Tejeda-Sartorius et al., 2011; Amini et al., 2012; Dogaru et al., 2012; Mlakar et al., 2012; Namdari et al., 2012; Shahrokhi et al., 2012; Konstantinović et al., 2014). Nodaway, several allelic compounds such as aldehydes, alkaloids, apocarotenoids, flavonoids, steroids, xyloids, chlorogenic acid and saponins have been identified from amaranth residues (Shahrokhi et al., 2011; Shahrokhi et al., 2012). The recent study was carried out in order to evaluate the allelopathic effects of different leachate concentrations of redroot pigweed on germination and growth of some important and common crop species in Iran in order to determine their sensitivity and resistance to chemicals produced by redroot pigweed. 2 MATERIALS AND METHODS 2.1 Experimental design and treatments The experiment was conducted as factorial based on completely randomized design (CRD) with 3 replications. Experimental factors were crop species at four levels including cucumber (Cucumis sativus 'Basmenj'), alfalfa (Medicago sativa 'Hamedan'), common bean (Phaseulus vulgaris 'Dorsa') and bread wheat (Triticum aestivum 'Pishgam') and different concentrations of redroot pigweed leachate (5 % and 10 %). Double distilled water was considered as control. 2.2 Sampling and plant extract preparation Redroot pigweed fresh material including root, stem, leaf and flower was collected from crop fields of Khosroshahr (East Azerbaijan, Iran) and powdered after air drying under lab conditions. For leachate preparation, 10 grams of powdered material were suspended in100 ml double distilled water and mixed for 24 hours by a horizontal rotary shaker for producing uniform suspension (Shahrokhi et al., 2011; Mlakar et al., 2012; Shahrokhi et al., 2012). Suspension was filtered using two layers of sterile cheese cloth and this filtrate was considered as leachate. Furthermore, leachate 5 % was prepared by dilution of leachate 10 % using double distilled water. 2.3 Plant culture and bioassay tests For evaluation of the allelopathic effect of weed extracts on germination and growth of cucumber, alfalfa, common bean and bread wheat seeds were disinfected using 1 % (v/v) sodium-hypochlorite solution for 5 minutes and washed sufficiently using sterile distilled water. Ten seeds of each species were placed in Petri dishes containing sterile filter paper and 5 ml of leachate with appropriate concentration were added. Control seeds were moistened with 5 ml of sterile double distilled water. Petri dishes were sealed with parafilm for prevention of pollution and water evaporation and transferred to darkness. After 2 days all germinated seeds were transferred to climate chambers with controlled conditions (2530 °C, 16/8 (light/dark) photoperiod and relative humidity of 60 %). The percentage of germinated seeds was recorded daily and growth parameters like seedling length, shoot length, seminal root length, fresh and dry weight of seedlings were determined after 7 days. Relative growth rate (Equation 1) (Tomlinson et al., 2012) and seedling survival rate (Equation 2) (Kusmana, 2010) were calculated using following formulae: Equation 1: RGR =- x 100 yAt Where RGR is relative growth rate, Ay is growth amount, At is growth time (day) and y is the fresh/dry weight of primary tissue or organ. A Equation 2: SSR= — X 100 Where SSR is seedling survival rate, A is number of germinates and B is the number of germinated seeds. 2.4 Data analysis The data were analyzed using GLM procedure by SPSS software (Ver. 16) and Tukey's multiple range tests was used for mean comparisons at 1 % probability level. 3 RESULTS According to statistical evaluation (analysis of variance), the effect of different concentrations of redroot pigweed leachate on seed germination percentage; seedling, shoot and seminal root length; fresh and dry weight of seedlings and its interaction with crop species was significant (p < 0.01). However, the effect of different leachate concentrations on germination and growth of species was not the same (Table 1). Table 1: Mean squares of redroot pigweed leachate's concentrations effect on germination and growth related characteristics of crop species Source of variation Df Shoot Length Seminal root Length Seedling Length Fresh Weight Dry Weight Germin. Percentage Treatments 2 3148.0 ** 16473.4 ** 31332.8 ** 88395.3 ** 6706.9 ** 5077.8 ** Species 3 2431.3 ** 2949.7 ** 10382.9 ** 194355.7 ** 74284.8 ** 3425.9 ** Treatments*Species 6 852.1 ** 1585.8 ** 3835.2 ** 19268.8 ** 4578.5 ** 848.2 ** Error 24 17.67 46.53 122.22 3046.29 844.98 75.0 Coefficient of variation (%) 11.67 18.94 30.70 153.31 ).74 significant at p < 0.01 by Tukey's multiple range tests, n = 3 24.05 Hamideh BAKHSHAYESHAN-AGDAM et al. 3.1 Seed germination Except for bread wheat plants, treatment with 5 % redroot pigweed leachate of led to decrease in seed germination. The highest reduction was recorded in alfalfa. Treatment of plants with 10 % redroot pigweed leachate led to a decrease in seed germination in all species. Bread wheat and alfalfa plants showed the lowest and the highest decrease in seed germination respectively. According to the results of germination percentage, bread wheat and cucumber were identified as the most resistant, and Control ■ 5% RPL ■ 10% RPL 120 Cucumber Alfalfa Common bean Bread wheat Figure 1: The effect of different concentrations (5 % and 10 %) of the redroot pigweed's leachate (RPL) on seed germination of crop species (n = 3, p < 0.01). a 120 g 100 Control --- 5% RPL & IS e У 80 У/"" s / h ^ & e о 'S •S g h ^ O 60 40 20 A' / + * , — • 10% RPL 0 1 2 3 4 5 Time (day) 6 7 alfalfa and common bean were classified as the most sensitive plants among studied species (Figure 1). Daily recording of germination percentage indicated a delay phase in germination of treated plants in all species (Figure 2). The results of these records were also similar to the germination percentage. On the other hand, bread wheat plants showed the lowest delay time, whereas the highest delay time was observed in alfalfa. Figure 2: Effects of redroot pigweed leachate (RPL, 5 and 10 %) on seed germination of (a) cucumber, (b) alfalfa, (c) common bean, (d) bread wheat during 7 days after treatment (n = 3,p < 0.01). 100 M IS e 8 h ^ = o Чя •S o 80 60 40 20 Control 5% RPL 10% RPL 3 4 5 6 7 Time (day) C 0 3.2 Seedling survival rate (SSR) Only the alfalfa seedling survival rate (SSR) significantly decreased in plants treated with 5 % redroot pigweed leachate and other species were not affected significantly (p < 0.01). Treatment of 10 % redroot pigweed leachate led to considerable decrease in alfalfa and cucumber seedling survival rate, while this was not notably affective on bread wheat and common bean plants. Analysing this parameter, bread wheat and common bean were the most resistant, cucumber was relatively sensitive and alfalfa was the most sensitive plants in response to the redroot pigweed leachate (Figure 3). Figure 3: The effects of different concentrations (5 % and 10 %) of the redroot pigweed's leachate (RPL) on seedling survival rate of crop species (n = 3,p < 0.01). 3.3 Shoot, seminal root and seedling length Shoot length of cucumber was not notably affected by treatment with 5 % of redroot pigweed leachate, but in bread wheat and alfalfa this parameter decreased significantly (p < 0.01). In common bean plants shoot length decreased 19.24 % in comparison with control plants, but was not significant (Table 2). Significant decrease in shoot length of bread wheat; cucumber and alfalfa were observed in plants treated by leachate 10 %. In common bean plant, this parameter decreased by 27.62 %, but the trend was not significant (p < 0.01) (Table 2). According to the obtained results, common bean and bread wheat were the most resistant plants; cucumber was moderately sensitive and alfalfa was the most sensitive species to the redroot pigweed leachate, respectively. In all studied species seminal root length was significantly shorter in plants treated with 5 % and 10 % leachate of redroot pigweed plant, however, the difference among plants treated with 5 % and 10 % leachate was only significantly different in cucumber plant (p < 0.01) (Table 2). Therefore, according to this parameter, common beans and bread wheat were the most resistant plants; cucumber and alfalfa were the most sensitive species to redroot pigweed plant. The results of seedling length were similar to the results of shoot and seminal root length. Common bean and bread wheat were classified as the most resistant species, cucumber was moderately susceptible and alfalfa was the most sensitive species to redroot pigweed leachate (Table 2). Redroot pigweed leachate increased shoot/seminal root length ratio of cucumber, bread wheat and common bean plants and the ratio was higher in plants treated with 10 % leachate (Table 2). The shoot/seminal root length ratio in cucumber, common bean and bread wheat plants treated with 5 % leachate were 4.21, 2.98 and 3.71 times bigger than in control plants, respectively. In bread wheat and common bean plants treated with 10 % leachate shoot/seminal root length ratio was 6.01 and 8.154 times higher, respectively, when compared to controls. However, the effect of redroot pigweed leachate on shoot/seminal root length ratio and was not significant (p < 0.01). Considering this parameter, among studied species bread wheat and common bean can be classified as the most resistant, cucumber as moderately susceptible and alfalfa as the most sensitive to redroot pigweed leachate. Table 2: The effect of different concentrations (5 and 10 %) of the redroot pigweed's leachate on shoot, seminal root and seedling length (mm) and shoot/seminal root length ratio of crop species (n = 3, p < 0.01). Parameters Plant Species Shoot Length Seminal root Length Seedling Length Shoot/ Seminal root Control 61.07±2.99 a 123.79±11.18 a 181.09±19.04 a 0.494±0.02 b Cucumber 5 % 63.67±2.46 a 30.99±4.41 b 94.68±5.23 b 2.081±0.31 a 10 % 0.0±0.0 b 0.0±0.0 c 0.0±0.0 c 0.0±0.0 c Control 11.46±1.10 a 30.28±4.78 a 41.75±5.35 a 0.383±0.06 a Alfalfa 5 % 0.0±0.0 b 0.0±0.0 b 0.0±0.0 b 0.0±0.0 b 10 % 0.0±0.0 b 0.0±0.0 b 0.0±0.0 b 0.0±0.0 b Control 19.33±0.72 a 41.24±5.93 a 60.57±6.46 a 0.474±0.06 a Common bean 5 % 15.61±1.64 a 11.95±4.04 b 27.56±5.21 b 1.416±0.51 a 10 % 13.99±0.83 a 6.12±3.71 b 20.12±2.88 b 2.848±1.86 a Bread wheat Control 5 % 10 % 54.13±10.99 a 22.66±1.70 b 9.12±1.81 b 87.65±17.76 a 10.15±2.20 b 1.89±0.32 b 141.79±28.69 a 32.81±3.70 b 11.02±1.48 b 0.617±0.01 b 2.285±0.40 ab 5.031±1.98 a 3.4 Fresh and dry weight of seedlings Both 5 and 10% leachate leads to significant decrease in seedling fresh weight of bread wheat, cucumber and alfalfa plants (p < 0.01). In common bean seedling fresh weigh decreased up to 34 %, but the trend was not significant (p < 0.01). Alfalfa growth was completely inhibited by both treatments, whereas cucumber growth was only inhibited with 10 % redroot pigweed leachate (Table 3). Therefore, according to this parameter, common beans and bread wheat were the resistant plants; cucumber and alfalfa were the sensitive species to redroot pigweed allelopathic effects. The effect of redroot pigweed leachate on seedling dry weight of cucumber and alfalfa plants was similar to its effect on fresh weight. 5 % leachate stimulated common bean dry weight, but significant decrease occurred in plants treated with 10 % leachate in comparison with control plants (p < 0.01). However, the effect of leachate on bread wheat plants dry weight was in contrast and not significant. On the other hand, leachate of 5 % reduced and leachate of 10 % stimulated dry material accumulation in bread wheat plants (Table 3). Considering this parameter, bread wheat is the most resistance and alfalfa is the most sensitive species to redroot pigweed leachate. 3.5 Related growth rate (RGR) Relative growth rate (RGR) varied between studied species and redroot pigweed leachate treatments (Table 3). In cucumber, RGR was considerably decreased, while in bread wheat plants it was slightly stimulated. Common bean was differently affected by redroot pigweed leachate. In this plant RGR was significantly increased (p < 0.01) by 5 % leachate treatment, whereas 10 % leachate led to considerable reduction. Considering the results of this parameter, bread wheat and common bean are the most resistance, cucumber is moderately sensitive and alfalfa is the most sensitive species to redroot pigweed leachate. Table 3: The effect of different concentrations (5 and 10 %) of the redroot pigweed's leachate on fresh and dry weight of seedlings (mg) and relative growth rate (RGR, 1.day-1) of crop species in 7 day after treatment (n = 3, p < 0.01). Plant Species Treatments Parameters Fresh Weight Dry Weight RGR Control 320.12±31.86 a 31.72±5.44 a 10.05±2.11 a Cucumber 5 % 239.27±36.76 b 24.94±3.08 a 7.89±0.98 a 10 % 0.0±0.0 c 0.0±0.0 b 0.0±0.0 b Control 25.08±2.69 a 0.64±0.05 a 4.52±0.36 a Alfalfa 5 % 0.0±0.0 b 0.0±0.0 b 0.0±0.0 b 10 % 0.0±0.0 b 0.0±0.0 b 0.0±0.0 b Control 438±32.94 a 233.15±16.93 ab 13.22±0.96 ab Common bean 5 % 425.44±6.11 a 251.16±25.97 a 14.27±1.47 a 10 % 288.75±86.62 a 155.01±46.41 b 8.79±2.64 b Control 142.33±37.37 a 27.44±1.32 a 9.55±0.46 a Bread wheat 5 % 74.82±10.60 b 26.70±5.77 a 9.29±2.01 a 10 % 67.64±2.44 b 31.22±1.76 a 10.87±0.62 a 4 DISCUSSIONS In the present study, different concentrations of redroot pigweed's leachate caused 6.90-100 % reduction in seed germination of studied species. Allelopathic inhibitory potential of redroot pigweed was frequently reported in the literatures (Shahrokhi et al., 2011; Tejeda-Sartorius et al., 2011; Amini et al., 2012; Dogaru et al., 2012; Mlakar et al., 2012; Namdari et al., 2012; Shahrokhi et al., 2012; Konstantinović et al., 2014). Control of redroot pigweed is not necessary in natural environments because its populations have disturbed distribution and displaced by other plants after several years over natural succession (Costea et al., 2004). Most control methods documented for this weed are specific to agricultural systems (Costea et al., 2004; Rosskopf et al., 2005; Zhang and Mu, 2008; Dogaru et al., 2012). The use of herbicides as a thin layer on the surface of soil is one of these methods (Sarabi et al., 2011; Sodaei zadeh and Hosseini, 2012). The development of resistant varieties from redroot pigweed by using herbicides showed that these methods were not effective in long time periods (Costea et al., 2004; Rosskopf et al., 2005; Sarabi et al., 2011). Also, biological control of redroot pigweed using insects was ineffective (Costea et al., 2004; Rosskopf et al., 2005); however, there are reports on different pigweed species control by fungi Phomopsis amaranthicola Rosskopf, Charud, Shabana & Benny. Sp. nov. in field conditions (Rosskopf et al., 2005). Nowadays, only cultivation of crop species which are resistant to redroot pigweed allelochemicals in fields aggressed with this plant appears to be promising. The results of this study clearly showed that seed germination and seedling growth of studied species were differently affected by redroot pigweed allelochemicals. According to recorded parameters, common bean was sensitive in seed germination but resistant in seedling growth stages. The exactly contrast responses were observed in cucumber. However, bread wheat plant was relatively resistance species in both germination and subsequent seedling growth phases. Although alfalfa slightly germinated in the presence of redroot pigweed allelochemical but its seedling growth and development was completely inhibited. Therefore, this species was the most sensitive species. The result of germination rate clearly showed that redroot pigweed can reduce crop plants seed germination, but the effective time is different in species. While bread wheat seeds germination started in first day, in other species germination showed a delay phase up to 3 days. Furthermore, seeds germination rate in treated bread wheat plants was lower in comparison to control, but the germination rate increased over time and finally reached to control. Weaker compensation ability was observed in other species. Therefore, the allopathic effect of redroot pigweed on the seeds germination of crops is higher in short time and compensation capability was dependent on plant species and leachate concentration. The effect of redroot pigweed leachate on seminal root length was higher than that in shoot lenght. Measurements of other growth parameters and studying of mechanisms involved in resistance of these organs can be useful in fine evaluation of this finding. Also conducting of this experiment using soil, perlite or hydroponic culture of plants could lead to reliable results for evaluation of allopathic effects of redroot pigweed on crops. 5 CONCLUSIONS According to the results of presented study, bread wheat and common bean were the most resistant species, cucumbers was resistant species at low redroot pigweed leachate concentration but sensitive at high concentration, and alfalfa was the most sensitive species to the redroot pigweed leachate. Therefore, among the four studied crop species the cultivation of bread wheat and common bean plants in the regions with redroot pigweed's invasion is affordable, and avoidance of alfalfa cultivation in these regions is essential because this species is quite sensitive to compounds produce by redroot pigweed. 6 REFERENCES Abdul Raoof K.M., Siddiqui M.B. 2012. Allelopathic impact of rhizosphere soil of Tinospora cordifolia on growth and establishment of some weed plants. African Journal of Agricultural Research, 7: 39523956, doi: 10.5897/AJAR11.2163 Amini R.A. 2013. Allelopathic potential of little seed canary grass (Phalaris minor Retz.) on seedling growth of barley (Hordeum vulgare L.). Journal of Biodiversity and Environmental Sciences, 3: 85-91 Amini R.A., Movahedpour F., Ghassemi-Golezani K., Dabbagh Mohammadi-Nasab A., Zafarani-Moattar P. 2012. Allelopathic assessment of common amaranth by ECAM. International Research Journal of Applied and Basic Sciences, 3: 2268-2272 Costea M., Weaver S., Tardif F. 2004. The biology of Canadian weeds. 130. Amaranthus retroflexus L., A. powellii S. Watson and A. hybridus L. (Update). Canadian Journal of Plant Science, 84: 631-668, doi: 10.4141/P02-183 Dhole J.A., Bodke S.S., Dhole N.A. 2011. Allelopathic effect of aqueous extract of five selected weed species on seed mycoflora, seed germination and seedling growth of Sorghum vulgare Pers. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 2: 142-148 Dogaru G.V., Budoi S.G., Sandoiu D.D.I. 2012. Determination of the Amaranthus retroflexus Damage Threshold in Maize Crop. Advances in Agriculture and Botanic, 4: 1-5 Duretto M.F., Morris D.I. 2011. Amaranthaceae, Version 2011:1. In: Flora of Tasmania Online. Duretto M.F. (Ed.). Tasmanian Museum and Art Gallery, Australia: 1-29 Khalaj M.A., Amiri M., Azimi M.H. 2013. Allelopathy: physiological and sustainable agriculture important aspects. International journal of Agronomy and Plant Production, 4: 950-962 Khan A.L., Hussain J., Hamayun M., Kang S.M., Kim H.Y., Watanabe K.N., Lee I.N. 2010. Allelochemical, eudesmane-type sesquiterpenoids from Inula falconeri. Molecules Journal, 15: 15541561, doi: 10.3390/molecules15031554 Konstantinović B., Blagojević M., Konstantinović B., Samardžić N. 2014. Allelopathic effect of weed species Amaranthus retroflexus L. on maize seed germination. Romanian Agricultural Research, 31: 1-7 Kusmana C. 2010. The growth of Rhizophora mucronata and Avicennia marina seedlings planted using Guludan technique in coastal area of Jakarta. Conference of the Earth and Space Sciences, Indonesia: 1-7 Iamonico D. 2010. Biology, life-strategy and invasiveness of Amaranthus retroflexus L. (Amaranthaceae) in central Italy: preliminary remarks. Botanica Serbica, 34: 137-145 Mlakar S.G., Jakop M., Bavec M., Bavec F. 2012. Allelopathic effects of Amaranthus retroflexus and Amaranthus cruentusextracts on germination of garden cress. African Journal of Agricultural Research, 7: 1492-1497 Modhej A., Rafatjoo A., Behdarvandi B. 2013. Allelopathic inhibitory potential of some crop species (wheat, barley, canola, and sunflower) and wild mustard (Sinapis arvensis). International Journal of Biosciences, 3: 212-220, doi: 10.12692/ijb/3.10.212-220 Namdari T., Amini R.A., Sanayei S., Alavi-Kia S., Dabbagh Mohammadi-Nasab A. 2012. Allelopathic effects of redroot pigweed (Amaranthus retroflexus L.) root exudates on common bean seedling growth. International Research Journal of Applied and Basic Sciences, 3: 1230-1234 Rosskopf E.N., Yandoc C.B., Charudattan R. 2005. Genus-specific host range of Phomopsis amaranthicola (Sphaeropsidales), a bioherbicide agent for Amaranthus spp. Biocontrol Science and Technology, 16: 27-35, doi: 10.1080/09583150500187975 Salehian H., Eshaghi O. 2012. Growth analysis some weed species. International Journal of Agriculture and Crop Sciences, 4: 730-734 Sarabi V., Rashed Mohassel M.H., Valizadeh M. 2011. Response of redroot pigweed (Amaranthus retroflexus L.) to tank mixtures of 2,4-D plus MCPA with foramsulfuron. Australian Journal of Crop Science, 5: 605-610 Shahrokhi S., Darvishzadeh M., Mehrpooyan M., Farboodi M. 2012. Comparison of allelopathic effects of Amaranthus retroflexus L. different organs extracts on germination and initial growth of Alvand and Zarrin wheat cultivars. International journal of Agronomy and Plant Production, 3: 489494 Shahrokhi Sh., Hejazi S.N., Khodabandeh H., Farboodi M., Faramarzi A. 2011. Allelopathic effect of aqueous extracts of pigweed, Amaranthus retroflexus L. organs on germination and growth of five barley cultivars. International Conference on Chemical, Biological and Environmental Engineering, 20: 80-84 Sodaeizadeh H., Hosseini Z. 2012. Allelopathy an environmentally friendly method for weed control. International Conference on Applied Life Sciences, Turkey, 387-392 Soltys D., Krasuska U., Bogatek R., Gniazdowska A. 2013. Allelochemicals as bioherbicides — present and perspectives. V: Herbicides - Curent Research and Case Studies in Use. Price A.J., Kelton J.A. (Eds.). InTech Publisher, Rijeka, Croatica: 517-542 Tejeda-Sartorius O., Vaquera-Huerta H., Cadena-Iniguez J. 2011. Effect of amaranth residues (Amaranthus hypochondriacus L.) on weed control and yield or radish, onion and carrot. Spanish Journal of Agricultural Research, 9: 284-295, doi: 10.5424/sjar/20110901-040-10 Terji I. 2008. Allelopathic effects of juglone and decomposed walnut leaf juice on muskmelon and cucumber seed germination and seedling growth. African Journal of Biotechnology, 7: 1870-1874 Tomlinson K.W., Sterck F.J., Bongers F., da Silva D.A., Barbosa E.R.M., Ward D., Bakker F.T., van Kaauwen M., Prins H.H.T., de Bie S., van Langevelde F. 2012. Biomass partitioning and root morphology of savanna trees across a water gradient. Journal of Ecology, 100: 1113-1121, doi: 10.1111/j.1365-2745.2012.01975.x Weir T.L., Park S.W., Vivanco J.M. 2004. Biochemical and physiological mechanisms mediated by allelochemicals. Current Opinion in Plant Biology, 7: 472-479, doi: 10.1016/j.pbi.2004.05.007 Zhang Y., Mu X. 2008. Allelopathic effects of Amaranthus retroflexus L. and its risk assessment. Acta Botanica Boreali Occidentalia Sinica, 4: 771776 COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.03 Agrovoc descriptors: sesame, seed germination, germination, seedlings, growth, seed treatment ultrasound, enzyme activity, water uptake Agris category code: f02, f60 Sonication of seeds increase germination performance of sesame under low temperature stress Fariborz SHEKARI1, Seyyed-Hamid MUSTAFAVI1, Amin ABBASI1 Received April 14, 2015; accepted August 13, 2015. Delo je prispelo 14. aprila 2015, sprejeto 13. avgusta 2015. ABSTRACT IZVLEČEK A laboratory experiment was conducted to determine the effect of ultrasound (US) exposure time on germination behavior of sesame seeds. All tests were carried out at 20 kHz in a water bath ultrasonic device varying two factors, treatment duration (10, 20 and 30 min) and germination temperature (15, 20 and 25 °C). Parallel tests were run in which seeds were soaked in water without sonication in order to eliminate the effect of water from US test results. US treatments enhanced seeds water uptake. At mild exposure time it improved sesame seed germination performance and seedling growth at suboptimal temperatures as indicated by higher germination percentage and germination rate. US applying for 20 min had relatively high superoxide dismutase activity; however, had not significant differences with control and US duration for 10 min. The catalase activity was strongly increased by applying the US for a 10 and 20 min. Among the treatments, application of US vibration for 10 and 20 min reduced both of malondialdehyde and H2O2 contents, however high US duration (30 min) increased both of the traits. In general, ultrasonic priming technique can be useful for early planting the sesame seeds, and lead to higher yields. Key words: enzyme activity, germination performance, seedling growth, ultrasound, water uptake SONIFIKACIJA SEMEN SEZAMA Z ULTRAZVOKOM POVEČA NJIHOVO KALITEV V RAZMERAH HLADNEGA STRESA V laboratorijskem poskusu smo določali učinke ultrazvoka (US) na kalitev semen sezama. Vsi poskusi so bili izvedenei v ultrazvočni vodni kopeli s frekvenco ultrazvoka 20 kHz , pri čemer smo spreminjali dva dejavnika in sicer trajanje obdelave z ultrazvokom (10, 20 in 30 min) in temperaturo kalitve (15, 20 in 25 °C). Vzporedno so potekali poskusi, v katerih so bila semena samo namočena v vodi brez ultrazvočne sonifikacije, da bi odpravili učinke vode pri ultrazvočno obdelanih semenih. Obdelava semen z ultrazvokom je v njih povečala privzem vode. Pri srednjih obravnavanjih z ultrazvokom se je izboljšala kalitev in rast kalic pri suboptimalnih temperaturah, kar se je odrazilo kot večji odstotek kalitve in njen hitrejši potek. US obdelava za 20 min je rahlo povečala aktivnost superoksid dizmutase, vendar v primerjavi s kontrolo in obdelavi z US 10 min ni bilo značilnih razlik. Aktivnost katalaze se je pri obdelavah z 10 in 20 min močno povečala. Obdelava z ultrazvokom za 10 in 20 min je zmanjšala vsebnost malondialdehida in H2O2, obdelava za 30 min pa je vsebnost obeh parametrov povečala. Na splošno lahko na osnovi te raziskave povzamemo, da je ultrasonična predobdelava semen sezama koristna tehnika za njegovo zgodnjo setev, kar vodi v večje pridelke. Ključne besede: encimska aktivnost, kalitev, ultrazvok, privzem vode rast kalic, 1 Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Maragheh, Maragheh, Iran 1 INTRODUCTION Sesame (Sesamum indicum L.) is one of the most important oilseed crops used by humans (Weiss, 2000). It has a high resistance level in drought stress condition, and is therefore appropriate crop for cultivation in dry-land conditions. But in these regions, water availability in the soil can be insufficient to support seed germination and early seedling growth, which are the most sensitive stages for water shortage. In order to conquer for this problem, sesame seeds should be sown earlier in the season, when a lot of water is available, so, canopy closing and growth degree day (GDD) requirement for completing the growing stage is gain earlier and reproductive stage and following seed development and maturity complete early. One of the most important obstacles of this approach is low temperature in the early stages of season that negatively affects seed germination and seedling establishment. Seed germination and seedling establishment are the most critical stages for survival of plants under unfavorable conditions. One of the most important factors that affect germination and subsequently later stages is low temperature. Seeds can germinate over a wide range of temperatures, but maximum percentage germination is typically reduced at the extremes of the range (Probert, 2000). Germination is divided into three phases: imbibition, activation and post germination growth. The major negative effects of low temperature during germination seem to be associated to the imbibition phase (Hoekstra et al., 1992). Arin and Kiyak (2003) reported that difficulty in water uptake under low temperature can influence the later stage of growth and development. For example, emergence percentage decreased under the low temperatures. Low temperature during imbibition phase of germination leads to the increase of electrolyte leakage from the seeds, which has been attributed to the disturbance of plasma membrane integrity (Hoekstra et al., 1992). Low temperature promotes gel phase formation and increase rigidity, thereby increasing the likelihood of imbibitional injury (Crowe et al, 1989). Bochicchio et al, (1991) reported that imbibition of seeds is necessary to reorganize fully the structure of cell membrane lipids, but, if during the imbibition process, the temperature is such that membrane lipids are in a gel phase, formation of a continuous bilayer might not be possible, or the bilayer formed might be functionally imperfect. Sharma et al., (2011) reported that oxidative stress may be a significant factor in relation to low temperature damage in plants. Reactive Oxygen Species (ROS) play a key role in various events of seed life. In seeds, ROS production has been considered for a long time as being very detrimental, since the works dealing with ROS were mainly focused on seed ageing or seed desiccation, two stressful situations which often lead to oxidative stress. At the opposite, it now appears more and more clearly that ROS would play a key signaling role in the achievement of major events of seed life, such as germination or dormancy release. Many reports have shown that the transition from a quiescent seed to a metabolically active organism (phase II of germination) is associated with ROS generation, suggesting that it is a widespread phenomenon (Bailly, 2004). ROS are involved in endosperm weakening during germination. Cellular antioxidant mechanisms seem to tightly control ROS concentrations, rather than to eliminate them completely, suggesting that some ROS might play normal physiological roles and act as signaling molecules. The reactivation of metabolism following seed imbibition may provide an important source of active oxygen species (AOS). For example, H2O2 is produced at the early imbibition period of soybean (Puntarulo et al., 1991). There are several techniques that have positive effect on low temperature tolerance at germination stage. Ultrasound is a novel physical method that involves the application of sound frequencies in the inaudible range (20-100 kHz) to interact with the materials. It was proven that application of ultrasound treatment could change the state of the substances and even accelerate the reactions (Aladjadjiyan, 2007). This technique is unique among existing seed pretreatment methods in that it is simple, cheap, environmentally friendly and multifunctional (Goussous et al., 2010). Ultrasound treatment to stimulate germination has been investigated in many seed types including maize, barley, rice and sunflower (Aladjadjiyan, 2002; Florez et al, 2007; Yaldagard et al, 2008a, b). Goussous et al, (2010) and Yaldagard et al, (2008a) showed that US treatments increase seed water uptake, the important stage that was inhibited by low temperatures; so, we use this technique to investigate the beneficial effect of US on seed germination performance in low temperatures. Besides, there has not been any investigation on the effects of US treatment on ROS and antioxidant enzyme content following the ultrasonication. So this research was aimed to determine whether ultrasonic treatment is usable as a seed priming method for sesame. 2 MATERIALS AND METHODS 2.1 Seed materials Native seed lots of sesame (Sesamum indicum 'Oltan') were obtained from Tabriz University, Iran which collected the seed in the same year that the study was undertaken. 2.2 Seed treatment The ultrasonication experiments were carried out at 20 kHz on the ultrasonic generator (UW2200, Berlin). All tests were performed on samples (50 seeds for each treatment) dispersed in 100 ml of distilled water with direct sonication for 0, 10, 20 and 30 min. To rule out the effect of water in these tests, a control replicate of each test was soaked in a similar volume of water but without sonication. Water circulating in ultrasonic equipment as well as in the water bath was kept at 25 °C. 2.3 Germination tests Three replicates of 50 seeds were placed in covered 9-cm Petri dishes containing a single filter paper with 5 mL test solutions. The Petri dishes with seeds were put in sealed plastic bags to avoid moisture loss. Seeds were germinated at constant temperatures (T) of 15, 20 and 25 °C the dark in an incubator. Germination was scored when the seminal root was 2 mm long. 2.4 Germination performance measurements At the end of experiment, Final germination percentage (FGP), germination rates (GR), germination uniformity (GU), seminal root and shoot length were recorded to evaluate germination performance. Daily germination percentage was recorded and subjected to statistical analysis. GR (T50) was defined as days needed to reach 50 % of FGP. GU (Ti0-90) was defined as days needed for 10 % of FGP to 90% of FGP. 2.5 Seed water uptake The water uptake of seeds necessary for germination was determined under 15 °C. For this purpose, three replications of 50 seeds were placed in petri dishes as described for germination experiments, removed at 15 min after initiation of imbibition, drained and blotted with absorbent paper, weighted and placed again into the petri dishes. After 30 min, 1 h and 2 h, the seeds were reweighted as described above. The water uptake was expressed as the seed moisture content at different times. 2.6 Enzyme extractions and assays Measurements of enzyme activities, lipid peroxidation and H2O2 contents were carried out with imbibed but non-germinated seeds and with whole seedlings at 3 days after germination. In order to better discriminate the behavior of the seeds and seedlings, the temperature of 15 °C only has been chosen. Two grams of peeled seeds or whole seedlings were used for enzymes extraction. The samples were homogenized in 20 ml of 0.1 M potassium phosphate buffer (pH 7.8) centrifuged for 15 min at 16,000xg, at 0 °C. Extraction was at 4 °C. The supernatant sample was then stored at -20 °C prior to assaying. Superoxide dismutase (SOD, EC 1.15.11), catalase (CAT, EC 1.11.1.6) were extracted and assayed according to Bailly et al., (1996), and expressed as units per gram FW. 2.7 Evaluation of hydrogen peroxide and malondialdehyde contents H2O2 concentration was measured by the methods of Moloi and Westhuizen (2006). Results are expressed in nmole per gram dry weight. Lipid peroxidation was evaluated by measuring malondialdehyde (MDA) content from 0.2 g (fresh weight) of seeds or seedlings, according to Predieri et al. (1995). The samples were homogenized in 5 ml sodium phosphate buffer followed by centrifugation for 15 min at 8,000*g. A 0.5 ml aliquot of the supernatant was combined with an equal volume of thiobarbituric acid (TBA) reagent and boiled for 20 min. Absorbance was determined at 532 and 600 nm. MDA concentration was expressed in micromoles per gram dry weight. 2.8 Data analysis Analysis of variance appropriate to the experimental design was conducted, using SPSS software. Means of each trait were compared according to Duncan multiple range test at P < 0.05. Excel software was used to draw figures. 3 RESULTS AND DISCUSSION 3.1 Effect of different exposure times on seed water uptake Before any treatment, seed moisture was 13 %. With increasing the US exposure time, seed moisture increased. At the early times, US treated seeds, particularly US treatment for 30 min, had rapid water uptake compared with control, then water uptake slope (rate of water uptake) was enhanced in control, while reduction was observed in US for 20 and 30 min (Fig. 1). At the end, seed moisture content of control and mild treatment duration (10 and 20 min) were approximately similar. However, at high US duration, seed moisture content was lower than control. One of the possible explanations could be that sonication (for short periods) may create or enlarge fissures in the protective coating surrounding the seed and pericarp and after steeping in the water a significant rise in seedling moisture resulted. US treatment for high duration (30 min) might have led to much cell wall disruption that allowed greater accessibility of cell membranes to the effects of US, thus increasing their permeability and finally leading to post treatment water leakage. Similar results were observed by Goussous et al, (2010). Figure 1: Seed moisture content of sesame seeds soaked in water in ultrasonic device (US) for 0 - 120 min 3.2 Effect of different us exposure times and temperatures on germination performance Germination percentage (GP) of sesame seeds increased with increasing the treatment duration, reaching the limit (80 %) at 20 min. this GP value was approximately 12 % above that of the control ЛА/- seeds. However, at long duration (30 min), GP significantly decreased (approximately 18 %). Similar result was reported by Goussous et al., (2010) that showed that application of mild US duration improved germination percentage of wheat seeds. The effects of ultrasonic treatment on seed germination depend on frequency of ultrasonic wave and exposure time as well as on plant species (Aladjadjiyan, 2012). It is noticeable from Table 1 that significant differences also existed in GP among incubation temperatures. Seeds of sesame germinated better at 25 °C. It is also observed that, at suboptimal temperature (15 °C), 20 min US treatment, enhanced GP by 22 %, but at optimal temperatures improvement of GP by 20 min US was only 2 % above control. Therefore, US treatment had more pronounced effects on germination at low temperatures than at optimum ones. US duration treatment significantly affected germination rate (GR) and uniformity (GU) (Table 1). With increasing the US duration, GR increased. The highest GR (0.27) was obtained at 30 min, reaching 28 % above control. GU decreased by US treatments, however, difference between control and 10 min US was not significant. In general, US priming technique improved sesame seed germination performance at 15 °C as indicated by higher GP and GR (Table 1), indicating an improved of chilling tolerance. Germination performance improvement by US application had been reported by Goussous et al. (2010) on wheat, Yaldagard et al. (2008) on barley and Aladjadjiyan (2002) on carrot. It is demonstrated that US exerts its major effects by inducing mechanical effects (acoustic cavitation) and disruption of plants cell walls, thereby increasing water uptake, important phase of germination that are negatively affected by low temperatures. The extra absorbed water reacts freely and readily with the cell embryo, so, metabolic processes such as gibberellic acid release and activation of enzymes expedited (Yaldagard et al. 2008a), and then will significantly reduce the mean germination time and will increase the rate and yield of germination. At long period of US (30 min) decreased germination performance. It is possible that US treatment for 30 min was too extreme to be tolerated by the small and fragile seeds of sesame leading to lysis of cells. In this study non-sonicated seeds only exposed to water were used as control. Hydration of seeds by soaking in water for various periods without allowing seminal root emergence is one method of priming, which generally improves germination performance (Ashraf and Foolad 2005). Therefore, sonication priming can be used instead of usual priming ways (hydropriming). Table 1: Germination percentage, rate and uniformity of sesame seeds exposed to different duration of ultrasound (US) treatment and incubated at three temperatures; 15, 20 or 25 °C US duration Temperature (°C) Germination Percentage (%) Rate (1/day) Uniformity (day) 0 15 20 25 62f 70def 82ab 0.191 0.21h 0.23f 4.73a 4.07bc 3.69cd 10 15 20 25 72cdf 74bcd 84a 0.20i 0.23f 0.24e 4.32b 3.8cd 3.77cd 20 15 20 25 76abcd 80abc 84a 0.25d 0.26c 0.22g 3.67cd 3.5d 3.37d 15 51g 0.31a 3.74cd 30 20 62f 0.29b 3.72cd 25 64ef 0.22g 3.52d Different letters in each column indicate significant difference at P<0.05. 3.3 Seed germination trends Control seeds were germinated well when incubation temperature was 25 °C, but US treatment seeds were not significantly affected by temperatures at early stages of germination. Higher temperature caused rapid germination in US and control seeds (Fig. 2). The optimum temperature for sesame seed germination is 25 °C (Bennet, 2011). The temperature below the optimum, decreased germination rate (Bradford, 2002). Langham (2007) reported that with soil temperatures around 25°C, the seed imbibes enough moisture and encourage a rapid germination. At all of the temperatures, high US duration (30 min) had lowest GP, but cumulative GP slop (i.e. GR) was high. At low temperature (15 °C), GP curve for control seeds was lower than 10 and 20 min US, however, with increasing the temperature, GP curve for control seeds was approached to 10 and 20 min US duration curves. At 25 °C, control and mild US duration treatments (10 and 20 min) had approximately similar curves (Fig. 2). Therefore, US priming technique for appropriate duration were more beneficial at suboptimal temperature than optimal ones. And it can improve germination performance of sesame seeds under chilling stress. Figure 2: Cumulative seed germination of US treatment and control seeds under different temperatures (15, 20 and 25 °C) 3.4 Effect of us and temperature treatments on seedling growth Seedling length and dry weight were significantly affected by priming technique. The size of the seedlings was larger in treatments where seeds were primed by 20 min or 10 min, and smaller in control and 30 min US treatment. At all temperatures, seedling size of mild US treated seeds (20 min), was higher than control, but high US duration at low incubation temperatures produce more slender seedlings (compared to control) (Fig. 3). At higher temperatures, 30 min US treatment of seeds for 30 min decreased seedling's growth. Their size is lower than in controls. According to literature low temperature promotes gel phase formation and increase rigidity of membrane, so, it seems that, in this situation, membrane may be able to tolerate mechanical changes that caused by US duration for 30 min. At higher temperatures, however, membrane rigidity is eliminated (Nijsse et al, 2004), which presumably decrease tolerance to high duration US treatment. In a research conducted by Fateh et al. (2012) on fennel, they showed that US treatment had adverse effect on seedling growth. Aladjadjiyan (2012) reported that seedling length of lentil had approximately linear relationship with US exposure time, and with increasing the US time, these traits increased. 40 35 Ш Ь 30 £ M 25 г 20 ■D M С тз OJ 15 OJ (Л 10 5 0 ►......control 1-- US-10 •-US-20 ► — US-30 15 20 25 Temperature (°C) Figure 3: Effect of US treatments on seedling dry weight and length at different temperatures 3.5 Enzyme activities SOD activity did not significantly change during germination phase. So this enzyme activity was similar from imbibition phase to seedling growth. Whereas, about CAT activity; after imbibition, CAT activity had increased by 29 % and the activity of this enzyme was higher at seedling stage than imbibition time (Fig. 4). It can be concluded that SOD activity is not correlated with seed germination, and it may be mainly involved in preserving the viability of seeds and protecting them from reactive oxygen species formed during storage. CAT activity changes during germination are demonstrating that this enzyme in addition to had role in storage time; it had a detoxifying role at germination stage too. These results are in agreement with certain finding of Yeh et al. (2005), which showed that activity of antioxidant enzymes such as CAT and SOD is closely related with germination and storage longevity. Among the treatments, 20 min US treatment induced relatively high SOD activity. There was, however, not significant difference between this treatment and shorter US treatment (10 min) and the control. High duration of US (30 min) decreased SOD activity. At all of the treatments, SOD activity changes were not significant between imbibed seeds and seedlings (Fig. 4). The CAT activity was strongly increased by applying the US for a moderate time (10 and 20 min), thus enhancing the antioxidant defence of the cells. Our data also showed that US treatment for a long time (30 min) reduced CAT activity in the both of imbibed seeds and seedlings. Chen et al. (2013) reported that seeds exposed to ultrasonic vibration showed high CAT and SOD activities, so, improved resistance to cadmium and lead in wheat seedling. Stimulation of CAT activity by seed priming was also reported by Bailly et al. (2002). The catalase intervenes in the respiration of plants, which caused degradation of the endosperm and cotyledons reserve substances and synthesis of some necessary substances for nutrition and embryo growth. Therefore, it seems that stimulation of germination process and seedling growth by ultrasonic vibration may be attributed to CAT activity. Bailly et al. (2002) showed that improvement of germination performance by priming was clearly associated with higher CAT activity. 8 7 1 6 •<Ü 2 5 и !4 = 3 з О 2 i/i 1 0 Figure 4: Effects of US treatments on SOD and CAT activities in imbibed seeds Qand seedlings 3.6 Lipid peroxidation and H2O2 content Lipid peroxidation (degradation) was evaluated by determination of seed malondialdehyde content. MDA is one of the final products of the peroxidation of unsaturated fatty acids in phospholipids and is responsible for cell membrane damage (Sharma et al., 2011). MDA contents of seeds and seedlings are summarized in Fig. 5. In all of the treatments, MDA contents were higher in imbibed seeds than in seedlings. Despite an active metabolism associated with seedling growth, there was no increase in lipid peroxidation. Our data showed that hydrogen peroxide content was not significantly changed during seedling development following the imbibition, despite of producing by mobilization of stored reserves by ß-oxidation in glyoxysomes, a type of peroxisome (Bewley and Black, 1994). Indeed, peroxisomes are also the site of localization of catalase, which eliminates H2O2. Therefore, production of H2O2 by converting the lipid reserves into sugars during the first stages of seedling development can be reduced by catalase activity that increased in this period. Among the treatments, application of US vibration for 10 and 20 min reduced both of MDA and H2O2 contents, however high US duration (30 min) increased both of the traits. It is notable that MDA and H2O2 enhancement in imbibed seeds is higher than seedlings (Fig. 5). Imbibed control and US treated seeds for 10 min, and further growth of seedlings generated by these seeds, did not lead to significant changes in H2O2 content. It seems that increase in MDA and H2O2 content by US priming may be attributed to increase in antioxidant enzymes activity such as catalase that could be able to eliminate these detoxifying agents. The results obtained underline the likely involvement of CAT in germination and early growth of seedlings of sesame thus suggesting that control of H2O2 homeostasis is an important event in expression of seed vigor. However, H2O2, together with other ROS, may have many cellular US-10 US-20 US-30 targets, such as proteins and DNA (Sharma et al, 2011). Alternatively, CAT also plays a key role in H2O2 removal during fatty acid ß-oxidation in glyoxysomes (Olsen and Harada, 1995). Therefore, 4S Q W * И 0 E и 1 < и es о Figure 5: Effects of US treatments on MDA and H2O: high CAT activity could be associated with better mobilization of lipid reserves and faster seedling development. 3r5 Control IJS-10 I JS-?0 I JS-?.0 : contents in imbibed seeds [3 and seedlings 4 CONCLUSION Results of this research indicated that US treatment effectively enhanced germination performance and seedling growth of sesame seeds especially at suboptimal temperatures. This increase in germination performance could have a positive impact on the success of early field establishment and canopy closer leading to better plant establishments and influence weed managements. So, this technique can be useful for alleviating the adverse effect of suboptimal temperature on seed germination, therefore, it can be very important in earlier canopy closing and finally improve yield. 5 REFERENCES Aladjadjiyan A. 2002. Study of the influence of magnetic field on some biological characteristics of Zea mays L. Journal of Central European Agriculture 3: 89-94 Aladjadjiyan A. 2007. The Use of Physical Methods for Plant Growing Stimulation in Bulgaria. Journal of Central European Agriculture 8: 369-380 Aladjadjiyan A. 2012. Physical factors for plant growth food quality. In: food production, approaches, challenges and tasks. Intech Arin L and Kiyak Y. 2003. The effects of pre-sowing treatments on emergence and seedling growth in tomato seed (Lycopersicon esculentum Mill.) under several stress conditions. Pakistan Journal of Biological Science 6: 990-994, doi: 10.3923/pjbs.2003.990.994 Ashraf M and Foolad MR. 2005. Pre-sowing seed treatment: A shotgun approach to improve germination, plant growth and crop yield under saline and non-saline conditions. Advances in Agronomy 88: 223-271, doi: 10.1016/S0065-2113(05)88006-X Bailly C. 2004. Active oxygen species and antioxidants in seed biology. Seed Science Research 14, 93-107, doi: 10.1079/SSR2004159 Bailly C, Benamar A, Corbineau F, and COME D. 1996. Changes in malondialdehyde content and in superoxide dismutase, catalase and glutathione reductase activities in sunflower seeds as related to deterioration during accelerated aging. Physiologia Plantarum 97: 104-110, doi: 0.1111/j. 1399-3054.1996.tb00485.x Bailly C, Bogatek-Leszczynska R, Come D, and Corbineau F. 2002. Changes in activities of antioxidant enzymes and lipoxygenase during growth of sunflower seedlings from seeds of different vigour. Seed Science Research 12: 47-55, doi: 10.1079/SSR200197 Bennet M. 2011. Sesame seed: A Handbook for Farmers and Investors. 29/08/11 .Available at www.agmrc.org/media/cm/ sesame_38F4324EE52CB. pdf Bewley JD and Black M. 1994. Seeds. Physiology of development and germination (2nd edition). New York, Plenum Press Bochicchio A, Coradeschi MA, Zienna P, Bertolini M, and Vazzana C. 1991. Imbibitional injury in maize seed independent of chilling. Seed Science Research 1: 8590, doi: 10.1017/S0960258500000702 Bradford KJ. 2002. Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Science 50: 248-260, doi: 10.1614/0043- 1745(2002)050[0248:AÜHTTQ]2.0.CÜ;2 Chen Y, Liu Q, Yue Xz, Meng Zw, and Liang L. 2013. Ultrasonic vibration seeds showed improved resistance to cadmium and lead in wheat seedling. Environment science pollution research, DOI 10.1007/S11356-012-1411-1 Crowe J.H., Hoekstra F.A., and Crowe L.M., 1989. Membrane phase transitions are responsible for imbibitional damage in dry pollen. Proceedings of the National Academy of Sciences USA 86: 520-523, doi: 10.1073/pnas.86.2.520 Fateh E, Noroozi H, Farbod M, and Gerami F. 2012. Assessment of Fennel (Foeniculum vulgare ) seed germination characteristics as influenced by ultrasonic waves and magnetic water. European Journal of Experimental Biology 2: 662-666 Florez M, Carbonell V, and Martinez E. 2007. Exposure of maize seeds to stationary magnetic fields: Effects of germination and early growth. Environmental and Experimental Botany 59: 68-75, doi: 10.1016/j. envexpbot.2005.10.006 Goussous SJ, Samarah N.H, Alqudah AM, and Othman MO. 2010. Enhancing seed germination of four crop species using an ultrasonic technique. Experimental Agriculture 46: 231-242, doi: 10.1017/S0014479709991062 Hoekstra FA, Crowe JH, and Crowe LM. 1992. Germination and ion leakage are linked with phase transitions of membrane lipids during imbibition of Typha latifoliapollen. Physiologia Plantarum 84: 2934, doi: 10.1111/j .1399-3054.1992.tb08760.x Langham DR. 2007. Phenology of sesame. In: Janick J., and Whipkey A. [ed.], New Crops and New Uses, 210275. ASHS Press, Alexandria, VA Moloi MJ and Westhuizen AJ. 2006. The reactive oxygen species are involved in resistance responses of wheat to the Russian wheat aphid. Journal of Plant Physiology 163: 1118-1125, doi: 10.1016/j.jplph.2005.07.014 Nijsse J, Walther P. and Hoekstra FA. 2004. Cold-induced imbibition damage of lettuce embryos: a study using cryo-scanning electron microscopy. Seed Science Research 14: 117-126, doi: 10.1079/SSR2004161 Olsen L J and Harada JJ. 1995. Peroxisomes and their assembly in higher plants. Annual Review of Plant Physiology and Plant Molecular Biology 46: 123-146, doi: 10.1146/annurev.pp.46.060195.001011 Predieri S, Norman HA, Krizek DT, Pillai P, Mirccki RM, and Zimmerman RH. 1995. Influence of UV-B radiation on membrane lipid composition and ethylene evolution in 'Doyenne d' Hiver' pear shoots grown in vitro under different photo synthetic photon fluxes. Environmental Experimental Botany 35: 151-160., doi: 10.1016/0098-8472(95)00003-2 Probert R.J. 2000. The role of temperature in the regulation of seed dormancy and germination. In: Fenner M. [ed.] Seeds: The Ecology and Regeneration in Plant Communities. 261-291. CAB International, Wallingford, doi: 10.1079/9780851994321.0261 Puntarulo S, Galleano M, Sanchez RA, and Boveris A. 1991. Superoxide anion and hydrogen peroxide metabolism in soybean embryonic axes during germination. Biochimica et Biophysica Acta 1074: 277-283, doi: 10.1016/0304-4165(91)90164-C Sharma A, Bhushan JHA, and Dubey RA. 2011. Oxidative stress and antioxidative defense systems in plants growing under abiotic stresses. In: Pessarakli M, [ed.], Handbook of plant and crop stress. 89-138. CRC press Weiss EA. 2000. Oil Seed Crop. 2nd Edition Blackwell Longman Group Ltd. USA Yaldagard M, Mortazavi SA, and Tabatabaie F. 2008a. Influence of ultrasonic stimulation on the germination of barley seed and its alpha-amylase activity. African Journal of Biotechnology 7: 2465-2471 Yaldagard M, Mortazavi SA, and Tabatabaie F. 2008b. Application of ultrasonic waves as a priming technique for accelerating and enhancing the germination of barley seed: Optimization of method by the Taguchi approach. Journal of the Institute of Brewing 114: 14-21, doi: 10.1002/j.2050-0416.2008.tb00300.x Yeh Y, Chiu MKY, Chen CL, and Sung JM. 2005. Partial vacuum extends the longevity of primed bitter gourd seeds by enhancing their anti-oxidative activities during storage. Science Horticulture 104: 101-112, doi: 10.1016/j. scienta.2004.08.006 COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.04 Agrovoc descriptors: Pisum sativum, peas, phosphorus, phosphate fertilizers, rhizobacteria, Pseudomonas fluorescens, plant growth, plant growth stimulants, growth, crop yield Agris category code: f01, f04 Effects of phosphorus fertilizer rate and Pseudomonas fluorescens strain on field pea (Pisum sativum subsp. arvense (L.) Asch.) growth and yield Bahram SALEHI1 and Hashem AMINPANAH*1 Received October 24, 2014; accepted August 04, 2015. Delo je prispelo 24. oktobra 2014, sprejeto 04. avgusta 2015. ABSTRACT IZVLEČEK A field experiment was conducted at Rezvanshahr, Guilan province, Iran, to evaluate the effects of phosphorus fertilizer rate and Pseudomonas fluorescens strains on growth and yield of field pea (Pisum sativum L.). The experimental design was a randomized complete block in a factorial arrangement with three replicates. Factors were phosphorus fertilizer rates (0, 25, 50, 75, and 100 kg P2O5 ha-1 as triple superphosphate), and seed inoculation with P. florescens strains [control (non-inoculated), inoculated with strain R41, and strain R187). Analysis of variance showed that plant height, seed yield, pod number per m2, 100-seed weight, biological yield, harvest index, and leaf P concentration were significantly influenced by phosphorus fertilizer rate and P. florescens strain. At the same time, phosphorus fertilizer rate x P. fluorescens strain interaction was significant only for 100-seed weight. On the other hand, seed number per pod was significantly affected neither by phosphorus fertilizer rate nor by pseudomonas strains. Result showed that seed yield was significantly increased from 1099 ± 67 to 1898 ± 118 kg ha-1 as P2O5 application rate increased from 0 to 75 kg ha-1, and thereafter relatively remained constant. There was no significant difference in seed yield between plants raised from inoculated seeds with P. fluorescens, strain R187 (1664 ± 97 kg ha-1) and those raised from inoculated seeds with P. fluorescens, strain R41 (1669 ± 104 kg ha-1). At the same time, plants raised from inoculated seeds with P. fluorescens (both strains) produced greater grain yield compared to those raised from uninoculated seeds (1370 ± 80 kg ha-1). Based on the results of this study, P2O5 application at the rate of 75 kg ha-1 and inoculation with pseudomonas bacteria are recommended for obtaining the greatest seed yield in field pea. Key words: phosphorus, plant growth-promoting rhizobacteria, Pisum sativum UČINKI GNOJENJA S FOSFORJEM IN DODATKOV SEVOV BAKTERIJE Pseudomonas fluorescens NA RAST IN PRIDELEK POLJSKEGA GRAHA (P. sativum subsp. arvense (L.) Asch.) Z namenom ovrednotenja vplivov gnojenja z različnimi odmerki fosfornih gnojil in dodatkov sevov bakterije Pseudomonas fluorescens na rast in pridelek poljskega graha (P. sativum subsp. arvense (L.) Asch.) je bil izveden poljski poskus v provinci Rezvanshahr, Guilan, Iran. Načrt poskusa je bil naključni bločni faktorski poskus s tremi ponovitvami. Faktorji v poskusu so bili gnojenje s fosforjem (0, 25, 50, 75 in 100 kg P2O5 ha-1, kot trojni superfosfat) in inokulacija semen s sevi bakterije P. florescens (kontrola (ne inokulirano), inokulirano s sevom R41 in sevom R187). Analiza variance je pokazala, da so na parametre kot so višina rastlin, pridelek zrnja, število strokov na m2, masa 100-semen, biološki pridelek, žetveni indeks in vsebnost P značilno vplivala gnojenja s fosforjem in inokulacija s sevi bakterije P. florescens, vendar je imelo hkratno gnojenje s fosforjem in inokulacija s sevi bakterije P. fluorescens značilen vpliv le na maso 100-semen. Po drugi strani se število semen na strok ni značilno spremenilo niti z različnimi odmerki fosforja niti z dodatki sevov bakterij. Rezultati so pokazali, da se je pridelek zrnja značilno povečal od 1099 ± 67 na 1898 ± 118 kg ha-1, ko se je uporaba P2O5 povečala iz 0 na 75 kg ha-1, in je potem ostal relativno konstanten. Med rastlinami, katerih semena so bila inokulirana s sevom bakterije P. fluorescens, R187 (1664 ± 97 kg ha-1) in tistimi, katerih semena so bila inokulirana s sevom P. fluorescens, R41 (1669 ± 104 kg ha-1) ni bilo značilnih razlik v pridelku zrnja, vendar je bil pridelek zrnja inokuliranih rastlin pri obeh sevih večji od neinokuliranih rastlin (1370 ± 80 kg ha-1). Na osnovi izsledkov te raziskave lahko za doseganje večjih pridelkov poljskega graha priporočamo gnojenje s fosforjevimi gnojili v odmerku 75 kg, P2O5 ha-1 s hkratno inokulacijo s sevi zgoraj omenjenih bakterij. Ključne besede: fosforjeva gnojila, rast-stimulirajoče rizobakterije, Pisum sativum Department of Agronomy and Plant Breeding, Rasht Branch, Islamic Azad University, Rasht, Iran; corresponding author: aminpanah@iaurasht.ac.ir 1 INTRODUCTION Pisum sativum subsp. arvense (L.) Asch., the field pea which is also known as the garden pea, is one of the most important pulse crop. World wide, green peas is produced on 2.25 million ha, with an estimated of total production of 18.5 million tons and dry peas is produced on 6.76 million ha, with an estimated of total production of 10.4 million tons in 2012 (FAO, 2012). Field pea is a cool-season crop which is usually cultivated in early-November and harvested in late-May in northern Iran. Field pea has a high nutritive value, and is high in fiber, protein, vitamins (folate and vitamin C), minerals (iron, magnesium, phosphorus and zinc), and lutein (Urbano et al., 2003). Phosphorus is one of essential nutrients for plant growth and development. Phosphorus regulates protein synthesis in plants, because it is a component of the complex nucleic acid structure. Phosphorus is important in cell division and development of new tissue. Also, phosphorus plays a vital role in plant energy reactions, photosynthesis, respiration, genetic transfer, seed and fruit production, and nutrient transport in plants (Raghothama and Karthikeyan, 2005). Phosphorus is also a component of phytin, a major storage form of P in seeds, phospholipids, and ATP. Moreover, phosphorus promotes root growth and stimulates tillering and often hastens maturity. The responses of leguminous crops to P fertilizer are mainly determined by the soil P available, but are not related to soil organic matter, total N, total P, soil CaCO3 contents, and soil N available (Li et al., 2011). Results show that, when the available P in the soil was less than 10 mg kg-1, P fertilizer gave good effect and application of P fertilizer was required, while above 15 mg P kg-1 the application of P fertilizer alone had no consistent effect (Lin et al., 1964). Li and Li (1992) reported that leguminous crops had different response to P application rate compared to cereal crops. They reported that wheat yield was significantly increased from 2040 to 4491 kg ha-1 as P rate increased from 0 to 97.5 kg ha-1. In contrast, the highest pea yield was at the P rate of 78 kg P ha-1, and thereafter decreased. One of the reasons proposed for explaining the difference in responses to P fertilizer is the higher P demand of legumes than non-legumes. Although P is abundant in soils in both organic and inorganic forms (Khan et al., 2009), the amount of available forms to plants is generally low, because the majority of soil P is found in insoluble forms, while the plants absorb it only in soluble ions (H2PO4- and HPO42- ) (Bhattacharyya and Jha, 2012). To overcome the P deficiency in soils, phosphorus fertilizers must be frequently added to agricultural fields, but regular application of phosphate fertilizers is not only costly but is also environmentally undesirable, as is possible cause of eutrophication. This has led to search for an economically viable and eco-friendly option for improving crop production in low P soils. Legume root is colonized by numerous rhizospheric microorganisms, and these organisms have definite influence on the survival and nodulation ability of seed inoculated rhizobia (Dashti et al., 1998; Davison, 1988). Phosphate solubilizing microorganisms could convert insoluble phosphates into available forms for plant via the process of acidification, chelation, exchange reactions, and production of gluconic acid (Chung et al., 2005; Gulati et al., 2010), and hence a viable substitute to chemical phosphorus fertilizers (Khan et al., 2006). Of the various phosphate solubilizing microorganisms, Pseudomonas flurescens is considered as one of the most significant phosphate solubilizing bacteria, which not only provide P to the plants, but also produce siderophore, antibiotic, and phytohormones such as indole-acetic acid (Leinhos and Nacek, 1994). Some PGPR strains such as pseudomonas (Grimes and Mount, 1984) enhance legume growth, nodulation, and nitrogen fixation when coinoculated with rhizobia. Fluorescent pseudomonads are also known to produce salicylic acid, which acts as local and systemic signal molecules in inducing resistance in plants (De Meyer and Hofte, 1997). Benhamou et al. (1996 a, b) found that Pseudomonas fluorescens induced accumulation of lignin in pea roots. Pseudomonas spp. can form gluconic acid through the oxidative glucose metabolism (Gyaneshwar et al., 2002). Sharma et al. (2003) point out that in 10 ^M Fe-citrate along with Pseudomonas strain GRP3 treatment, chlorophyll a, chlorophyll b and total chlorophyll contents increased significantly by 34, 48 and 39 %, respectively, compared to the control. In a field experiment, van Elsas (1986) reported significant increase in wheat seedling growth after inoculation with pseudomonas and bacillus. Inoculation of plants with PGPR can enhance the drought tolerance (Figueiredo et al., 2008), which can be attributed to the production of IAA, cytokinins, antioxidants and ACC deaminase. Sgroy et al., (2009) declared that several PGPR strains such as Bacillus subtilis, B. licheniformis, B. pumilus, and Pseudomonas putida have crucial roles in cell elongation, increasing ACC deaminase activity, and plant growth promotion. Inoculation of Pseudomonas fluorescens significantly increased total root length, surface area and volume in tomato and cucumber (Saravanakumar et al., 2007). Reduced application rates of chemical fertilizers through inoculation with plant growth-promoting rhizobacteria were proposed by researchers. Adesemoye et al. (2009) found that supplementing 75 % of the recommended fertilizer rate with inoculants produced plant growth, yield, and nutrient (nitrogen and phosphorus) uptake that were statistically equivalent to the full fertilizer rate without inoculants. At the same time, Shaharoona et al. (2008) reported that N use efficiency increased in response to inoculation with Pseudomonas fluorescens at all fertilizer levels in wheat, causing 115 %, 52 %, 26 %, and 27 % increase over the uninoculated (control) at N, P, and K application rates of 25 %, 50 %, 75 %, and 100 % recommended doses, respectively. This experiment was conducted to evaluate the response of field pea growth and yield to different phosphorus fertilizer rate and Pseudomonas fluorescens strains. 2 MATERIALS AND METHODS A field experiment was conducted at Rezvanshahr, Guilan province, Iran, from early-November 2013 to late-May 2014. Some soil properties of the experimental field were presented in table 1. The experimental design was a randomized complete block in a factorial arrangement with three replicates. Factors were phosphorus fertilizer rates (0, 25, 50, 75, and 100 kg P2O5 ha-1 as triple superphosphate which was applied as side placement), and Pseudomonas florescens strains [control (non-inoculated), seed inoculation with strain R41, and strain R187]. These strains were obtained from Soil and Water Research Institute, Karaj, Iran. Some properties of florescent Pseudomonads strains were presented in table 2. Before the inoculation, the Gum Arabic (10 %) was applied to the seeds. Then, the seeds of field pea (P. sativum subsp. arvense 'Utrillo') were inoculated with P. florescens strain R41, or strain R187 in the proportion of 10 g of peat (108 cells/g peat) kg-1 seed according to Ferreira et al. (2010). The inoculated seeds were dried in sunshade for five hours and then were planted in seven 3-m rows spaced 30 cm apart at a density of 10 seeds m-2 (30 seeds in each row) on 5 November. N and K fertilizers were applied just before final land preparation as recommended doses i.e. 15 kg N ha-1 (as starter in the form of urea), and 50 kg K2O ha-1 (as potassium sulphate). Weeds were controlled manually during the experiment. Plants were harvested on 28 May 2014. Plant height was measured from the soil surface to the top of the main stem at harvest stage. Ten randomly selected plants were harvested from each plot at ground level for measuring number of pod per plant, number of seeds per pod, and 100-seed weight. Aboveground biomass from 1 m2 of each plot was oven-dried at 70 °C for 96 h, and weighted for biological yield determination. Seed yield was determined by hand-harvesting the crop plants from 2.5 m2 per plot and was adjusted to 160 g kg-1 seed moisture content. In each plot, field pea leaves were oven-dried at 70 °C for 48 h and grounded to pass through a 1-mm sieve and P concentration were measured using the spectrophotometry method of Lowry and Lopez (1946). Phosphorus concentration was expressed as the percent of leaf dry weight. Analyses of variance were conducted using SAS procedures (SAS Institute, 2004) based on a factorial trial and randomized complete block design. For Pseudomonas fluorescens strains factor, the F-ratios were found to be significant for plant height , pod number per m2, seed number per pod, biological yield and harvest index, so means separations were conducted using fisher's protected LSD at the 5 % probability level. For P rate factor, the F-ratios were found to be significant for plant height, pod number per m2, seed number per pod, biological yield and harvest index, so linear or quadratic regressions with standard error of the mean were used to describe the relationship between P application rate and these dependent 3.25 7.1 54.4 17.2 28.4 sand loam variables. For traits such as 100-seed weight and leaf P concentration, the interaction between Pseudomonas fluorescens strain and P rate was significant. So, for each inoculation level, linear regressions with standard error of the means were used to describe the relationship between P application rate and these dependent variables. otal N Available P Available K (%) (mg kg-1) (mg kg-1) 0.36 0Л1 32 215 Table 1: Some soil properties (0-30 cm) of experimental field prior to sowing OC Sand Silt Clay EC Tt pH Texture (%) (%) (%) (%) (ds m-1) Table 2: Some bacteria properties using for this experiment (Soil and Water Research Institute, Karaj, Iran) Bacteria ACC-deaminase Phosphorus solubilizing IAA production Sherojjlrare pradiiction production activity (mg l-1) diameter) P. fluorescens , , . „ „ . . + + 5.8 0.5 strain R187 P. fluorescens + + 8.9 0.51 strain R41 3 RESULTS AND DISCUSSION 3.1 Plant height Analysis of variance showed that the main effects of phosphorus fertilizer rate and Pseudomonas fluorescens strain were significant for plant height, but the interaction between them was not significant (Table 3). For both Pseudomonas fluorescens strains and for the control, plant height was significantly increased from 72.9 ± 1.02 cm to 86.4 ± 1.71 cm as P2O5 rate increased from 0 to 75 kg ha-1, and thereafter remained statistically constant (Figure 1). Phosphorus plays a vital role in cell division and elongation and, therefore, lower plant height in phosphorus-deficient plants may be due to the reduction in cell division and elongation (Kavanova' et al., 2006). Averaged across P fertilizer rates, the plants raised from seed inoculated with Pseudomonas fluorescens (both strains) was significantly taller than uninoculated ones; however there was no significant difference in plant height between plants raised from seed inoculated with Pseudomonas fluorescens strain R41 and strain R187 (Table 4). Pseudomonas bacteria are considered as one of the most significant phosphate solubilizing bacteria which provide P to the plants. Promotion effect of high P level and pseudomonas bacteria on plant height was probably due to better development of root system and nutrient absorption (Hussain et al., 2006). In addition, Dey et al (2004) observed that inoculation of plant growth promoting rhizobacterial isolates Pseudomonas fluorescens PGPR1 and Pseudomonas fluorescens PGPR2 significantly enhanced the plant height of peanut (Arachis hypogaea L.). 01 f\ Table 3: Mean squares of ANOVA for plant high (H), seed yield (Y), pod number per m (PN), seed number per pod (SP), 100-seed weight (SW), biological yield (BY), harvest index (HI) and leaf P concentration (LPC) as affected by phosphorus rate and Pseudomonas fluorescens strain S.O.V df H Y PN SP SW BY HI LPC R Phosphorus rate (P) Pseudomonas fluorescens strains (Ps) P X Ps Error 2 4 2 7 ns 471** 79* 88109ns 950549** 440924** 1125ns 4123* 4176* 0.1ns 2.4ns 1.7ns 0.2 ns 37.9** 20.2** 391806 ns 2480016** 2346986** 1 ns 114** 13 * 0.00002ns 0.00321** 0.00462** 8 28 3 ns 22 30163ш 47994 431ns 1256 0.1ns 1.1 1.6** 0.4 214903ns 168554 4 ns 4 0.00039** 0.00009 CV (%) - 6 14 7 16 3 7 6 3 *, ** represent significance at 0.05 and 0.01probability level, respectively. ns represents no significant difference Table 4: Averages of plant high (H), seed yield (Y), pod number per m (PN), seed number per pod (SP), biological yield (BY), and harvest index (HI) response to Pseudomonas fluorescens strains as average across P rates ~~ Traits Pseudomonas strains—--- H Y PN SP BY HI Control 79± 1.9 1370 ± 80.0 553± 9.6 6.0± 0.4 4714± 150.0 29.0± 0.7 Pseudomonas fluorescens Strain41 83± 2.1 1669± 104.0 553± 9.6 6.5± 0.3 5420± 176.0 30.8± 0.7 Pseudomonas fluorescens Strain187 83± 1.9 1664± 97.0 524± 9.3 6.7± 0.4 5375± 167.0 30.6± 0.8 LSD (0.05) 3 164 26 0.8 307 1.4 Phosphorus rate (kg ha-1) Figure 1: Effect of phosphorus fertilizer rate on plant height as average across Pseudomonas fluorescens strains. Vertical bars represent ± 1 SE of means Bahram SALEHI and Hashem AMINPANAH 3.2 Seed yield The main effects of phosphorus fertilizer rate and Pseudomonas fluorescens strain were significant for seed yield, while Pseudomonas fluorescens strain X phosphorus fertilizer rate interaction was not significant (Table 3). A quadratic equation (Y = -0.049 X2 +12.96 X + 1103.77, R2= 0.98) provided a good description of the relationship between seed yield and P application rate. Seed yield was significantly increased from 1099 ± 67 to 1898 ± 118 kg ha-1 as P2O5 application rate increased from 0 to 75 kg ha-1, and thereafter relatively remained constant when averaged across Pseudomonas fluorescens strains (Figure 2). Regardless of P application rate, there was no significant difference in grain yield between plants raised from seed inoculated with Pseudomonas fluorescens strain R187 (1664 ± 97 kg ha-1) and those raised from seed inoculated with Pseudomonas fluorescens strain R41 (1669 ± 104 kg ha-1). At the same time, plants raised from seed inoculated with Pseudomonas fluorescens (both strains) produced greater grain yield compared to uninoculated (1370 ± 80 kg ha-1) ones (Table 4). Pseudomonas bacteria not only could convert insoluble phosphates into available forms for plant via the process of acidification, chelation, exchange reactions, and production of gluconic acid (Chung et al., 2005; Gulati et al., 2010), but also could produce siderophore (Dey et al., 2004), ACC-deaminase enzyme (Dey et al., 2004; Shaharoona et al., 2008) and phytohormones such as indole-acetic acid (Leinhos and Nacek, 1994; Dey et al., 2004). At the same time, leaf growth depression under phosphorus deficiency is well documented (Assuero et al., 2004; Kavanova' et al., 2006). Meanwhile, leaf number reduces by P deficiency. Therefore, the reduction in leaf surface area in phosphorus-deficient plants reduces light interception and photosynthesis assimilates, which in turn reduces plant dry matter. Also, the metabolism of N is inhibited with an inadequate supply of P, while the supply of N is necessary to allow crops to use P (Li and Zhao, 1990). 400 - 25 50 75 100 Phosphorus rate (kg ha-1) 0 0 Figure 2: Effect of phosphorus fertilizer rate on seed yield as average across Pseudomonas fluorescens strains. Vertical bars represent ± 1 SE of means 3.3 Pod number per m2 Analysis of variance showed that the main effects of phosphorus fertilizer rate and Pseudomonas fluorescens strain were significant for pod number per m2, but the interaction between them was not significant (Table 3). Regardless of Pseudomonas fluorescens strain, pod number per m2 was increased from 516 ± 12.0 to 574 ± 12.5 pod m-2 as P2O5 application rate increased from 0 to 100 kg ha-1 (Figure 3). Pod number per m2 was significantly higher at inoculated plots (553 ± 9.6 pod m-2 for both strains) than uninoculated ones (524 ± 9.3 pod m-2) as averaged across P application rates (Table 4). The increase in pod number per m2 at high P level may be due to the positive P effects on increasing the flower formation and improving the fruit setting. Dey et al. (2004) reported that pod number in peanut (Arachis hypogaea L.) was significantly increased by inoculation with Pseudomonas fluorescens strain. 500 - 480 J-1-1-1-1-1 0 25 50 75 100 Phosphorus rate (kg ha-1) Figure 3: Effect of phosphorus fertilizer rate on pod number per m2 as average across Pseudomonas fluorescens strains. Vertical bars represent ± 1 SE of means 3.4 Seed number per pod Analysis of variance showed that seed number per pod was not significantly affected by phosphorus fertilizer rate and Pseudomonas fluorescens strains. At the same time, Pseudomonas fluorescens strains X phosphorus fertilizer rate interaction was not significant (Table 3 and 4). 3.5 100- Seed weight Phosphorus fertilizer rate and Pseudomonas fluorescens strains had significant effect on 100-seed weight. Moreover, a significant phosphorus fertilizer rate x Pseudomonas fluorescens strain interaction (P < 0.01) was found for 100-seed weight (Table 3). For uninoculated treatment and strain R41, 100-seed weights were linearly increased as phosphorus fertilizer rate increased from 0 to 75 kg P2O5 ha-1, and thereafter remained relatively constant (Figure 4). In contrast, for strain R187, 100-seed weight was linearly increased as phosphorus fertilizer rate increased from 0 to 100 kg P2O5 ha-1 (Figure 4). Better growth and development of crop plants due to phosphorus supply and nitrogen uptake might have increased the supply of assimilates to seed, which ultimately gained more weight (Ali et al., 2004). This finding is similar to the results of Ali et al. (2004), who reported that the highest 1000-seed weight for chickpea was obtained with seed inoculation and 90 kg ha-1 phosphorus application, while the lowest 1000-seed weight was obtained with uninoculation and zero applied phosphate. In addition, Dey et al. (2004) reported that, in most cases, seed inoculated plants produced significantly greater 100-seed mass over control plants. 32 30 28 5? lm Where W is seed weight, a is the intercept, b is the slope, t is days after anthesis and tm is the end of seed filling period (time of mass maturity). Subsequently, seed filling rate (SFR) was calculated as: SFR = MSW/SFD Where MSW is maximum seed weight and SFD is seed filling duration. At maturity, 10 plants from each plot were harvested and seeds per plant were counted, and then mean number of seeds for each plot was calculated. Finally, 1m2 in the middle of each plot was harvested and seeds detached from the pods and seed yield per unit area was determined. Statistical analysis was performed with MSTATC and SAS soft-wares and Excel soft-ware was used to draw the figures. Duncan test was applied to compare means of each trait at 5 % probability. 3 RESULTS Combined analyses of variance (Table 1) showed significant effects of year on seeds per plant, rate and duration of seed filling and seed yield, but not on maximum seed weight. Maximum seed weight, seed filling duration and seed filling rate were not significantly affected by irrigation intervals, while the effects of irrigation on seeds per plant and seed yield per unit area were significant. Rate and duration of seed filling and maximum seed weight were significantly influenced by radiation deficiency. Interaction of irrigation * light interception was also significant for seeds per plant, seed filling rate and seed yield, but interaction of irrigation * year was only significant for seed yield (Table 1). Table 1: Combined analyses of variance of the effects of different irrigation and shading treatments on soybean Source df Seeds per plant Maximum seed weight Seed filling duration Seed filling rate Seed yield Year(Y) 1 341.47** 2.31 5288.23** 47.87** 146148.51** Rep (Y) 4 94.19 990.3 123.11 3.18 6324.38 Irrigation (I) 3 609.74* 110.68 13.29 0.832 46844.34** Y * I 3 39.3 851.98 26.29 0.471 4605.87** Ea 12 26.26 313.81 78.91 0.758 2442.17 Light (L) 2 29.53 3606.51* 718.09* 19.05* 241.67 I * L 6 126.73** 475.99 74.13 5.21* 8157.65* L * Y 2 8.15 169.89 35.81 0.87 230.31 L * I * Y 6 6.04 217.57 90.45 1.17 1789.64 Eb 32 27.1 438.28 93.37 1.34 1601.53 C.V (%) - 21.05 16 25.74 29.32 22.54 *'** Significant at p<0.05 and p<0.01, respectively Number of seeds per plant in 2012 was higher than that in 2011 (Table 2). Seeds per plant under Ii and I2 decreased, whereas under I3 and I4 increased as a result of radiation deficit. The highest number of seeds per plant was obtained from well watered plants under full sunlight. In general, mean numbers of seeds per plant of soybean under I3 and I4 were lower than that under I1 and I2 (Figure 1). Maximum seed weight and seed filling duration of plants under 25% light (L3) were higher than those under full sunlight (L1) and 65% light (L2). Mean of seed filling duration in 2011 was significantly higher than that in 2012, while seed filling rate in Table 2: Means of maximum seed weight, seed filling treatments in 2011 and 2012 2012 was significantly higher than that in 2011. Seed filling rate of plants under full sunlight was higher than that under shading treatments, with no significant difference between L2 and L3 (Table 2). Plants under full sunlight had the highest seed filling rate under all irrigation treatments. This superiority was more evident under water stress (Figure 2). ation and rate of soybean under irrigation and radiation Treatments Seeds per plant Maximum seed weight (mg) Seed filling duration (day) Seed filling rate (mg day-1) Year 2011 22.55b 130.66a 46.11a 2.83b 2012 26.91a 131.01a 28.96b 4.52a Light interception L1 25.4a 125.15b 32.82b 3.81a L2 25.34a 122.45b 37.67ab 3.25b L3 23.45a 144.91a 42.11a 3.44b Different letters in each column indicate significant difference at P < 0.05. L1, L2, L3: 100 %, 65 % and 25 % light interception, respectively 40 ^ a II 12 13 Irrigation LI □ L2 E3 L3 ffl Figure 1: Seeds per plant under different irrigation and shading treatments. I1, I2, I3, I4: Irrigation after 60, 90, 120 and 150 mm evaporation, respectively. L1, L2, L3: 100 %, 65 % and 25 % light interception, respectively Figure 2: Seed filling rate of soybean under different irrigation and radiation treatments. Ib I2, I3, I4: Irrigation after 60, 90, 120 and 150 mm evaporation, respectively. Lb L2, L3: 100 %, 65 % and 25 % light interception, respectively Seed yield per unit area of plants under all irrigation treatments in 2011 was generally lower than that in 2012 (Figure 3). In general, seed yield under Ii and I2 was higher than that under I3 and I4 in all light interceptions. However, seed yield of plants under I1 and I2 decreased, but under I3 and I4 increased as a result of shading. The highest seed yield was recorded under well watering with full sunlight (Figure 4). 300 -, a a 250 E 200 Y1 Y2 Year □ 11 012013 НИ Figure 3: Seed yield of soybean under different irrigation treatments in 2011 (Y1) and 2012 (Y2). I1, I2, I3, I4: Irrigation after 60, 90, 120 and 150 mm evaporation, respectively Figure 4: Seed yield of soybean under different irrigation and radiation treatments. Ib I2, I3, I4: Irrigation after 60, 90, 120 and 150 mm evaporation, respectively. Lb L2, L3: 100 %, 65 % and 25 % light interception, respectively 4 DISCUSSION Similar maximum seed weight in two years was the result of longer seed filling duration in 2011 and higher seed filling rate in 2012 (Table 2). It has been reported that seed filling rate (Ghassemi-Golezani et al. 2009) and seed filling duration (De Souza et al. 1997) are positively associated with maximum seed weight in soybean. Although seed filling rate of plants under shade was lower than that under full sunlight, lower radiation increased seed filling duration (Table 2) as a result of decreasing temperature (Ghassemi-Golezani et al. 2013). Seed filling duration under low radiation (L3) was about 9 days longer than that under full sunlight (Li), leading to 15.8 % enhancement in maximum seed weight. Similarly, Nasrullahzadeh et al. (2007) reported that delaying physiological maturity under low light increases seed filling duration and consequently mean seed weight of faba-bean. Hadi et al. (2006) also showed that reduction in radiation could increase seed filling duration and mean seed weight of common bean. Seed weight is determined during the seed filling process and duration of seed filling is an important component of maturity (Monpara 2011). Reduction in seed filling rate due to shading, particularly under severe water stress (Figure 2) may be associated with reduction in cotyledon cell division and cell number of soybean. It has been suggested that both cotyledon cell number and assimilate supply are important in determining seed growth rate (Egli et al. 1989). According to Egli and Bruening (2001), reduction in assimilate availability due to shading decreases seed filling rate and increases effective filling period in soybean. Anyway, variation in seed filling rate under different light interceptions had no significant effect on final seed weight of soybean (Table 2). Increasing seed filling rate of non-shaded plants with increasing water stress (Figure 2) is the result of early senesces (Bahrani et al. 2009). It has been reported that under water deficit, particularly when there is access to carbohydrates either directly from the leaf photosynthesis or from those prestored in stems or leaves, seed filling rate increases (Ahuja et al. 2008). Yang et al. (2001) suggested that an altered hormonal balance in rice seeds by water stress during seed filling, especially a decrease in GAs and an increase in ABA, enhances the remobilization of pre-stored carbon to the seeds and accelerates the seed filling rate. Since there was no significant difference in maximum seed weight between two years (Table 2), higher seed yield in 2012 (Figure 3) resulted from greater number of seeds per plant under all irrigation treatments (Figure 1). However, decreasing seed yield of soybean under well watering and mild water stress and improving it under moderate and severe water deficit due to light deficit (Figure 4) are directly related with changes in seed filling duration and consequently in seed weight (Table 2) and number of seeds per plant (Figure 1) under these conditions. 5 CONCLUSION Plants could be subjected to different levels of shading or solar radiation in intercropping, agroforestry and cropping under fruit trees. Water deficit may also occur in these conditions. Therefore, it is very important to understand the interactive effects of water and radiation deficits. The results of this research clearly showed that shading could reduce the drought impact on soybean plants via enhancing seed filling duration, seed weight, seeds per plant and consequently seed yield per unit area due to reducing temperature. However, soybean is not an appropriate crop to grow under shade, when water supply is sufficient. Similar works on different crops, particularly on shade tolerant plants, can improve our knowledge about these interactions. 6 REFERENCES Ahuja L.R., Reddy V.R., Saseendran S.A., Qiang Y. 2008. Current water deficit stress simulations in selected agricultural system models. In: Saseendran S.A., Ahuja L.R., Ma L. (Eds.). Response of crops to limited water, American Society of Agronomy, Madison, USA, pp. 1-38 Bahrani A., Heidari-Sharifabad H., Tahmasebi-Sarvestani Z., Moafporian G.H., Ayenehband A. 2009. Wheat response to nitrogen and post-anthesis water deficit. Proc Int Conf on CBEE, Singapore. pp. 33-34. Bell G.E., Dannenberger T.K., McMaho M.G. 2000. Spectral irradiance available for turfgrass growth in sun and shade. Crop Sci., 40: 189-195, DOI: 10.2135/cropsci2000.401189x Bertolli S.C., Rapchan G.L., Souza G.M. 2012. Photosynthetic limitations caused by different rates of water-deficit induction in Glycine max and Vigna unguiculata. Photosynthetica, 50: 329-336, DOI: 10.1007/s11099-012-0036-4 Desclaux D., Huynh T., Roumet P. 2000. Identification of soybean plant characteristics that indicate the timing of drought stress. Crop Sci., 40: 716-722, DOI: 10.2135/cropsci2000.403716x De Souza P.I., Egli D.B., Bruening W.P. 1997. Water stress during seed filling and leaf senescence in soybean. Agron. J., 89: 807-812, DOI: 10.2134/agronj1997.00021962008900050015x Dumoulin V., Ney B., Eteve G. 1994. Variability of seed and plant development in pea. Crop Sci., 34: 992-998, DOI: 10.2135/cropsci1994.0011183X003400040030x Egli D.B., Bruening W.P. 2001. Source-sink relationship, seed sucrose levels and seed growth rates in soybean. Ann. Bot., 88: 235-242, DOI: 10.1006/anbo.2001.1449 Egli D.B., Bruening W.P. 2004. Water stress, photosynthesis, seed sucrose levels and seed growth in soybean. J. Agr. Sci., 142: 1-8, DOI: 10.1017/S0021859604004095 Egli D.B., Ramseur E.L., Zhen-Wen Y., Sullivan C.H. 1989. Source-sink alterations affect the number of cells in soybean cotyledons. Crop Sci., 29: 732-735, DOI: 10.2135/cropsci1989.0011183X002900030039x Ghassemi-Golezani K., Bakhshi J., Zehtab-Salmasi S., Moghaddam M. 2013. Changes in leaf characteristics and seed yield of soybean (Glycine max L.) in response to shading and water stress. Int. J. Biosci., 3: 71-79.DOI: 10.12692/ijb/3.2.71-79 Ghassemi-Golezani K., Taifeh-Noori M., Oustan S.H., Moghaddam M. 2009. Response of soybean cultivars to salinity stress. J. Food, Agri. Environ., 7: 401- 404 Hadi H., Ghasesemi-Golezani K., Rahimzadeh Khoei F., Valizadeh M., Shakiba M.R. 2006. Responses of common bean (Phaseolus vulgaris L.) to different levels of shade. J. Agro., 5: 595-599, DOI: 10.3923/ja.2006.595.599 Kobata T., Takami T. 1986. Changes in respiration, dry matter production and its partition in rice (Oryza sativa L.) in response to water deficit during seed filling period. Bot. Mag., 99: 379- 393, DOI: 10.1007/BF02488717 Ludlow M.M., Muchow R.C. 1990. A critical evaluation of traits for improving crop yields in water-limited environments. Adv. Agro., 43: 107153, DOI: 10.1016/S0065-2113(08)60477-0 Messina M. (1997): Soyfoods: Their role in disease prevention and treatment. In: Liu K. (Ed.). Soybeans: Chemistry, technology and utilization, Chapman and Hall, New York, USA, pp. 442-466, DOI: 10.1007/978-1-4615-1763-4_10 Mc Williams D.A., Berglund D.R., Endres G.J. 2004. Soybean growth and management. North Dakota State University. University of Minnesota. Monpara B.A. 2011. Seed filling period as a measure of yield improvement in bread wheat. J. Crop Imp., 38: 1-5. Nasrullahzadeh S., Ghassemi-Golezani K., Javanshir A., Valizade M., Shakiba M.R. 2007. Effects of shade stress on ground cover and seed yield of faba bean (Vicia faba L.). J. Food Agri. Environ., 5: 337- 340. Ney B., Duthion C., Fontaine E. 1993. Timing of reproductive abortion in relation to cell division, water content, and growth of pea seeds. Crop Sci., 33: 267-270, DOI: 10.213 5/cropsci1993.0011183X003300020010x Salimi S., Moradi S. 2012. Effect the correlation, regression and path analysis in soybean genotypes (Glycine Max L.) under moisture and normal condition. Int. J. Agro. Plant Prod., 3: 447-454. Wong G.G. 1991. Shade tolerance of tropical forages: A review. In: Shelton HM, Stuart WW (Eds). Forages for plantation crops, Australian Center for International Agricultural Research, ACIAR Proceedings, Canberra, Australia, pp. 64-69 Yang J., Zhang J., Wang Z., Zhu Q., Wang W. 2001: Hormonal changes in the seeds of rice subjected to water stress during seed filling. Plant Physiol., 127: 315-23, DOI: 10.1104/pp.127.1.315 Zhao D., Oosterhuis D. 1998. Cotton responses to shade at different growth stages: Nonstructural carbohydrate composition. Crop Sci., 38: 11961203, DOI: 10.2135/cropsci1998.0011183X003800050014x COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.06 Agrovoc descriptors: allelopathy, biological competition lettuce, Lactuca sativa, cannabis, Cannabis sativa, seed germination, germination, extracts Agris category code: f01, f62 Allelopathic effect of medicinal plant Cannabis sativa L. on Lactuca sativa L. seed germination Homa MAHMOODZADEH1*, Mohsen GHASEMI2, Hasan ZANGANEH1 Received April 24, 2015; accepted July 20, 2015. Delo je prispelo 24. aprila 2015, sprejeto 20. julija 2015. ABSTRACT IZVLEČEK In order to examine allelopathic effect of Cannabis sativa L. on germination capability and seedling growth of Lactuca sativa L., a study was performed in laboratory conditions. Treatments were set up in randomised block design in four replications for each of four concentration ranges of 25, 50, 75 and 100 % of aqueous extract made of shoot parts and 4 identical extract concentrations made of root of cannabis. Control variant was lettuce seed treated by distilled water. During the studies shoot and seminal root length of lettuce seedlings were measured after treatments with different concentrations of extracts made of root and shoot parts of cannabis, and the obtained values were compared with the control. The obtained results suggest that the extract from the shoot parts of cannabis in high concentrations of 75 and 100% had inhibiting effect to the germination indices while the extract from the root had no statistically significant effect on germination of lettuce seeds. Extract made of root part of cannabis showed also stimulatory effect to shoot and seminal root length of lettuce seedlings in extract concentrations of 50, 75 and 100 %. Key words: allelopathy, lettuce, aqueous extract, cannabis, seed germination indices ALELOPATIČEN UČINEK KONOPLJE (Cannabis sativa L.) NA KALITEV SEMEN VRTNE SOLATE (Lactuca sativa L.) V laboratorijskih razmerah je bil preučevan alelopatičen učinek navadne konoplje (Cannabis sativa L.) na kalitev semen in rast kalic vrtne solate (Lactuca sativa L.). Obravnavanja so bila izvedena kot naključni bločni poskus v štirih ponovitvah z vsako od štirih koncentracij, 25, 50, 75 in100 %, vodnega izvlečka poganjkov in korenin konoplje. V kontrolnem poskusu so bila semena vrtne solate tretirana na enak način z distilirano vodo. Poleg indeksa kalitve sta bili v poskusi merjeni še dolžina poganjkov in semenskih korenin kaleče solate. Rezultati so pokazali, da je imel izvleček poganjkov konoplje v večjih koncentracijah, 75 in 100 %, inhibitorni učinek na kalitveni indeks, medtemko izvlečki iz korenin niso imeli statistično značilnega vpliva na iste merjene parametre. Izvleček iz korenin konoplje je imel stimulativni učinek na dolžino poganjkov in semenskih korenin vrtne solate pri koncentracijah 50, 75 in 100 %. Ključne besede: alelopatija, vrtna solata, vodni izvleček, konoplja, kalitveni indeks 1 INTRODUCTION Hundreds of medicinal plant species are being used in modern medicines. They have been used as remedy for different diseases e.g. fever, malaria, cough, flu, asthma, colds, chest diseases, skin itch, acne, headache, jaundice, nausea, ulcer, tumors, typhus, stomach pain, heart attack, chills, inflammation, herpes, hepatitis, swelling, etc (Ishaque and Shahni, 1998). Most of them have been collected from wild sources. There is an increasing demand for medicinal plants-based 1 Department of Biology, Faculty of Science, Mashhad Branch, Islamic Azad University, Mashhad, Iran; corresponding author: homa_mahmoodzadeh@yahoo.com Department of Agriculture, Mashhad Branch, Islamic Azad University, Mashhad, Iran 2 drugs and pharmaceuticals in the world market. However, pharmaceutically active compounds can also behave as allelochemicals. These allelopathic compounds can also be used as natural herbicides and other pesticides (Einhelling, 1995).The term "allelopathy" was proposed for expressing the harmful, stimulatory, enhanced and beneficial effects that one plant species has on another through the formation of chemical retardants escaping into the environment (Molisch, 1937). Allelochemicals are plant metabolites present in plants as end products and by-products. These chemicals are present in different parts of plants like stem, leaves, roots, flowers, inflorescence, fruits and seeds. Out of these plant parts, leaves seem to be the most consistent producers of these allelochemicals. These allelochemicals are often released from the plants by volatilization, leaching, exudation and decomposition from plant residues (Molisch, 1937). Major allelochemicals found in plants with documented allelopathic activity are phenolic compounds (Chon et al., 2002) that have stimulatory effects on seed germination and seedling growth of plants. This is generally accepted in the literature that phenolic compounds at low concentrations are stimulatory to germination and plant growth (Hegab et al., 2008; Ghareib et al., 2010), but higher concentrations resulted in a sharp germination reduction. The well-known terpenoids include menthol, camphor, thujone and the cannabinoids are found in Cannabis sativa (Ameh et al., 2010). Allelopathics are often due to synergistic activity of allelochemicals rather than to single compounds. The additive or synergistic effects become significant even at low concentrations of the extracts (Einhelliing, 1995). The concept of allelopathy was further supported and developed by Bonner (1950), Grummer and Beyer (1960), Evenari (1961), Whittaker (1970), Pitman and Duke (1978) and Fischer et al. (1978). According to Lavabre (1991), allelopathic effects are controversial and still poorly understood. In allelopathy, a major tool for research is bioassay which controls laboratory conditions, high sensitivity gives reproducible results, and takes relative short time to perform. There are many ways to evaluate the herbal aqueous extracts of allelopathic activities. These are hydroponic culture methods, Ratoon screening method, Plant box method (Lee et al., 2003), a plastic tray with 6 holes (Fujii et al., 2004), Dish pack method - a new bioassay for volatile allelopathy (Fujii et al., 2005), Sandwich method (Fujii et al., 2003) and Filter paper (Barbosal et al., 2008). The filter paper is a suitable method because it can tolerate the moderate temperature during incubation (25 °C) in the laboratory. The aqueous extracts remain stable for longer period of time. Millipore filter paper is used to make the method sterile. The reason for the use of filter paper in techniques is that, it is easily available and free from contamination. It is easily handled and a good media for germination, it has high flow rate for movement of extracts and porosity (Gill et al., 2009). Allelopathic effect of medicinal species against other plants is well studied (Wahab et al., 1967; Rice, 1971; Han et al, 2008 and Li et al., 2009). Cannabis sativa is known for centuries as an effective weeds suppressing crop plant in Iran. Weeding role of this plant is mainly attributed to its high competitiveness for water, food and light, as it overshadows the soil quickly after the initial growth phase and therefore suppresses weed growth (Ranalli, 1999). In general, crop rotation and related practices should aim to give the competitive advantage to the crops in rotation against weeds. Only few studies concerned the rotation effects of Cannabis sativa, as an annual crop, fits well into crop rotation and can serve to the control of pests, as it is not related to conventional food crop species (Ranalli, 1999), hence the main purpose of the present study is to evaluate the allelopathic activity of medicinal plant, Cannabis sativa L. ssp. sativa on lettuce (Lactuca sativa L.). 2 MATERIALS AND METHODS 2.1 Plant material and extraction procedure In the period 2013-2014, at farms near Mashhad, parts of C. sativa L. ssp. sativa ('TN-96-35') were collected. Plant material was divided into shoot, i.e. stem plus leaf and root. Shoot and root parts were pulverized, after which separate extracts were made from each of these parts of of C. sativa L. Ten g of fresh shoot or root parts were mixed with 100 ml distilled water in a blender. The homogenate was filtered through tissue paper after 10 minutes and the filtrate was centrifuged at 3000 X g for 20 min and the supernatant was used as stock solution. Extract of shoot and and root part of C. sativa was made in a range of concentrations of 25, 50, 75 and 100 % of stock solution 2.2 Seed germination test Filter paper in Petri dishes, of 150 x 25 mm in size was moistened by 5 ml of the obtained extracts, and tested lettuce seed was germinated on it. Control was moistened by distilled water. Lettuce seed (Lactuca sativa'Longifolia') surface was sterilized before adding of extracts according to Elemar and Filho (2005). Each concentration of C. sativa extracts was made in four replications. Samples were laid in thermostatic device at 22 ± 2°C for 7 days. Laboratory tests were set up in randomized block design in four replications. Each Petri dish contained 25 lettuce seeds, i.e. 100 seeds per treatment. Germination tests were performed according to the rule issued by the International Seed Testing Association. The number of germinated seeds was noted daily for 7 days. Seeds were considered as germinated when their seminal root reached at least 1 mm length. In this study, we used following germination parameters: Germination percentage (GP, %), Germination rate (GR), Relative germination percentage (RGP), Mean germination time (MGT), Germination index (GI) and Weighted germination index (WGI). Final percentage germination (GP) for each treatment was calculated after seven days. The germination index (GI) is based on number of seeds that germinated and the germination rate. These parameters were also calculated from the formulas proposed by (Figueroa and Armesto, 2001; Bu et al., 2007; Wu and Du 2007). GP = 100 X GN / SN (1) GN is the total number of germinated seeds, SN is the total number of seeds tested RGP = GP treatment / GP control x 100 (2) GI = (I(N-i) X Gi) X 100)/(N X GN) (3) GI is a synthetic measure designed to reflect the synthetical germination ability including germination rate and germination numbers. Where i is the number of days since the day of sowing and Gi is the number of seeds germinated on day i. A weighted germination index (WGI) as described by Bu et al. (2007) was calculated with maximum weight given to the seeds germinating early and less to those germinating late WGI = [NXn1+(N-1) X n2+(N-Z) Xn3+...]/ NxN' (4) where n1, n2, ..., n60 are the number of seeds that germinated on first, second, and subsequent days until the 60th day, respectively; N is total days of experiment; N' is the total number of seeds placed in incubation GR = I Gi / I ni Gi (5) Where i is the number of days since the day of sowing and Gi is the number of seeds germinated on day i Vigor index = germination % x seedling length (root + shoot). (6) After an incubation period of 7 days, shoot and seminal root length of seedlings were measured using a ruler. 2.3 Data analysis Significant differences for all statistical tests were evaluated at the level of p < 0.05 with ANOVA. All data analyses were conducted using SPSS for Windows, Version 13.0. 3 RESULTS Based upon conducted studies, data on effect of extracts made of shoot and root parts of C. sativa to germination indices and seedling growth of L.sativa were obtained. Extracts made from shoot parts in concentrations of 75 and 100 % showed significant effects on germination indices and seedling growth of lettuce including: germination percent, relative germination percent, germination rate, mean germination time, weighted germination index and seminal root length, while all concentrations of shoot extracts of C. sativa showed no significant effect on germination index, vigor index and shoot length. Measured values of lettuce seed germination treated by extract of the shoot parts of C. sativa confirmed that extract showed allelopathic - inhibitory effect to the germination indices and growth of seminal root in comparison to the obtained control values. The obtained results for extract concentration of 75 % made of shoot parts of C. sativa showed that germination percent and relative germination percent were 90 % which was less in comparison to the value of control of 100 %; for the medium extract concentration of 100 % determined germination percent was 76.67 %. For mean germination time, at higher concentrations were also established lower values. For extract concentration of 75 %, MGT was 4.8 days, whereas in the highest concentration of 100 %, MGT of lettuce seeds was the lowest, i. e. 4.53 in comparison to control variant that was 5 days. For concentration of 100 % of extract made of shoot parts of C. sativa, the average value of WGI was 0.84, and control was 1, for concentration of extract of 75 %, the established value of WGI was 0.93,while control was 8.09. Concentration of 75 % and 100 % resulted in GR of 0.45 and 0.38 Nday-1, respectively, with control value of 0.5 Nday-1. For variant of 75 % of extract from the shoot parts of C. sativa, lettuce seminal root length was 2.3 cm. while control was 3.3 mm, the application of highest concentration of extract made of shoot part of 100 % resulted in average seminal root length of 2.1 cm. Duncan test showed statistically significant difference (P<0.05) between the most germination indices of lettuce seed only in the case of the extract made of the shoot parts of C. sativa in concentration of 75 and 100 % (Table 1). Table 1: Statistical data (mean ± standard error) on effects of the shoot parts of Canabis sativa L. to germination of lettuce seeds Shoot extract (%) GP(%) GR(Nd-1) RGP MGT(day) GI WGI VI Shoot length(cm) Seminal root length(cm) 0 100± 0 0.5± 0 100± 0 5± 0 33.3± 0 1 ±0 506.67± 110 2.1 ±0.65 3.3± 0.26 25 96.67± 5.7 0.48± 0.02 96.67 ±5.7 4.93± 0.11 32.2± 1.9 0.97± 0.04 575.6± 89 2.86± 0.7 3.06± 0.11 50 90± 10 0.45± 0.05 90± 10 4.8± 0.2 29.9± 3.3 0.93± 0.07 457.3± 57.9 2.4± 0.45 2.7± 0.46 75 *90± 0 *0.45± 0 *90± 0 * 4.8 ±0 33.3± 0 *0.93± 0 483± 99 2.8± 0.36 *2.3 ±0.6 100 *76.67± 15.2 *0.38± 0.07 *76.67 ± 15.2 *4.53 ±0.3 26.6± 6.6 *0.84± 0.1 361± 58.9 2.6± 0.26 *2.1± 0.32 *Marked differences are significant at p<0.05 Bioassay revealed that for extract of the root of C. sativa there were no statistically significant deviations between values of lettuce seed GP, RGP, MGT, GI, VI from control values. For variant of 25, 75 and 100 % of extract from the root parts of C.sativa, WGI of lettuce seeds was 0.97, while control was 1. The application of highest concentration of extract made of root part of 100 % resulted in average GR of 0.46 Nday"1, whereas the average GR in control was 0.5 Nday-1. Length of lettuce seminal root in treatment with the 75 and 100 % extracts made of the root part of C. sativa confirmed stimulatory effect in comparison to the control variant. Extract made of root part of C. sativa also did show stimulatory effect to shoot length in extract concentrations of 50 % (Table 2). Table 2: Statistical data on effects of the root parts of Canabis sativa L. to germination of lettuce seeds Root GP(%) GR(Nd-1) RGP MGT(da GI WGI VI Shoot Seminal root extract(%) y) length(cm) length(cm) 0 100± 0 0.5± 0 100± 5± 0 33.3± 1± 0 506.67± 2.1± 0.65 3.3± 0.26 0 0 110 25 96.67 0.48± 100± 4.93± 32.2± *0.97± 382.6± 2.1 ±0.55 3.3± 0.47 ±5.7 0.02 0 0.11 1.9 0.04 105 50 96.67 0.5 ±0 100± 5± 0 33.3± 1± 0 322± 2.1± 0.52 2.9± 0.3 ±5.7 0 0 42.3 75 96.67 0.48 96.67 4.93± 32.2 *0.97± 314± *3.36± 0.46 *4.3 ±0.85 ±5.7 ±0.02 5.7± 0.11 ± 1.9 0.04 16.9 100 93.33± *0.46 96.67 5.26± 31.1 *0.97± 197.3± 2.6± 0.57 *4.3± 0.51 5.7 ±0.02 5.7± 0.64 ± 1.9 0.04 62 *Marked differences are significant at p<0.05 4 DISCUSION In the study, allelopathic effect of the medicinal plant, C. sativa was established for germination indices and early growth of lettuce. Extracts made of shoot parts of C. sativa showed inhibitory effects to lettuce seed germination indices except from GI and VI. Extract made of the shoot parts, in concentration of 75 and 100 % significantly affected mentioned factors, while the lower two concentrations did not show a significant effect. Extracts made of shoot parts of C. sativa did not show statistically significant effect to shoot growth in any concentration. Extracts made of shoot part of C. sativa in concentrations of 75 and 100 % showed statistically significant effect to the growth of seminal root, while concentrations of 25 and 50 % had no statistically significant effect. The seeds imbibed with shoot extracts of C. sativa delayed and inhibited germination in comparison to control. The inhibitory effect of different concentrations of shoot extract of C. sativa on seed germination might be due to imbalance in metabolism regulated by various enzyme activities (Oyun, 2006). The structure of plasma membrane might have become denatured by the phytotoxins present in shoot extract of C. sativa when the seeds were soaked in extract. Positive correlation was observed between the increase in the concentration of extract and the inhibition of germination percentage. Allelochemicals are known to inhibit the metabolic processes i.e. cellular respiratory ability of the target plant and energy transfer which is responsible for ATP synthesis (Demos et al., 1974). The phytotoxins present in shoot extracts of C. sativa might have arrested the protease, a -amylase activity resulting in inhibition of protein and starch breakdown which reduces the germination process. Extract made of root part of C. sativa had stimulatory effect to shoot and seminal root length in extract concentrations of 50, 75 and 100 %. The similar phenomenon was observed by other authors (Sun et al., 2006) analyzing the allelopathic effect of Solidago canadensis L. on rape. Anjum et al. (2010) performed laboratory experiments to examine the allelopathic potential of some medicinal plants on the germination and growth of lettuce. Using sandwich method, Albezzia lebbeck (L.) Benth. and Broussonetia papyrifera (L.) Vent. have strong inhibitory effects on the seminal root and hypocotyls growth of lettuce. However, stimulatory effects were recorded with C. sativa and Parthenium hysterophorus L. at 5mg leaves concentrations (Anjum et al., 2010). Extract from the shoot parts of C. sativa has a higher inhibitory effect to lettuce germination and seedling growth than extract from roots. Contents of biologically active compounds in shoot and root parts of C. sativa are probably different both qualitatively and quantitatively. 5 CONCLUSIONS Higher content of allelochemicals present in extract of shoot parts of C. sativa may be responsible for the inhibition of metabolic activities of lettuce in the laboratory bioassay tests The study revealed reduced germination capability of lettuce seeds after treatment by extract made of the shoot parts of C. sativa which was supported by calculated statistical significance that indicated existence of allelopathic effect. Extract made from the roots of C. sativa did not have allelopathic effect to the growth of lettuce and seed germination. 6 REFERENCES Ameh S.J., Obodozie O., Inyang U. S., Abubakar M.S., Garba M. 2010. Current phytotherapy - A perspective on the science and regulation of herbal medicine. Journal of Medicinal Plants Research. 4(2): 72-81 Anjum A.U., Hussain Z., Yousaf F.K. and Umer A. 2010. Evaluation of allelopathic action of some selected medicinal plant on lettuce seeds by using sandwich method. J. Med. Plants Res. 4: 536-541 Barbosal G.E., Vania R.P., Sérgio T.M. 2008. Allelopathic evidence in Brachiaria decumbens and its potential to Invade the Brazilian Cerrados. Rua do Matao, Travessa 14; Cidade Università. 51(4):825-831 Bonner J. 1950. The role of toxic substances in interaction of higher plants. Bot. Rev. 16: 51-65, doi: 10.1007/BF02879785 Bu H.Y., Chen X.L., Wang Y.F. 2007. Germination time, other plant traits and phylogeny in an alpine meadow on the eastern Qinghai-Tibet plateau. Community Ecology. 8: 221 - 227, doi: 10.1556/ComEc.8.2007.2.8 Chon S.U., Choi S.K., Jung S., Jang H.G., Pyo B.S., Kim S.M. 2002. Effects of alfalfa leaf extracts and phenolic allelochemicals on early seedling growth and root morphology of alfalfa and barnyard grass. Crop Prot. 21: 1077-1082, doi: 10.1016/S0261-2194(02)00092-3 Demos E. K., Woolwine M., Wilson R. H., McMillan, C. 1975. The effect of ten phenolic compounds on hypocotyl growth and mitochondrial metabolism of mungbean. American Journal of Botany. 62:97102, doi: 10.2307/2442083 Einhelling F.A. 1995. Characterization of mechanisms of Allelopathy Modeling and experimental approaches. In: cheng Idergit HH and Dakshini KMM. (eds), allelopathy, organism, processes and applications. American Chemical Society, Washington, pp 132-141 Elemar V., Filho V. 2005. Allelopathic effects of aconitic acid on wild poinsettia (Euphorbia heterophylla) and morningglory (Ipomoea grandifolia). Brazilian Society on Weed Science Congress, 40(1):217 Evenari M. 1961. Chemical influence of other plants (allelopathy Handbuch der pflanzen-Physiol. 16: 691-736 Figueroa J.A., Armesto J.J. 2001. Community-wide germination strategies in a temprate rainforest of southern chile: ecological and evolutionary correlates. Australian Journal of Botany 49: 411 -425, doi: 10.1071/BT00013 Fischer R.F., Woods R.A., Glavicic M.R. 1978. Allelopathic effects of goldrod and ashes on young sugar maple. Canadian J. Res. 8: 1-9, doi: 10.1139/x78-001 Fujii Y., Parvez S.S., Parvez M.M., Ohmae Y., Iida, O. 2003. Screening of medicinal plant species for allelopathic activity using Sandwich method. Weed Biol. Manage. 3: 233-241, doi: 10.1046/j.1444-6162.2003.00111.x Fujii Y., Shibuya T., Nakatani K., Itani T., Hiradate S.M., Parvez M. 2004. Assessment method for allelopathic effect from leaf litter leachates. Weed Biol. Manage. 4: 19-23, doi: 10.1111/j.1445-6664.2003.00113.x Ghareib H.R.A., Abdelhamed M.S., Ibrahim O.H. 2010. Antioxidative effects of the acetone fraction and vanillic acid from Chenopodium murale on tomato plants.Weed Biol. Manage. 10: 64-72, doi: 10.1111/j.1445-6664.2010.00368.x Gill G., Anoliefo L.S., Iduoze U.V. 2009. Allelopathic effects of aqueous extract from Siam Weed on the growth of Cowpea. Department of Botany, University of Benin, Benin City, Nigeria 3rd . edi. pp. 3-20 Han C.M., Pan K.W., Wu N., Wang J.C., Li W. 2008. Allelopathic effect of ginger on seed germination and seedling growth of soybean and chive. Sci. Hortic. 116(3): 330-336, doi: 10.1016/j.scienta.2008.01.005 Hegab M.M., Khodary S.E.A., Hammouda O., Ghareib H. R. 2008. Autotoxicity of chard and its allelopathic potentiality on germination and some metabolic activities associated with growth of wheat seedlings. Afr. J. Biotechnol. 7: 884-892 Inderijt I., Duke S.O. 2003. Ecophysiological aspects of allelopathy. Planta 217: 529-539, doi: 10.1007/s00425-003-1054-z Ishaque M., Shahan M.N.I. 1998. Survey and domestication of wild medicinal plants of Sindh. Survey report. KAKC, Islamabad Pakistan pp. 2-3 Lavabre E.M. 1991. Weed control, McMillan Education Ltd. London. pp. 1-10 Lee S.B., Kim K.H., Hahn S.J., Chung I.M. 2003. Evaluation of screening methods to determine the allelopathic potential of rice varieties against Echinochloa crus-galli Beauv. var. oryzicola Ohwi, Allelopathy J. 12: 37-52 Li H.Y., Pan K.W., Liu Q., Wang J.C. 2009. Effect of enhanced ultraviolet-B on allelopathic potential of Zanthoxylum bungeanum. Sci. Hortic. 119(3): 310314, doi: 10.1016/j.scienta.2008.08.010 Molisch H. 1937. Der einfluss einer pflanze auf die andere Allelopathie. The role of chemical inhibition in Vegetational. pp. 99-106 Oyun M. B. 2006. Allelopathic potentialities of Gliricidia sepium and Acacia auriculiformis on the germination and seedling vigour of maize. American Journal of Agricultural and Biological Sciences. 1(3): 44 - 47, doi: 10.3844/ajabssp.2006.44.47 Pitman A.R., Duke W.B. 1978. Allelopathy in agroecosystem. Annu. Rev. Phytopathol. 16: 431451, doi: 10.1146/annurev.py.16.090178.002243 Ranalli P. 1999. Agronomical and physiological advances in hemp crops. In:Advances in Hemp Research Haworth Press Binghamt, NY, USA, pp.61-84 Rice E.L. 1971. Possible role of Ambrosia psilostachya patterning and succession in old fields. Am. Midland Naturalist. 86: 344-357, doi: 10.2307/2423628 Rice E. L. 1984. Allelopathy. II edition. New York: Academic Press. 421 Sun B., Tan J., Wan Z., Gu F., Zhu M. 2006. Allelopathic effects of extracts from Solidago canadensis L. against seed germination and seedling growth of some plants. J. Environ. Sci. 18:304-309 Wahab A., Niel A.S., Rice E.L. 1967. Plant inhibition by Johnson grass and its possible significance in old field succession. Bull. Torrey Bot Club, 94: 486-487, doi: 10.2307/2483566 Whittaker R.H. 1970. The biochemical ecology of higher plants. In Sondheimer, E. and B. Simeone (eds.), Chemical Ecology, Academic Press, N.Y., USA, pp. 43-70, doi: 10.1016/b978-0-12-654750-4.50009-8 Wu G.L., Du G.Z. 2007. Germination is related to seed mass in grasses ( Poaceae) of the eastern Qinghai -Tibetan plateau, China. Nordic Journal of Botany 25: 361 - 365, doi: 10.1111/j.0107-055X.2007.00179.x COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.07 Agrovoc descriptors: rice, oryza, nitrogen fertilizers, rhizobacteria, azotobacter, Azospirillum, plant growth stimulants, growth, crop yield Agris category code: f01, fo4, f62 Grain, milling, and head rice yields as affected by nitrogen rate and bio- fertilizer application Saeed FIROUZI2 Received May 29, 2014; accepted August 22, 2015. Delo je prispelo 29. maja 2014, sprejeto 22. avgusta 2015. ABSTRACT IZVLEČEK To evaluate the effects of nitrogen rate and bio-fertilizer application on grain, milling, and head rice yields, a field experiment was conducted at Rice Research Station of Tonekabon, Iran, in 2013. The experimental design was a factorial treatment arrangement in a randomized complete block with three replicates. Factors were three N rates (0, 75, and 150 kg ha-1) and two bio-fertilizer applications (inoculation and uninoculation with Nitroxin, a liquid bio-fertilizer containing Azospirillum spp. and Azotobacter spp. bacteria). Analysis of variance showed that rice grain yield, panicle number per m2, grain number per panicle, flag leaves area, biological yield, grains N concentration and uptake, grain protein concentration, and head rice yield were significantly affected by N rate, while bio-fertilizer application had significant effect on rice grain yield, grain number per panicle, flag leaves area, biological yield, harvest index, grains N concentration and uptake, and grain protein concentration. Results showed that regardless of bio-fertilizer application, rice grain and biological yields were significantly increased as N application rate increased from 0 to 75 kg ha-1, but did not significantly increase at the higher N rate (150 kg ha-1). Grain yield was significantly increased following bio-fertilizer application when averaged across N rates. Grains N concentration and uptake were significantly increased as N rate increased up to 75 kg ha-1, but further increases in N rate had no significant effect on these traits. Bio-fertilizer application increased significantly grains N concentration and uptake, when averaged across N rates. Regardless of bio-fertilizer application, head rice yield was significantly increased from 56 % to 60 % when N rate increased from 0 to 150 kg ha-1. Therefore, this experiment illustrated that rice grain and head yields increased with increasing N rate, while bio-fertilizer application increased only rice grain yield. Key words: nitrogen fertilizer, plant growth-promoting rhizobacteria, rice yield and yield components VPLIV GNOJENJA Z RAZLIČNIMI ODMERKI DUŠIKOVIH GNOJIL IN BIO-GNOJIL NA PRIDELEK ZRNJA IN MLEVSKE LASTNOST RIŽA Z namenom vrednotenja učinkov gnojenja z različnimi odmerki dušika in uporabe bio-gnojil na pridelek riža in njegove mlevske lastnosti je bil izveden poljski poskus na Rice Research Station of Tonekabon, Iran, v letu 2013. Načrt poskusa je bil faktorski naključni bločni poskus s tremi ponovitvami. Preučevani dejavniki v poskusih so bili tri gnojenja z različnimi odmerki dušika (0, 75, in 150 kg ha-1) in uporaba dveh bio-gnojil (z ali brez inolukacije z bio-gnojilom Nitroxin, tekoče bio-gnojilo, ki vsebuje bakterije iz rodov Azospirillum spp. in Azotobacter spp.). Analiza variance je pokazala, da je imelo gnojenje z dušikom značilen učinek na pridelek zrnja riža, število latov na m2, število zrn na lat, površino najvišjega lista (zastavarja), biološki pridelek, privzem in vsebnost N v zrnju, vsebnost beljakovin v zrnju in pridelek oluščenega riža, uporaba bio-gnojil pa je imela značilen vpliv le na pridelek zrna riža, število zrn na lat, površino najvišjega lista, biološki pridelek, žetveni indeks, privzem in vsebnost N v zrnju in vsebnost beljakovin v zrnju. Rezultati raziskave so pokazali, da sta se pridelek zrnja riža in njegov biološki pridelek povečala ne glede na uporabo bio-gnojil, ko se je gnojenje z dušikom povečalo z 0 na 75 kg ha-1, vendar gnojenje z večjimi odmerki N (150 kg ha-1) ni imelo značilnega vpliva na povečanje teh dveh parametrov. Pridelek zrnja se je značilno povečal pri uporabi bio-gnojil pri vseh odmerkih dušika. Vsebnost in privzem N v zrnje sta se značilno povečala pri povečanju gnojenja z dušikom iz 0 na75 kg ha-1, vendar nadaljna povečanja gnojenja z N niso imela značilnega vpliva na ta parametra. Uporaba bio-gnojil je značilno povečala vsebnost in privzem N v zrnju pri vseh odmerkih dušika. Ne glede na uporabo bio-gnojil, se je pridelek oluščenega riža značilno povečal iz 56 % na 60 %, ko se je gnojenje z N povečalo z 0 na 150 kg ha-1. Izsledki te raziskave kažejo, da se je pridelek zrnja riža in oluščenega riža povečal z večjim gnojenjem z dušikom, uporaba bio-gnojil pa je povečala le pridelek zrnja. Ključne besede: dušikova gnojila, rast stimulirajoče rizobakterije, pridelek riža in njegove komponente Department of Agronomy and Plant Breeding, Rasht Branch, Islamic Azad University, Rasht, firoozi@iaurasht.ac.ir Iran; P.o.Box: 41335-3516; E-mail: 1 INTRODUCTION Rice (Oryza sativa L.) is the staple food crop for about 3 billion world's population. In many countries, rice provides more than 70 % of human caloric intake. In Iran, much of the population consumes rice at least once a day (Kanawapee et al., 2011). Iran's total rice production stands at 2.2 million tonnes per annum, while its annual consumption is about three million tonnes (Rezazadeh et al., 2013). So, Iran has to import about 800 thousand tonnes of rice from some rice producing countries. Consequently, increasing the rice production in the country is an essential. Plant nutrients, which come primarily from chemical fertilizer, are essential for crop production. In agriculture, nitrogen is an essential element for crop growth and development. Nitrogen is a basic constituent of chlorophyll, proteins and all enzymes are involved in photosynthesis, especially Rubisco which alone accounts for more than 75 % of the total leaf nitrogen (Hak et al., 1993). Li et al. (2012) and Manzoor et al. (2006) declared that rice grain yield was significantly increased with increasing nitrogen fertilizer application rate. At the same time, nitrogen has been known as an important factor influencing rice milling quality (Perez et al., 1996). Dilday (1988) reported that the head rice yield decreased 7 to 22 % and 2 to 6 % in 'Lemont' and Newbonnet' rice cultivars, respectively, when no nitrogen applying compared to applying 200 kg N ha-1. Perez et al. (1996) indicated that the head rice yield was significantly increased as N rate increased from 0 to 225 kg ha-1. A lot of studies noted that the nitrogen use efficiency is relatively low in paddy fields. This indicates that a major portion of applied nitrogen is wasted in paddy fields. Nitrogen losses occur through denitrification, volatilization, and leaching which may cause the air and water pollutions (Brown et al., 2012). Therefore, reducing the chemical nitrogen rate by applying the bio-fertilizers may be a solution. Bio-fertilizers are substances which comprise of living microorganisms that stimulate the plant growth by increasing the supply or availability of primary nutrients to the plant and the synthesis of growth-promoting substances. Hence, bio-fertilizers can be expected to reduce the use of chemical fertilizers. Plant growth-promoting rhizobacteria like as Azospirillum and Azotobacter can supply nutrients for crops through nitrogen fixation and produce phytohormones like auxins, cytokinins, gibberellins and ethylene (Keyeo et al., 2011). Therefore, this experiment was conducted to evaluate the effects of nitrogen rate and bio-fertilizer application on rice grain yield, yield components and head rice yield. 2 MATERIALS AND METHODS 2.1 Experimental site, design, and plant growth conditions A field experiment was conducted at Rice Research Station of Tonekabon, Iran, in 2013. The soil texture was loamy with 1.5 % organic matter content, pH 7.7, total N 0.9 g kg-1, available P 5.0 mg kg-1, and available K 140.0 mg kg-1. Three N rates (0, 75, and 150 kg ha-1) and two bio-fertilizer applications (inoculation and uninoculation with Nitroxin, a commercial liquid bio-fertilizer containing Azospirillum spp. and Azotobacter spp. bacteria), organized into a randomized complete block design with a 3 * 2 factorial treatment arrangement and three blocks, were applied to plot area. The colony forming unit (cfu) of Azotobacter and Azospirillum were 109 cells per gram of carrier material. Bio-fertilizer (Nitroxin) was applied at two stages according to the manufacture recommendation, i.e. seed dipping and seedling root dipping methods. Plot size was 3 m by 4 m. Consistent with the lowland paddy field practices in north of Iran, rice seeds ('Tarom') were sown in a nursery seedbed on 18 April and seedlings from these seeds were transplanted on 14 May at a hill spacing of 0.20 by 0.20 m, with three seedlings per hill. Fertilizer N (as urea) was split-applied, with 34 % just before final land preparation, 33 % at panicle initiation, and 33 % at flowering stage. Also, all plots received 100 kg P ha-1 as triple superphosphate and 75 kg K ha-1 as potassium sulfate just before final land preparation. Additionally, all weeds were removed manually whenever necessary. Plots were harvested on 21 August. 2.2 Plant sampling At the soft dough stage, five randomly chosen plants were removed from each plot and the flag leaves area (cm2) was determined with an area meter (Model LI-3100, LI-COR, Lincoln, NE, USA). At maturity stage, rice grain yield (based on 14 % humidity) was determined from 2.5 m2 per plot. Moisture content of grains was measured using a digital grain moisture meter (Model GMK-303R5-Korea) and grain yield per pot was calculated as ((100 - moisture content of the sample) x fresh grain weight)/86 to convert the sample to 14 % moisture content. Yield components, that is, number of panicles per square meter, number of filled grains and 1000-grain weight, were determined from 12 plants (excluding the border ones) sampled randomly from each plot. To determine aboveground biomass, a 1 m2 sample from each plot was randomly chosen, clipped at the ground level, threshed, dried at 70°C for three days, weighed, and expressed as the dry weight of above-ground plant per hectare. Harvest index was the proportion (percentage) of filled grain weight to total above-ground dry biomas. For measuring grain N concentration, rice grains were grounded to pass through a 1-mm sieve. N concentration was determined using micro-Kjeldahl method as described by Pregl (1945) and was expressed as the percent of grain dry weight. N uptake in grain was calculated by multiplying grain dry weight by grain N concentration. Grain protein concentration was calculated as 6.25 x nitrogen content measured by the micro Kjeldahl technique. Paddy samples for milling quality evaluation were harvested from the 2.5 m2 per plot, threshed by a simple motorized thresher and dried up to 8 %, wet basis (w.b.) using the laboratory dryer (Memmart Model 600, Germany) set at 45 °C. Paddy moisture content was determined using the digital grain moisture meter (Model GMK-303R5-Korea). After drying process, 200 g of dried paddy from each treatment were dehulled by a laboratory rubber roll huller (SATAKE Co. Ltd, Japan) and then was milled using a laboratory rice whitener (McGill Miller, USA). Mass of each milled rice sample was weighed by a laboratory scale with an accuracy of 0.01 g, separated into broken and head rice kernels by sizing with a laboratory rotary sieve (SATAKE TRG058, Japan) and then broken and whole kernel fractions were weighed. Head rice yield was determined as the mass of head milled rice after milling, divided by the mass of dried paddy prior to milling process (Zhao and Fitzgerald, 2013). Milling yield was also measured as the mass ratio of total milled rice to the un-hulled dried paddy prior to milling process. 2.3 Data analysis Data were analyzed by analysis of variance (ANOVA) procedure using SAS program (SAS Inst. 2004) and means were compared using Fisher's Protected LSD at the 0.05 level of significance. Pearson correlation coefficients were calculated using correlation analysis to assess the interrelationships between the different measured parameters. 3 RESULTS AND DISCUSSION 3.1 Yield and yield components The main effects of nitrogen rate and bio-fertilizer application were significant, but there was no significant interaction of nitrogen rate and bio-fertilizer application for grain yield (Table 1). Regardless of bio-fertilizer application, rice grain yield was significantly increased from 4251.4±346.5 to 5016.2±349.3 kg ha-1 (18 %) as N application rate increased from 0 to 75 kg ha-1, but did not significantly increase at the higher N rate (150 kg ha-1) (Table 2). Grain yield was significantly increased by bio-fertilizer application when averaged across N rates (Table 2). Pedraza et al. (2009) reported that inoculation of rice plants with Azospirillum significantly increased grain yield. Mukhopadhyay et al. (2013) also reported that the highest grain yield for rice was obtained when bio-fertilizer was applied with 60 % of recommended N rate. Induction of longer roots with increased number of root hairs and root laterals is a growth response attributed to IAA production by Azospirillum and Azotobacter, which increase grain yield in inoculated plants (Keyeo et al., 2011). Panicle number per m2 was significantly affected only by nitrogen rate, while grain number per panicle was significantly influenced by both nitrogen rate and bio-fertilizer application. Regardless of bio-fertilizer application, the highest (323±25.9 panicle) and the lowest (248.2±18.1 panicle) panicle number per m2 was observed in plots receiving 0 and 150 kg N ha-1, respectively (Table 2). Averaged across bio-fertilizer applications, grain number per panicle was significantly increased from 96.4±3.7 to 107.6±4.3 when nitrogen application rate increased from 0 to 150 kg ha-1 (Table 2). These results indicated that nitrogen application increased sink size by increasing both panicle number per m2 and grain number per panicle, while bio-fertilizer inoculation increased sink size only by increasing grain number per panicle. Similarly to these results, Weerakoon et al. (2005) also reported that panicle number per m2 and grain number per panicle increased with increases in N rate. On the other hand, 1000-grain weight was significantly affected neither by nitrogen rate nor by bio-fertilizer application (Table 1 & 2). Contrary to this result, Weerakoon et al. (2005) reported that 1000-grain weight increased with increasing in N rate. Regardless of N rate, grain number per panicle was significantly increased by 11 % when bio-fertilizer was applied. Similar result was reported by others (Mukhopadhyay et al., 2013; Isawa et al., 2010). Bio-fertilizer application increased panicle number per m2 and 1000-grain weight by 17 % and 4 %, respectively, but the increases were not statistically significant. In contrast, Mukhopadhyay et al. (2013) and Isawa et al. (2010) found that panicle number per m2 and 1000-grain weight for rice were significantly increased following bio-fertilizer application. The ANOVA also showed that the interaction between nitrogen rate and bio-fertilizer application were not significant for all of yield components (Table 1). This indicates that all yield components had similar responses to N rate with or without bio-fertilizer application. Rice grain yield was positively correlated with panicle number per m2, grain number per panicle, 1000-grain weight, flag leaves area, biological yield, harvest index, grain N concentration, and grain N uptake at P < 0.01 level (Table 3). Table 1: Mean squares of ANOVA for grain yield (Y), panicle number per m (PN), grain number per panicle (GN), 1000-grain weight (ThGW), flag leaves area (FLA), biological yield (BY), harvest index (HI), grain N concentration (GNC), grain N uptake (GNU), grain protein concentration (GPC), milling yield (MY), and head rice yield (HRY) as affected by nitrogen rate and bio-fertilizer application S.O.V Df Y PN GN ThGW FLA BY HI GNC (%) GNU GPC MY HRY R 2 43778 ns 23.4ns 128* 1.39ns 7647157 ns 589981ns 1.4ns 0.002ns 29 ns 0.01ns 9.6ns 12.1** Nitrogen 2 1885091** 37.4* 191** 11.14ns 54259227** 7098144** 7.2 ns 0.21** 1729** 8.3 ** 1.9ns 19.8 ** (N) Bio- fertilizer 1 5221834 37.9ns 638 3.65 ns 20723922* 17608156 25.6 0.41 4402** 16.1 ** 0.2ns 0.05 ns (B) NxB 2 349822 ns 1.2ns 19 ns 0.02 ns 2085236ns 1007564ns 3.2ns 0.017ns 188 ns 1.1 ns 1.6 ns 0.28ns Error 10 294163 9.4 30 10.60 4583681 886630 4.2 0.02 156 0.8 0.9 1.49 CV (%) - 11 16 5 13 22 7 5 10 15 10 2 2 *, ** represent significance at 0.05 and 0.01probability level, respectively ns represents no significant difference 3.2 Biological yield and harvest index Both nitrogen rate and bio-fertilizer application had significant effects (P < 0.01) on biological yield, while harvest index was significantly influenced only by bio-fertilizer application (Table 1). Moreover, no significant interactions between nitrogen rate and bio-fertilizer application were found for both biological yield and harvest index (Table 1). Regardless of bio-fertilizer application, biological yield increased from 10653.3±648.6 to 12159.1±637.3 kg ha-1 (14.1 %) when N rate increases from 0 to 75 kg ha-1, with no further increase in biological yield as N rate increased from 75 to 150 kg ha-1 (Table 2). Harvest indices were similar for all N rates when averaged across bio-fertilizer applications (Table 2). Thus, the increase in grain yield was due to an increase in total biomass production rather than harvest index. Mukhopadhyay et al. (2013) reported that harvest index increased following bio-fertilizer application. Table 2: Grain yield (Y), panicle number per m (PN), grain number per panicle (GN), 1000-grain weight (ThGW), flag leaves area (FLA), biological yield (BY), harvest index (HI), grain N concentration (GNC), grain N uptake (GNU), grain protein concentration (GPC), milling yield (MY), and head rice yield (HRY) response to nitrogen rate and bio-fertilizer application Y (kg ha-1) PN (No. m2) GN (No. panicle) ThGW (g) FLA (cm2) BY HI (kg ha-1) (%) GNC GNU GPC MY HRY (%) (kg ha-1) (kg ha-1) (g 100g) (%) Nitrogen rates (kg ha-1) 0 4251.4±346.5° 248.2±18.1° 96.4±3.7" 22.7± 1.0° 6216.1± 10653.3± 224.9 6486 39.6±0.9° 1.29±0.1° 55.6±6.9° 8.0±0.4" 69.8±0.6° 56.8±0.7° 75 5016.2±349.3° 306.8±23.7°" 100.3±2.9" 23.5± 0.9° 9937.4± 12159.1± 1132.0° 637.3° 40.9±1.0° 1.59±0.0° 81.6±11.3° 9.9±0.7° 69.9±0.7° 58.5±0.7" 150 5342.8±237.3° 323.0±25.9° 107.6±4.3° 25.4± 1.4° 12168.2± 12753.4± 1239.2° 402.7° 41.8±0.7° 1.63±0.1° 87.5±6.3° 10.2±0.5° 70.8±0.5° 60.5±0.6C LSD (0.05) 697.03 61.9 7.1 4.1 2754.03 1210.7 2.6 0.19 1.2 1.2 Bio-fertilizer application 5409.0±192.6° 315.0±20.5° 107.0±2.8° 24.3±1.0° 10513.2± 12855.9± 1286.8° 345.9° 42.0±0.6° 1.65±0.1° 90.0±7.1° 10.3±0.3° 70.3±0.5° 58.6±0.8° No 4332.3±258.9° 269.3±19.0° 95.0±2.4° 23.4±0.9' application LSD (0.05) 568.8 51.0 6.9± 10878.1± 870.7° 495.0b 3.4 2140.0 989.0 39.6±0.8° 1.35±0.0° 59.0±5.0° 8.4±0.5° 70.1±0.5° 58.9±0.6° 2.1 0.15 1.0 0.9 16.4 1.5 13.4 1.3 3.3 Flag leaves area There were significant effects of nitrogen rate and bio-fertilizer application on flag leaves area, while the interaction effect of nitrogen rate and bio-fertilizer application was not significant (Table 1). Regardless of bio-fertilizer application, flag leaves area was significantly increased from 6216.1±224.9 to 12168.2±1239.2 cm2 when N rate increased from 0 to 150 kg ha-1 (Table 2). Averaged across N rates, flag leaves area was significantly increased following bio-fertilizer application by 25 % (Table 2). Lemaire et al. (2008) declared that N shortage reduced leaf expansion in C3 cereals plants. Insufficient N availability during rice growth stage declined both flag leaf size and number and, therefore, reduced total net photosynthesis (Zong and Shangguan, 2014), which in turn decreased rice grain yield. Besides, Toth et al. (2002) suggested that lower rates of photosynthesis under low N supply are often attributed to reduction in chlorophyll content and Rubisco activity. Flag leaves area was positively correlated with grain and biological yields, yield components height, grain N concentration and uptake, and head rice yield at P < 0.01 level, but not correlated with HI, and milling yield (Table 3). Table 3: Correlation coefficients for measurements of rice as influenced by N rate and bio-fertilizer application Y PN GN ThGW FL BY HI GNC GNU GPC MY PN 0.51" 1 GN 0.55** 0.49* 1 ThGW 0.54*" 0.01ns 0.22ns 1 FL 0.57*" 0.51* 0.60** 0.47™ 1 BY 0.97*" 0.52** 0.58** 0.50* 0.56** 1 HI 0.86** 0.42ns 0.35ns 0.52* 0.44ns 0.73 ** 1 GNC 0.75** 0.65** 0.70 ** 0.42™ 0.65** 0.74** 0.62** 1 GNU 0.92** 0.60** 0.67** 0.52* 0.66** 0.89** 0.78** 0.94** 1 GPC 0.75** 0.65** 0.70 ** 0.42™ 0.65** 0.74** 0.62** 0.99** 0.94 ** 1 MY 0.01™ -0.14™ 0.21ns -0.24ns 0.07ns 0.08ns -0.09ns 0.01ns 0.01ns 0.01ns 1 HRY 0.51* 0.15ns 0.26ns 0.22™ 0.64** 0.42ns 0.29™ 0.69 ** 0.68 ** 0.69 ** 0.54** *, ** represent significance at 0.05 and 0.01probability level, respectively ns represents no significant difference Y, Grain yield; PN, panicle number per m2; GN, grain number per panicle; ThGW, 1000-grain weight; FLA, Flag leaves area; BY, biological yield; HI, harvest index; GNC, grain N concentration; GNU, grain N uptake; MY, milling yield; and HYR, head rice yield 3.4 Grain N concentration, grain N uptake, and grain protein concentration The main effects of nitrogen rate and bio-fertilizer application were significant (P < 0.01) for grain N concentration, grain N uptake, and grain protein concentration, but there were no significant interactions of nitrogen rate x bio-fertilizer application for all of them (Table 1). Regardless of bio-fertilizer application, grain N concentration, grain N uptake, and grain protein concentration had similar responses to N rate. Grain N concentration, grain N uptake, and grain protein concentration were significantly increased as N rate increased up to 75 kg ha-1, but further increases in N rate had no significant effect on these traits (Table 2). Regardless of N rate, grain N concentration, grain N uptake, and grain protein concentration were significantly increased when bio-fertilizer was applied (Table 2). The higher grain N concentration resulting from inoculation may be attributed to increased N uptake by a larger root surface area associated with additional root hairs and lateral root development and/or to biological nitrogen fixation (Biswas et al., 2000). Cong et al. (2009) and Pedraza et al. (2009) also reported that rice grain N uptake was significantly increased with applying bio-fertilizer. 3.5 Milling yield and head rice yield The ANOVA results showed that nitrogen rate and bio-fertilizer application as well as the interaction between them had no significant effects on milling yield (Table 1). Head rice yield was significantly affected by nitrogen rate, while bio-fertilizer application and the interaction between nitrogen rate and bio-fertilizer application were not significant (Table 1). Averaged across bio-fertilizer applications, head rice yield was significantly increased from 56.8±0.7 % to 60.5±0.6 % when N rate increased from 0 to 150 kg ha-1 (Table 2). The positive influence of nitrogen on head rice yield is contributed to this fact that N fertilization increases the packing of protein matrix between endosperm starches in rice grains and grain protein makes it more resistant to cracking and breakage during milling process (Blumenthal et al., 2008). Leesawatwong et al. (2005) also noted that the head rice yield was positively correlated with relative abundance of the storage protein in the lateral section of the endosperm of rice kernels. The positive effect of nitrogen on head rice yield also was reported by Perez et al. 1996, and Dilday (1988). Head rice yield was positively correlated with grain yield, flag leaves area, grain N concentration and uptake, grain protein concentration, and milling yield, but not correlated with yield components, biological yield, and harvest index (Table 3). л J 4 CONCLUSIONS This experiment illustrated that rice grain and head yields increased with increasing N rate, while bio-fertilizer increased only rice grain yield. Regardless of bio-fertilizer application, rice grain yield was significantly increased from 4251.4±346.5 to 5016.2±349.3 kg ha-1 as N application rate increased from 0 to 75 kg ha-1, but did not significantly increase at the higher N rate (150 kg ha-1). Grain yield was significantly increased by bio-fertilizer application when averaged across N rates. Regardless of bio-fertilizer application, head rice yield was significantly increased from 56.8±0.7 % to 60.5±0.6 % when N rate increased from 0 to 150 kg ha-1. 5 ACKNOWLEDGEMENTS The author is grateful for the funding supplied by Rice research institute of Iran for providing the Rasht branch, Islamic Azad University and research facilities. 6 REFERENCES Biswas J.C., Ladha J.K., Dazzo F.B., Yanni Y.G., Rolfe B.G. 2000. Rhizobial inoculation influences seedling vigor and yield of rice. Agron. J. 92: 880886, doi: 10.2134/agronj2000.925880x Blumenthal J.M., Baltensperger D.D., Cassman K.G., Mason C.S., Pavlista A.D. 2008. Importance and effect of nitrogen on crop quality and health. Published in Nitrogen in the Environment: Sources, Problems, and Management, Second edition, edited by J. L. Hatfield and R. F. Follett (Amsterdam: Elsevier, 2008). Copyright © 2008 Elsevier, doi: 10.1016/b978-0-12-374347-3.00003-2 Brown J.R., Blankinship J.C., Niboyet A., van Groenigen K.J., Dijkstra P., LeRoux X. 2012. Effects of multiple global change treatments on soil N2O fluxes. Biogeochemistry 109, 85-100, doi: 10.1007/s10533-011-9655-2 Cong P.T., Dung T.D., Hien T.M., Hien N.T., Choudhury A.T.M.A., Kecskés M.L., Kennedy I.R. 2009. Inoculant plant growth-promoting microorganisms enhance utilisation of urea-N and grain yield of paddy rice in southern Vietnam. Eur. J. Soil Biol. 45, 52-61, doi: 10.1016/j.ejsobi.2008.06.006 Dilday R.H. 1988. Effect of nitrogen fertilizer on milling quality of rice (Oryza Sativa). Proceedings Arkansas Academy of Science. 42:26-27 Hak R., Rinderle-Zimmer U., Lichtenthaler H.K., Natr L. 1993. Chlorophyll a fluorescence signatures of nitrogen deficient barley leaves. Photosynthetica 28: 151-159 Isawa T., Yasuda M., Awazaki H., Minamisawa K., Shinozaki S., Nakashita H. 2010. Azospirillum sp. strain B510 enhances rice growth and yield. Microbes Environ. 1: 58-61, doi: 10.1264/jsme2.ME09174 Kanawapee N., Sanitchon J., Srihaban P., Theerakulpisut P. 2011. Genetic diversity analysis of rice cultivars (Oryza sativa L.) differing in salinity tolerance based on RAPD and S SR markers. Electronic Journal of Biotechnology, 14(6): No. 4, pp: 17 Keyeo F., Ai'shah O.N., Amir H.G. 2011. The effects of nitrogen fixation activity and phytohormone production of diazotroph in promoting growth of rice seedlings. Biotech. 10: 267-273, doi: 10.3923/biotech.2011.267.273 Leesawatwong M., Jamjod S., Kuo J., Dell B., Rerkasem B. 2005. Nitrogen fertilizer increases seed protein and milling quality of rice. Cereal Chemistry 82: 588-593, doi: 10.1094/CC-82-0588 Lemaire G., van Oosterom E., Jeuffroy M.H., Gastal F., Massignam A. 2008. Crop species present different qualitative types of response to N deficiency during their vegetative growth. Field Crops Res. 105, 253265, doi: 10.1016/j.fcr.2007.10.009 Li Y., Chen X., Shamsi I.H., Fang P., Lin Y. 2012. Effects of Irrigation Patterns and Nitrogen Fertilization on Rice Yield and Microbial Community Structure in Paddy Soil. Pedospher, 22 (5): 661-672, doi: 10.1016/S1002-0160(12)60051-4 Manzoor Z., Awan T.H., Zahid M.A., Faiz F.A. 2006. Respons of rice crop (SUPER BASMATI) to different nitrogen levels. J. Anim. Pl. Sci. 16(1-2): 52-55 Mukhopadhyay M., Datta J.K., Garai T.K. 2013. Steps toward alternative farming system in rice. Europ. J. Agronomy 51:18- 24, doi: 10.1016/j.eja.2013.06.005 Pedraza R.O., Bellone C.H., de Bellone S.C., Sorte P.M.F.B., Teixeira K.R.S. 2009. Azospirillum inoculation and nitrogen fertilization effect on grain yield and on the diversity of endophytic bacteria in the phyllosphere of rice rainfed crop. Europ. J. Soil Boil. 45: 36-43, doi: 10.1016/j.ejsobi.2008.09.007 Perez C.M., Juliano B., Liboon S., Alcantara J.M., Cassman K.G. 1996. Effects of late nitrogen fertilizer application on head rice yield, protein content, and grain quality of rice. Cereal Chem. 73 : 556-560 Pregl F. 1945. Quantitative Organic Microanalysis. 4th ed. J.A. Churchill Ltd. London, p.126-129 Rezazadeh T., Aghaiypour Kh., Heidari Z. 2013. The significance of food safety in trade and banning the importation of GMO products into Iran. Croat. J. Food Sci. Technol. (2013) 5 (2) 92-95. SAS 2004. SAS Institute, version 9.1.3. Cary, NC, USA. Toth, V.R., Meszkaros I., Veres S., Nagy J. 2002. Effects of the available nitrogen on the photosynthetic activity and xanthophyll cycle pool of maize in field, J. Plant Physiol. 159: 627-634, doi: 10.1078/0176-1617-0640 Weerakoon W.M.W., Ingram K.T., Moss D.N. 2005. Atmospheric CO2 concentration effects on N partitioning and fertilizer N recovery in field grown rice (Oryza sativa L.). Agric. Ecosyst. Environ. 108: 342-349, doi: 10.1016/j.agee.2004.12.014 Zhao X., Fitzgerald M. 2013. Climate Change: Implications for the Yield of Edible Rice. PLOS ONE, 8(6): e66218. pp:9 Zong Y., Shangguan Z. 2014. Nitrogen deficiency limited the improvement of photosynthesis in maize by elevated CO2 under drought. J. Integ. Agric. 13(1): 73-81, doi: 10.1016/S2095-3119(13)60349-4 COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.08 Agrovoc descriptors: sunflower, Helianthus annuus, plant breeding, genetic control, hybrids, hybridization, lipid content, yields Agris category code: f30 Genetic analysis of agro-morphological traits in promising hybrids of sunflower (Helianthus annuus L.) Maryam GOLABADI*1, Pooran GOLKAR2, Mohammad Reza SHAHSAVARI3 Received July 16, 2015; accepted August 17, 2015. Delo je prispelo 16. julija 2015, sprejeto 17. avgusta 2015. ABSTRACT The main objective underlying sunflower breeding programs is to develop high-yielding productive F1 hybrid cultivars. This study was conducted to investigate the genetic control of some agro-morphological traits of new sunflower F1 hybrids. For this purpose, fourteen inbred lines of sunflower were crossed with three male sterile inbred lines. Their hybrids (14 hybrids) were then evaluated against three control cultivars. The data thus obtained were analyzed using the nested model (North Carolina Design I) as a completely randomized block design (CRBD) with four replications. Analysis of variance showed that the hybrids were significantly different in all the traits studied, except for head and stem diameters. From among the hybrids evaluated, Cms19 x Rn1-81 was found to have the highest seed yield and oil content. Cluster analysis classified the hybrids into four different groups. Genetic analysis showed that days to maturity, seed weight, and oil content (%) were under the additive gene action. Breeding strategies based on selection could be suggested for the improvement of these traits. Head angle, head diameter, seed yield, and oil yield were under the dominance gene action; breeding based on hybridization methods is, therefore, proposed for these traits. Finally, both additive and dominance gene actions were observed to play important roles in the genetic control of plant height and stem diameter. Key words: additive, dominance effect, evaluation of hybrids, oil content, sunflower, yield IZVLEČEK GENETSKA ANALIZA AGRO-MORFOLOŠKIH LASTNOSTI PRI OBETAJOČIH KRIŽANCIH NAVADNE SONČNICE (Helianthus annuus L.) Glavni cilj žlahniteljskih programov navadne sončnice je razvoj visoko produktivnih F1 hibridnih sort. V raziskavi smo preučevali genetsko kontrolo nekaterih agro-morfoloških lastnosti nekaterih novih F1 hibridov navadne sončnice. V ta namen smo opravili križanja 14 inbridiranih linij navadne sončnice s tremi moško sterilnimi inbridiranimi linijami. Dobljeni križanci (14 hibridov) so bili ovrednoteni glede na tri kontrolne sorte. Tako pridobljeni podatki so bili analizirani z vgnezdenim modelom (North Carolina Design I) v bločni zasnovi s štirimi ponovitvami. Analiza variance je pokazala, da so bili križanci značilno različni v vseh preučevanih lastnostih, z izjemo premera koška in premera stebla. Izmed ovrednotenih križancev je imel križanec Cms19 x Rn1-81 največji pridelek semena in največjo vsebnost olja. Klastrska analiza je razvrstila križance v štiri skupine. Genetska analiza je pokazala, da so bile lastnosti, kot so število dni do zrelosti, masa semena in vsebnost olja (%), pod aditivno gensko kontrolo. Za izboljšanje teh lastnosti priporočamo žlahniteljsko strategijo zasnovano na selekciji. Lastnosti kot so naklon koška, premer koška, pridelek semena in pridelek olja so bile dominantno dedovane, zato za te lastnosti priporočamo žlahtnenje na osnovi križanja. Pri lastnostih kot sta višina stebla in njegov primer smo opazili pomembni vlogi tako aditivnega kot dominantnega delovanja genov. Ključne besede: aditivno dominantni učinki genov, vrednotenje križancev, navadna sončnica, pridelek, vsebnost olja 1 Department of Agronomy and Plant Breeding, Collage of Agriculture, Isfahan Branch (Khorasgan), Islamic Azad University, P.O.Box:81595-158, Iran, Corresponding author E-mail: golabadim@gmail.com 2 Institute of Biotechnology and Bioengineering, Isfahan University of Technology, Isfahan, 84156-83111, Iran 3 Isfahan Agriculture and Natural Resources Center, Isfahan, Iran 1 INTRODUCTION Sunflower (Helianthus annuus L.) is widely grown in tropical, semi-arid, and arid regions such as Iran (Weiss, 2000). It is an important oil crop of high quality oil, good adaptation, and high seed yield (Razi and Asad, 1999; Hu et al., 2010). Sunflower oil contains approximately 12 % saturated fat and 64 % linoleic acid (an omega-6 essential fatty acid) (Weiss, 2000). The genotypes possessing self-incompatibility and cytoplasmic male sterility (CMS) offer the potential for hybrid production (Fick, 1987). Currently, the highest levels of sunflower cultivars belong to hybrid varieties grown in developed countries. The production of hybrid varieties of sunflower in Iran is accomplished by using CMS and restoring fertility (RF) lines. Hybrids of sunflower are more stable and highly self-fertile with a high yield performance and greater uniformity at maturity (Kaya and Atakisi, 2004). In some cases, the hybrid genotypes have been found to be superior in terms of seed yield to their parental lines. Shahsavari et al. (2010) observed significant differences in days to maturity, plant height, stem diameter, head diameter, seed weight, seed yield, and oil yield among twenty genotypes of sunflower including new hybrids and parental genotypes. Haq et al. (2006) also reported significant differences among sunflower hybrids with respect to their plant height, stem diameter, oil percentage, seed yield, and seed weight. Similarly, Razi and Assad (1999) reported significant differences in growth period, head diameter, seed weight, as well as oil and seed yields among the different genotypes of sunflower they studied. The creation of new sunflower hybrids with a high genetic potential for seed yield requires information about their mode of inheritance. Various genetic mating designs have been used to generate improved plants. All such designs are meant to realize the following four main objectives: 1) to obtain information about the genetic control of the traits under study, 2) to generate a breeding population for use as a basis in the selection and development of potential varieties, 3) to provide estimates of genetic gain, and 4) to gain information about the parents used in the breeding programs (Acquaah, 2012). North Carolina Designs (I, II, and Ill) were developed by Comstock and Robinson (1948). Design I (NcDI) is commonly used for estimating the additive and dominance variances (Acquaah, 2012). The main advantage of this design is its ability to supply a test of significance for the additive genetic variance (Hill et al., 1998). The design has also been successfully used in obtaining estimates of genetic variance in sunflower. Knowledge of genetic factors helps researchers select appropriate breeding methods. The genetic components and heritability of seed yield and its components in sunflower hybrids have been identified by different genetic designs such as NCD-II (Alza et al., 1997) and line x tester (Ghaffari et al., 2011). The present study was designed to evaluate both the mean performance of some new Fi hybrids and the genetic control of such traits as stem diameter, head angle, and days to maturity in sunflower via the NCD-I genetic design. 2 MATERIALS AND METHODS This research was conducted at the experimental research farm of Agricultural Research Institute of Isfahan, at Kabutar Abad region (51° 51' longitude and 32° 31 latitude) in 2012-2013. The North Carolina Design I was used to prepare a new genetic population of sunflower hybrids with improved traits. Three lines of cytoplasmic male sterility (CMS14, CMS19 and CMS 522), as the female parents, and 14 new restorer inbred lines (Rn1-144, Rn1-56, Rn-14, Rn-1-128, Rn1-152, Rn1-60, Rn-864, Rn-1-76, Rn-1-130, Rn1-149, Rn1-4, Rn1-81, Rn4 and Rn-1-77), as the male parents, were separately planted in one row 4 m long in a small crossing plot at two different planting dates in 2012. The CMS and restore lines were prepared by oil seed research branch of Agricultural Research Center of Isfahan, Iran. A distance of 60 cm was left between the rows. Some plants in every line were covered with sheer before flowering time. For hand pollination, liberal amounts of pollen were applied on three plants of every male sterile on every second day of the flowering period for a total number of three times. The seeds of 14 Fi hybrids with three control genotypes ('Azargol', 'Allstar', and 'Haysan-33') were evaluated in a completely randomized block design (CRBD) with four replications in 2013. Each experimental plot consisted of four lines in row of 5.5 m long each. The distances between and within the rows were set to 60 cm and 25 cm, respectively. The standard agronomic package of practices and suitable plant protection were adopted to raise healthy crops. Ten randomly selected plants were taken from the two middle rows of each experimental plot for evaluating their traits. in promising hybrids of sunflower (Helianthus annuus L.) 2.1 Traits studied Seed and oil yields of each plot were calculated (kg/ha) after elimination of two margin lines. Seed oil (%) was determined using the seeds collected from ten random plants per plot by the NMR (Nuclear Magnetic Resonance, H20-18-25A) method. Plant height (cm) was measured as the distance between soil surface and stem attachment to the head. Head angle was defined as the receptacle orientation expressed at maturity as an angle in degrees. Analysis of variance was carried out using the SAS 9.1 software. Mean comparison was accomplished by the Least Significant Difference (LSD) test at a probability of 5% and cluster analysis was conducted using the Ward method with the SPSS software. Finally, the genetic population was subjected to genetic analysis using the SAS software. The variance components of NC-I are reported in Table 1. Table 1: Analysis of variance and its components in North Carolina Design (I) Source of Variation D.F Mean squares Expected Mean Squares Related covariance Replication r-1 Female f-1 M3 c2+r c2f/m+rm c2f c2+r (Cov F.S - Cov H.S)+ rm CovH.S)( Female (male) f(m-1) M2 c2+r C2f/m c2+r (Cov F.S - Cov H.S) Error mf-1) (r-1) M1 C2 g2 r, f, and m denote replication, female, and male, respectively According to Table 1, dominance variance ( the following Relation (Kempthorne, 1957): According to Table 1, dominance variance (с2d ) and additive variance (с2a ) would be calculated (as F=1) using 1 + F 2 1 + F 2 2 1 + F 2 Cov (F.S) = [(—2—)c a + (—2—) с d] and Cov (H.S) =(-^)c2a Broad-sense and narrow-sense heritability of the studied traits (Mahmud and Keramer, 1951) and degree of dominance (Kearsey and Pooni, 1996) were obtained using the following Relation: Hb = 2 2 с A + с D Hn = d = j 252 d/52 a 2 CT A 2 2 2 с 2 + с 2 + с с 2 +с2 +с2 A D A D а 3 RESULTS AND DISCUSSION Analysis of variance showed significant differences among the entries for all the studied traits (Table 2). Moreover, female and female (male) mean squares were significant for all the traits (Table 2). This indicates the existence of high variations among the parental genotypes. The control genotypes showed significant differences in all the traits studied, except for seed diameter and oil content. Comparison of F1 hybrids vs. controls showed significant differences between the means of F1 hybrids and the control genotypes (Table 2). Previous studies have also reported significant differences in growth period, plant height, seed weight, oil yield, and seed yield on F1 hybrids of sunflower (Razi and Assad, 1999; Haq et al., 2006; Arshad et al., 2007). Table 2: Analysis of variance and genetic components for agronomic traits in 14 promising F1 hybrids and 3 control lines of sunflower with NCD-1 Mean squares S.O.V D.F DM PH HA HD SD SW SY OY OC Rep. 3 8.46 690.33** 1421.6** 7.238 6.94** 154.74** 800496* 96358** 1.77 Entries 16 89.1** 915.5** 1203.2** 7.87* 3.8** 345.6** 1855859.9** 341647** 14.5** Female 2 388.9** 776.35** 2059.6* 14.19** 7.4** 659.67** 1255622** 203312** 45.2** Female (Male) Control 11 2 40.8** 76.58** 160.2** 1982.33** 653.27** 3543.7** 5.72* 14.33** 1.5* 0.02 90.3** 1195.88** 344780* 7284571.5 80274* 1411360** 9.5** 2.46 Control vs. Fi Residual 1 48 45.81** 5.31 7368.43** 72.6 842.21 269.62 5.95 2.8 29.45** 0.58 969.18** 24.31 8820790.9 105113 1353993** 38774 31.5** 2.1 Genetic estimates а2 л 12.43 21.22 50.23 0.30 0.21 20.33 32530 4394.2 1.38 a2 d 2 10.9 70.79 0.57 0.12 6.33 43651.7 8177.8 0.38 d 0.56 0.99 1.67 1.95 1.08 0.78 1.63 1.92 0.74 h2b h2n 91.57 78.86 64.44 43.10 64.22 26.65 60.57 31.28 69.81 43.86 81.43 62.10 75.34 31.74 56.46 19.1 77.10 60.43 **, *: Significant at 1% and 5%, respectively; ns: not significant Abbreviations: DM: days to maturity, PH: Plant height, HA: Head angle, HD: Head diameter, SD: Stem diameter, SW: Seed weight, SY: Seed yield, OY: Oil yield, OC: Oil content. d =average of dominance, h2 b= broad-sense heritability, h2n: Narrow-sense heritability 3.1 Genetic components analysis The genetic components of the studied traits were calculated and reported in Table 2. The variance of female (o2f) (CMS lines) and female (male) (o2f/m) (restorer fertility lines) were significant for all the studied traits, implying the important effects of both additive and dominance gene actions on the genetic control of the traits investigated. The variance among the CMS lines (female) for all the traits were greater than that among the male lines (restorer), indicating the possible existence of some degree of maternal effects for the genetic control of the studied traits (Ghaffari et al., 2011). Alza et al. (1997) reported that female variance was significant for seed weight and oil content. 3.2 Days to maturity According to Table 2, a2a (12.43) is larger than a2d (2) for days to maturity (Table 2). Comparison of the variance components, the value of dominance ratio (0.56), and the high narrowsense heritability (78.86) indicate the importance of the additive gene action for the genetic control of days to maturity. In agreement with our findings, Saeidi et al. (2009) reported that additive genetic effects had a greater contribution to the genetic control of days to maturity than did the non-additive ones. Wehner (1984) reported that dominance variance was greater than additive variance for days to germination as a phenological trait. Ghaffari et al. (2011) reported both additive and dominance gene actions to be effective in the genetic control of days to maturity. 3.3 Plant height A major objective in sunflower breeding programs is to improve crops by reducing plant height. Genetic analysis in the present case showed that the value of a2a (22) was larger than that of a2d (10.9) for plant height (Table 2). Similar to the findings of Gaffari et al. (2011) and Ortegon et al. (1992), the dominance ratio (d=1) in the present study implied the importance of both additive and dominance gene actions in the genetic control of plant height. Also, Miller and Hammond (1991) reported that additive gene action played a more important role than the dominance one did. 3.4 Head angle and head diameter Dominance variance (a2d ) was found to be greater than a2a for head angle and head diameter (Table 2). This indicates the predominant roles of the dominance over the additive gene action in the genetic control of these traits. Gangappa et al. (1997) reported that non-additive gene action was predominant for the genetic control of head diameter, which is in agreement with our results. Contrary to our results, however, Ghaffari et al. (2011) reported additive ones to be important for the genetic control of head diameter. To the best of our knowledge, no study has been reported on the genetic control of head angle in sunflower. 3.5 Stem diameter Increasing stem diameter is another major objective in sunflower breeding programs. Analysis of genetic components showed that a2 a (0.21) was greater than a2d (0.12) for stem diameter (Table 2). Comparison of variance components, dominance ratio (1.08), and medium narrow-sense heritability (43.86) implied the importance of both additive and dominance gene actions in the genetic control of stem diameter. These results confirm those reported by Miller and Hammond (1991). 3.6 Seed weight According to Table 2, a2a (20.33) was greater than a2d (6.33) for seed weight (Table 2). The dominance ratio (0.78) and the high narrow-sense heritability (62.10) obtained in this study showed the predominant role of the additive over the dominance gene action in the genetic control of seed weight. This is in agreement with the findings of Ghaffari et al. (2011). However, Bajaj et al. (1997) reported the dominance gene action to be important for the genetic control of seed weight, which is not in agreement with our results. The differences between the results could be explained by differences in the genotypes used and the environmental effects in each study. 3.7 Seed and oil yield The magnitude of a2d (as compared to a2a ), the dominance ratio, and the low value of narrowsense heritability obtained in this study indicate the importance of the dominance gene action for the genetic control of the plant traits investigated (Table 2). The importance of dominance gene action for seed yield has also been reported elsewhere (Khani et al., 2005; Skoric et al., 2000; Ghaffari et al., 2011). Gomez et al. (1999) reported that line and line x tester mean squares were not significant for seed yield in sunflower. In agreement with our results, however, other studies performing line x tester analysis in sunflower have indicated that oil yield is governed by the nonadditive gene action (Kadkol et al., 1984; Ghaffari et al., 2011). 3.8 Oil content (%) Genetic analysis showed that a2a (1.38) was greater than a2d (0.38) (Table 2). The high values obtained for the narrow-sense heritability (60.43) and dominance ratio (0.74) indicate the importance of the additive gene action for the control of oil content. In agreement with our results, Saeidi et al. (2009) reported that additive gene action was more important than the non-additive effects for the genetic control of seed oil content. Contrary to our results, Andarkhor et al. (2013) reported the significant role of dominance gene action for the genetic control of oil yield. 3.9 Heritability of traits Broad-sense heritability varied between 91.57 (days to maturity) and 56.46 (oil yield) (Table 2). This is while narrow-sense heritability varied between 78.88 (days to maturity) and 19.1 (oil yield) (Table 2). The low-medium values obtained for the narrow-sense heritability demonstrated the low contribution of the additive genetic variance to the total genotypic variance (Kearsey and Pooni, 1996). 3.10 Mean comparison of Fi hybrids and controls The mean comparison of the studied traits is presented in Table 3. Earliness is an important trait in most regions of sunflower cultivation in Iran, where sunflower is grown as the second crop following the last irrigation of a main crop or in rotation with cereal crops. Early maturing hybrids are, therefore, appropriate for cultivation in these areas. Also, early maturity enables sunflower genotypes to avoid environmental stresses, especially biotic (diseases and insects) or abiotic stresses (heat and drought) at the ripening stage. In this study, days to maturity was found to range between 93 (Cms14xRn1-56) and 106.5 (Cms19xRn1-77) days (Table 3). Depending on the specific genotype used and the environmental conditions, different ranges have been reported for days to maturity in sunflower hybrids (Razi and Assad, 1999; Ghaffari, 2003). In the present study, the Cms14xRn1-144, Cms14xRn1-56, Cms522/2xRn14, Cms522/2xRn864, and Cms19xRn1-76 hybrids showed a shorter growth period than did the 'Allstar' hybrid (as the earliest hybrid in Iran) (Table 3). These promising hybrids could, therefore, be applied in breeding programs aimed at producing early maturity genotypes of sunflower. Plant height was found to range from 107 (Cms19xRn1-77) to 156.3 cm (Hysun-33) in the hybrids (Table 3). Plant height was shorter in all the test hybrids than in the two control ('Haysan-33' and 'Azargol') ones. It may, therefore, be concluded that the hybrids investigated in this study exhibited reduced plant heights as compared to the control genotypes. Razi and Assad (1999) reported that plant height in their study ranged between 124.3 and 222.9 (cm) in sunflower. Head diameter in the present study ranged between 19.9 cm in Cms19xRn1-149 and 15.9cm in Cms14xRn1-56 (Table 3). Based on these results, the hybrids were found superior to the control with respect to head diameter. Stem diameter ranged between 19.6 mm in Cms19xRn1-60 to 15.9 mm in Cms19xRn1-76 (Table 3). These results indicate a high variability in the hybrids with respect to stem diameter. Regarding seed weight, the values were observed to range between 75.9 ('Azargol') and 42.6 (Cms522/2xRn864) (g) (Table 3). Finally, seed yield recorded the highest values in 'Azargol', 'Haysan-33', and 'Allstar' as compared to the other hybrids (Table 3). The highest seed yield (4104.17 Kg/ha) was recorded for Cms19xRn1-81 (Table 3). However, no other significant differences, were observed between this hybrid and the control genotypes (Table 3). This finding is in agreement with those of Haq et al. (2006), Razi and Assad (1999), Ghaffari (2003), and Arshad et al. (2007). Generally speaking, the hybrid derived from the Cms-19xRn1-81 cross was found to be the best for seed yield among the hybrids investigated in this study. Improvement of seed yield and oil content forms a major goal in hybrid production programs. Oil yield is an important sunflower trait which justifies the economical production of specific hybrids since the oil from properly selected and modified genotypes offers a good potential for improving food products while it also has many industrial applications (Seiler, 2007). However, it is not easy to improve these traits due to the low heritability and high sensitivity of the plant to genotypic interactions with the environment (Marinkovic, 1992). The experiments in this study showed that oil yield ranged between 44.7% (Cms19xRn1-81) and 39.9% (Cms19xRn1-76) (Table 3). The hybrids of Cms522/2xRn1-4 and Cms19xRn1-81 showed to be superior with respect to seed and oil yields (Table 3). Cms19xRn1-77 was found to be the unsatisfactory hybrid in this study as it recorded the lowest seed and oil yields and the longest growth period. Some hybrids showed early maturity compared to 'Allstar' which is known as an early maturity genotype. Cluster analysis, as a multivariate analysis, is widely used to describe genetic diversity based on similarities or differences among genotypes (Peeters and Martinelli, 1989). The genotypes investigated in this study were subjected to cluster analysis using the Ward method which yielded a classification of genotypes into four distinct groups (Figure 1), with 6 hybrids assigned to group 1, 6 to group 2, 4 to group 3, and 1 to group 4. The mean comparison of different traits is presented in Table 4. Significant differences were observed among the groups in all the traits studied, except for stem diameter (Table 4). The differences in days to maturity, plant height, head angle, and head diameter observed among the groups were highly significant (Table 4). The second group exhibited the highest values of seed yield, oil yield, seed weight, and plant height. The two control hybrids ('Azargol' and 'Haysan-33') were in this group as well. Based on the mean values obtained for all the traits in the hybrids investigated, the hybrids Cms19xRn1-130, Cms19xRn1-149, and Cms19xRn1-81 along with the control 'Azargol' and 'Haysan-33' were found to have the best seed yields. Thus, these hybrids could be recommended for further evaluation from a seed yield improvement viewpoint. The third group was identified as the earliest maturity group. It also exhibited acceptable seed and oil yields. The genotypes in this group could be recommended for cases of limited planting season. The hybrid Cms19xRn1-77, in group 4, recorded the highest number of days to maturity among the four groups evaluated and ranked the lowest with respect to plant height, head angle, seed weight, and seed yield (Table 4). The highest value for head diameter belonged to this hybrid as well. The hybrids from common parents (i.e., Cms 522/2 and Cms 14) were classified in the same groups, indicating identical effects of parents on the progeny and probably the existence of strong maternal effects in the parents. In contrast, those from the parent Cms-19 were placed in different groups, indicating less of similar parental effects on the progeny. Generally speaking, the hybrids Cms-19xRn1-81, Cms19xRn1-130, and Cms19xRn1-149 had the best conditions for seed and oil yields. On the other hand, Cms14xRn1-56, Cms14xRn1-144, and Cms19xRn1-76 with suitable seed and oil yields were identified with earliness in growth period. Therefore, depending on the regional conditions, it seems better when selecting the best hybrids to make a tradeoff between yield and growth period. Alba et al. (2010) used cluster analysis for categorizing 11 sunflower hybrids based on 8 agronomic characters including oil yield with different sowing dates. The hybrids were classified by cluster analysis with respect to their performance into groups that could be differenced by means and stability. Table 3: Mean comparison of different studied traits in promising hybrids and control genotypes of sunflower Code Genotype DM PH (cm) HA HD (cm) SD (mm) SW (g) SY (Kg ha-1) OY (Kg ha-1) Oc(%) 1 Cms14xRn1-144 93.5 122 10.7 17.5 18.2 72.8 3166 1269.5 40.7 2 Cms14xRn1-56 93 112.7 26.5 15.9 17.9 53.9 3552 1454.7 40.9 3 Cms522/2xRn14 94 137 44 17.5 18.4 52.6 3447 1493.6 43.4 4 Cms522/2xRn1-4 1 02.2 122 39.2 16.5 18.1 45.4 3437 1538.5 44.7 5 Cms522/2xRn864 93.7 129.25 44.5 16.5 17.7 42. 6 3044.5 1353.6 44. 5 6 Cms522/2xRn4 97.7 138.5 53 16.5 17.7 44.6 3666.6 1530.2 41.7 7 Cms19xRn1-28 100.7 149.25 54.7 18.1 16.6 59 3116.6 1326.8 42.6 8 Cms19xRn1-52 101.2 147.25 48 16.7 19.1 61.7 3839.5 1684.6 43.9 9 Cms19xRn1-60 97.2 132.75 42.2 17.6 19.6 56.8 3668.7 1565.8 42.9 10 Cms19xRn1-76 96.2 114.25 12 17.6 15.9 58. 8 3229.1 1292.4 39.9 11 Cms19xRn1-130 103.5 149.75 50 17.5 16.3 62.2 3858. 3 1666.4 43.4 12 Cms19xRn1-49 104 136 34 19.9 17.2 64.1 3924.9 1620.9 41.3 13 Cms19xRn1-81 100.2 138.5 46.7 19.2 17.4 59.8 4104 1821.6 44.3 14 Cms19xRn1-77 106.5 107 8 20 17.6 47.5 2287.4 944.4 41.6 15 Allstar 96.7 115.5 20.2 17 18.1 65.9 4358.3 1815.9 41.6 16 Hysun-33 104.7 156.25 42 20 19.2 61.2 4985.4 2035.1 40.8 17 Azargol 102.2 150 57.5 19.5 17.7 75.9 4986. 2 2132.3 42.9 LSD (P=0.05) 3.19 11.8 22.7 2.31 1.05 6.83 449.3 272.9 2.08 Abbreviations: DM: days to maturity, PH: Plant height, HA: Head angle, HD: Head diameter, SD: Stem diameter, SW: Seed weight, SY: Seed yield, OY: Oil yield, OC: Oil content. C=u522/2'3flH CtalS'Bnl-« Qul9*ftDl-152 C3i522/2'Snì*4 йиаг/2*ш-4 Сшэ522/2ЧЫ См1Э*Йп1-128 Cu:9*R.il-13fl ÜolS'Rßl-Ш Саз19*ВпШ Вуят-33 (che eie] niargol (check] Сад:4*В.И-56 Allna: (ditele) Ctal4*Riil-l44 CMlS4Rnl-7fi CelJ'Rol-77 Figure 1: Cluster dendrogram of 17 sunflower genotypes based on Euclidean rescaled distances The biplots, therefore, provide more useful information for sunflower breeders and PCA can be performed based on agronomic traits data for the determination of real hybrid performances. Agronomic traits with favorable values of principal components were effectively used to discriminate entries for multivariate selection. Acute angle for seed yield and oil yield indicated a positive relationship between these traits (Figure 2). Seed weight, days to maturity, and head diameter were also closely associated (Figure 2). The associated traits can be, therefore, used for the selection of one of these traits, and this would provide the opportunity to implement a multi-trait selection process in sunflower breeding programs. Oil content was found not to be associated with seed yield or oil yield; rather, oil content exhibited strongly negative associations with oil yield and seed yield because of the obtuse angle of their vectors. Therefore, biplots provide more useful information in this case for sunflower breeders and PCA can be performed based on agronomic traits to determine the real performance of the hybrids. According to Figure 2, Cms19*Rn1-52, Cms19xRn1-130, and Cms19xRn1-81 hybrids were the superior ones with respect to plant height, oil content, and stem diameter. The hybrids Cms19xRn1-76 and Cms19xRn1-77 showed the least PC values, demonstrating the low breeding value of these hybrids for seed and oil improvement. Figure 2: Biplots for the 1st and 2nd principal components used for mean agronomic traits in sunflower Abbreviations: DM: days to maturity, PH: Plant height, HA: Head angle, HD: Head diameter, SD: Stem diameter, SW: Seed weight, SY: Seed yield, OY: Oil yield, OC: Oil content; Table 4: Means comparison of groups from cluster analysis based of LSD test for sunflower hybrids Trait¥ Mean squares Means of groups Group 1 Group 2 Group 3 Group 4 DM 0.33** 97.71bc 102.58ab 94.875c 106.5a PH (cm) 605.63** 134.46a 146.62a 116.12b 107b HA 1392.13** 45.17a 48.62a 17.37b 8b HD (cm) 3.13** 16.89b 19.04a 17b 20a SD (mm) 2.34ns 18.43a 17.4a 17.49a 17.6a SW (g) 422.45* 50.62ab 63.69a 62.86a 47.55b SY (kg/ha) 18831.78* 3517.43a 4162.63a 3576.56a 2287.47b OY (Kg/ha) 5502* 1527.7a 1767.18a 1458.14a 944.37b OC (%) 16.05* 43.53a 42.54ab 40.77b 41.36ab **, *: significant at 1% and 5%, respectively. ¥: Abbreviations: DM: days to maturity, PH: Plant height, HA: Head angle, HD: Head diameter, SD: Stem diameter, SW: Seed weight, SY: Seed yield, OY: Oil yield, OC: Oil content. Means followed by the same letter in each row are not significantly different at P = 0.05. 4 CONCLUSION This paper exploited the North Carolina Design 1 analysis to investigate the genetic implications regarding seed yield, oil yield, and certain agronomic traits in different new F1 hybrids of sunflower. Cluster analysis revealed significant differences among all the study groups for all the traits investigated, except for head diameter. The second group with six hybrids showed the highest values for grain yield, yield components, and oil yield. Therefore, the hybrids in this group may be recommended for application in breeding programs. Moreover, the predominance of additive gene action in explaining genetic variations observed in days to maturity, seed weight, and oil content (%) supports the statement that genetic improvement may be suggested through accumulation of favorable alleles from parents and using such proper methods as recurrent selection. The predominance of the dominance gene action in explaining the genetic variation observed in head angle, head diameter, seed oil, and seed yield supports the claim that hybridization breeding methods are required to improve these traits. The importance of both additive and dominance gene actions for the genetic control of plant height and stem diameter supports breeding methods based on both selection and hybridization for improving these traits. 5 REFERENCES Acquaah G. 2012. Principles of plant genetics and breeding. 2nd ed. Wiley-Blackwell, Oxford, doi: 10.1002/9781118313718 Alba V., Polignano G.B., Montemurro C., Sabetta W., Bisignano V., Turi M., Ravaglia S., Troccoli A., Colecchia S. A., Alba E., Blanco E. A. 2010. Similarity Patterns and Stability of Environmental Response in sunflower Hybrids. International Journal of Agronomy. 2010:1-9, doi: 10.1155/2010/637928 Alza J. O., Fernandez-Martinez J. M. 1997. Genetic analysis of yield and related traits in sunflower (Helianthus annuus L.) in dry land and irrigated environments. Euphytica, 95(2): 243-251, doi: 10.1023/A:1003056500991 Andarkhor S.A., Rameeh V., Alitabar R. A. 2013. Estimation of genetic parameters for yield components and seed yield in sunflower using line X tester analysis. African Journal of Biotechnology, 12(25): 3978-3983 Arshad M., Kashif -Ilyas M., Ayub Khan M. 2007. Genetic divergence and path coefficient analysis for seed yield traits in sunflower (Helianthus annuus L.) hybrids. Pakistan Journal of Botany, 39(6): 2009-2015. Bajaj R. K., Aujla K. K., Chahal G.S. 1997. Combining ability studies in sunflower. (Helianthus annuus L.). Crop Improvement, 34: 141-146. Comstock, R.E., Robinson H.E. 1948. The components of genetic variance populations. Biometrics 4: 254266, doi: 10.2307/3001412 Fick G.N. 1987. Sunflower. Pp 544-585. In: Rabbelen, G., Doweny, R.K. and Ashri, A.D.(eds). Oil crops of the World. McGrow Hill, U.S.A. Gangappa E., Channakishnaiah K. M., Harini M. S., Ramesh S. 1997. Studies on combining ability in sunflower. Helia, 20(27):73-84 Ghaffari, M. 2003. Use of principle component analysis method for selection of superior three way cross hybrids in sunflower. Seed and Plant Improvement Journal, 19(4): 513-527 Ghaffari M., Farrokhi I., Mirzapour M. 2011. Combining ability and gene action for agronomic traits and oil content in sunflower (Helianthus annuus L.) using F1 hybrids. Crop breeding Journal, 1(1): 73- 84 Gomez S. D., Bladini M., Charles D.A., Vannozzi G. P. 1999. Genetic variances and heritability of sunflower traits associated with drought tolerance. Helia, 22: 23 - 34 Haq A., Rashid A., Butt M. A., Akhter M. A., Aslam M. and Saeed A. 2006. Evaluation of sunflower (Helianthus annuus L.) hybrids for yield and yield components in central Punjab. Journal of Agricultural Research, 44(4): 277-284 Hill J., Becker H.C., Tigerstedt P. M. A. 1998. Quantitative and ecological aspects of plant breeding. Chapman and Hall, UK, London. P.275, doi: 10.1007/978-94-011-5830-5 Hu J., Seiler G., Kole C. 2010. Genetics, genomics and breeding of sunflower. CRC Press, doi: 10.1201/b10192 Kadkol G. P., Anand, J. J., Sharma, R. P. 1984. Combining ability and heterosis in sunflower. Indian Journal of Genetics and Plant Breeding, 44(3): 447-451 Kaya Y., Atakisi, I.K. 2004. Combining ability analysis of some yield characters of sunflower (Helianthus annuus L.). Helia, 27(41):75-84, doi: 10.2298/HEL0441075Y Kearsey M. J., Pooni, H. S. 1996. The Genetical Analysis of Quantitative Traits. Chapman and Hall, London, doi: 10.1007/978-1-4899-4441-2 Kempthorne O. 1957. An introduction to genetic statistics. John Willey and Sons, Inc. New York. Khani M., Daneshian J., Zeinali Khaneghah H. and Ghannadha, M.R. 2005. Genetic analysis of yield and its components using line xtester cross design in sunflower inbred lines under the stress and nonstress drought conditions. Iranian Journal of Agricultural Science, 36 (2): 435-445 Mahmud I., Keramer H.H. 1951. Segregation for yield, height and maturity, following a soybean crosses. Agronomy Journal. 43: 605- 609, doi: 10.2134/agronj1951.00021962004300120005x Marinkovic R. 1992. Path-coefficient analysis of some yield components of sunflower (Helianthus annuus L.). Euphytica, 60: 201-205 Miller J. F., Hammond J. J. 1991. Inheritance of reduced height in sunflower. Euphytica 53: 131136, doi: 10.1007/BF00023793 Ortegon M., Escabedo A. A., Villarreal L. Q. 1992. Combining ability of sunflower lines and comparisons among Parent lines and hybrids. Proc. 13th Int. Sunflower Conf. (Pisa - Italy). PP: 1178 Peeters J. P., Martinelli, J. A. 1989. Hierarchical clustering analysis as a tool to manage variation in germplasm collection. Theoretical and Applied Genetics, 78: 42-48, doi: 10.1007/BF00299751 Razi H., Assad, M.T. 1999. Comparison of selection criteria in normal and limited irrigation in sunflower. Euphytica, 105: 83-90, doi: 10.1023/A:1003472212917 Saeidi G. H. A., Rezaei. A. M., Abbasi A., Farokhi, E. 2009. General and specific combining ability for agronomic and seed quality traits in some inbred lines of sunflower. Iranian Journal of Field Crop Science, 40 (2): 105 - 113 Seiler G. J. 2007. Wild annual Helianthus anomalus and H. deserticola for improving oil content and quality in sunflower. Industrial Crops and Products, 22(1): 95-100, doi: 10.1016/j.indcrop.2006.07.007 Shahsavari, M. R., Nikobin, M. and Karimi, M. 2010. Final evaluation of new hybrids of sunflowers. First National Symposium of Oil Grain Plants, Isfahan University of Technology, Isfahan, Iran. Skoric D., Jocic S., Molnar I. 2000. General (GCA) and specific (SCA) combining abilities in sunflower. Proc. 15th Int. Sunflower Conference. Toulose France, PP: E23 - E27 Wehner T.C. 1984. Estimates of heritabilities and variance components for low temperature germination ability in cucumber. Journal of the American Society for Horticultural Science, 109: 664-667 Weiss E. A. 2000. Oil seed Crops. 2nd ed. Blackwell Science, Oxford. P.364 COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.09 Agrovoc descriptors: Plant extracts, Artemisia, Eucalyptus camaldulensis, Rosmarinus officinalis,plantprotection, insecticides, botanical insecticides, insecticidal properties, Myzus persicae, integrated control Agris category code: h01, h10 Insecticidal activity of three plants extracts against Myzus persicae (Sulzer, 1776) and their phytochemical screening Billal NIA1, Naama FRAH2 and Imane AZOUI3 Received July 29, 2015; accepted August 20, 2015. Delo je prispelo 29. julija 2015, sprejeto 20. avgusta 2015. ABSTRACT IZVLEČEK To reduce the use of synthetic pesticides and their negative effects on the environment, leaves extracts of Artemisia herba-alba Asso, Eucalyptus camaldulensis Dehnh and Rosmarinus officinalis L. were obtained with petroleum ether, ethanol and distilled water as solvents. These extracts were evaluated under laboratory conditions for their insecticidal effect against 3 to 4 days-old Myzus persicae individuals (Homoptera: Aphididae) at 1, 2.5, 5, and 10 %. We made observations after 24 hours. Etheric extract of all plants was effective and caused mortalities (100 %, 53 % and 60 % respectively) at the highest concentration. However, ethanolic and aqueous extracts did not show any significant insecticidal effect. The phytochemical screening showed the richness of etheric extract in terpenes. The results obtained suggest that we can make bioinsecticides based on leaves etheric extracts from these plants for use in integrated pest management. Key words: Artemisia herba-alba, botanical insecticides, Myzus persicae, Eucalyptus camaldulensis, Rosmarinus officinalis INSEKTICIDNO DELOVANJE IZVLEČKOV TREH RASTLIN NA LISTNO UŠ Myzus persicae (Sulzer, 1776) IN NJIHOVA FITOKEMICNA ANALIZA Z namenom zmanjševanja negativnih učinkov sintetičnih pesticidov na okolje so bili narejeni izvlečki listov s petroletrom, etanolom in distilirano vodo iz naslednjih treh rastlin Artemisia herba-alba Asso, Eucalyptus camaldulensis Dehnh. in Rosmarinus officinalis L.. Insekticidni učinki teh izvlečkov so bili ovrednoteni v laboratorijskih razmerah na 3 do 4 dni starih osebkih listnih uši vrste Myzus persicae (Sulzer, 1776), Homoptera: Aphididae) v 1, 2.5, 5, in 10 % razredčitvah. Opazovanja so bila opravljena 24 ur po uporabi. Učinkoviti so bili izvlečki s petroletrom vseh rastlin, ki so povzročili smrtnost (100 %, 53 % in 60 %) pri največjih koncentracijah. Etanolni in vodni ekstrakti niso imeli značilnega insekticidnega delovanja. Fitokemična analiza ekstraktov je pokazala veliko vsebnost terpenov v izvlečkih, dobljenih s petroletrom. Rezultati raziskave nakazujejo, da lahko naredimo bioinsekticide iz analiziranih rastlin na osnovi izvlečkov s petroletrom in jih uporabimo v integriranem varstvu rastlin. Ključne besede: Artemisia herba-alba, botanični insekticidi, Myzus persicae, Eucalyptus camaldulensis, Rosmarinus officinalis 1 INTRODUCTION Chemical pest control employs potent chemical pesticides to reduce or eliminate pests and constitutes the major way in crop production throughout the world. In fact, the use of these conventional insecticides have over the years manifested a number of disadvantages, the most 1 Mohamed Khider University, Faculty of Natural and Life Sciences, Department of Agronomy, 07000 Biskra, Algeria. E-mail: bnagro@yahoo.fr. 2 Hadj Lakhdar University, Institute of Veterinary and Agricultural Sciences, Department of Agronomy, 05000 Batna, Algeria. E-mail: frahnaama@yahoo.fr 3 Hadj Lakhdar University, Faculty of Sciences, Department of Natural and Life Sciences, 05000 Batna, Algeria. E-mail : azouiimane@hotmail.fr important of which are the risks involved for human health and for the environment (Ofuya and Okuku, 1994). To reduce the use of synthetic pesticides on fruit and vegetable plantations, phytochemicals and plant extracts have long been a subject of research in an effort to develop alternatives to conventional insecticides but with reduced health and environmental impact (Dancewicz et al, 2011). Most plant species that are used in phytomedicine contain ingredients, which inhibit the development of insects, hinder their feeding (antifeedants) or act as repellents and confusants (Laznik et al., 2010). The green peach aphid, Myzus persicae (Sulzer, 1776) is found throughout the world. In addition to attacking plants in the field, green peach aphid readily infests vegetables and ornamental plants grown in greenhouses (Capinera, 2011). Its management is generally based upon the use of synthetic insecticides (Ciarla et al, 2005). Unfortunately, there is little knowledge in the literature about the effect of a plant extracts such as Artemisia herba-alba Asso, Eucalyptus camaldulensis Dehnh. and Rosmarinus officinalis L. against aphids. This study aims to determine the toxicity of Artemisia herba-alba, Eucalyptus camaldulensis and Rosmarinus officinalis leaves extracts against Myzus persicae by using several concentrations. 2 MATERIALS AND METHODS 2.1 Selection of plant species and preparation of leaves extracts In April 2013, leaves of Artemisia herba-alba, Eucalyptus camaldulensis and Rosmarinus officinalis were collected from Batna in the East of Algeria. It is located at 35° 61' N latitude and 6° 24' E longitude with an elevation of 1048 meter above sea level. We prepared the extracts according to the method presented by N'guessan et al. (2009) using various techniques. First, we dried samples at 40 °C into an oven before grinding them with an electric grinder. Crude extracts were obtained by successive extractions with three solvents ordered by increasing polarity. In this order, we used petroleum ether, ethanol and distilled water. For extraction with petroleum ether, we dissolved 80 g of powder obtained from leaves in 240 mL of petroleum ether. A manual agitation was done for 10 min. Then, we filtered the mixture. The filtrate obtained was named etheric filtrate 1. On residual marks, we added 240 mL of petroleum ether; after 10 min of agitation and filtration, we obtained the etheric filtrate 2. The same operation allowed getting the etheric filtrate 3. These three filtrates were grouped together and concentrated on a bath sand. These series of operations resulted in a concentrated solution called etheric extract. After exhaustion by petroleum ether, residual marks were dried. The powder was recovered in 240 mL of ethanol. Homogenization by manual agitation during 10 min allowed getting the ethanolic filtrate 1. The same operation was repeated and gave the ethanolic filtrate 2. The ethanolic filtrates were also grouped and concentrated on a bath sand to give ethanolic extract. To prepare the aqueous extract, we infused dried powder in 800 mL of distilled water during 15 min. After filtration, we obtained aqueous extract. Finally, 4 concentrations were prepared from these extracts: 1, 2.5,5 and 10 %. 2.2 Aphid collecting and rearing We collected last stage larvae of Myzus persicae (Sulzer, 1776) in April 2014 from Biskra in the East of Algeria. It is located at 34° 52' N latitude and 5° 45' E longitude with an elevation of 120 meter above sea level. These larvae were found on Malva sylvestris L. A mass rearing of the green peach aphid was started on broad beans (Vicia faba L.) in a greenhouse. Each plant was inoculated with apterous adult when emerging in the morning. Aphids were collected after 10 days by brushing them carefully from the leaves. 2.3 Bioassay test To determine the insecticidal effect of etheric, ethanolic, and aqueous extracts of selected plants, 15 M. persicae apterous larvae (3 to 4 days-old) were placed in a Petri dish containing three leaves of V. faba soaked in different concentrations (1, 2.5,5 and 10 %) of these extracts with three replications. The experiment was carried out in the laboratory. The mortality was determined after 24 hours from the beginning of exposure. When no leg or antennal movements were observed, insects were considered dead (Salari et al, 2010). 2.4 Phytochemical screening We characterized the different chemical groups of plants extracts using standard procedures as described by Kayani et al. (2007), Benmehdi et al. (2012), and Rahim et al. (2012). 2.4.1 Test for alkaloids 0.2 g of each extract was warmed with 2 % H2SO4 for two minutes. Then, few drops of Dragendorffs reagent (solution of potassium bismuth iodide) were added. Presence of orange red precipitate indicated as positiveness for alkaloids. 2.4.2 Test for terpenoids (Salkowski test) 0.2 g of each extract was mixed in 2 mL of chloroform, and concentrated H2S04 (3 mL) was carefully added to form a layer. A reddish brown coloration of the inter face was formed to show positive results for the presence of terpenoids. 2.4.3 Test for saponins 0.2 g of each extract was shaken with 5 ml of distilled water. Then, it heated to boil. Frothing (appearance of creamy miss of small bubbles) shows the presence of saponins. 2.5 Statistical analysis The efficiency (E %) of different extracts was calculated according to the Schneider-Orelli formula: £T = [ t)/(10C- i) ] X 1Ф0 in which: b = percentage of individuals in the treated sample, and k = percentage of individuals found dead in the witness sample (Tomescu et al, 2009). A chi-square test was applied to estimate the correlation between mortality and concentrations. Afterwards, data were subjected to the logistic regression model to determine lethal concentrations. We used the statistical program Statistica 8 (StatSoft, Inc., Tulsa, OK) for all analyses. 3 RESULTS AND DISCUSSION In the conducted experiment, effects of the A. herba-alba, E. camaldulensis and R. officinalis leaves extracts were recorded in the control of the green peach aphid (Myzus persicae) after 24 hours. The statistical analyses indicated that only etheric extracts of all plants showed a dependence between the mortality and different concentrations (P < 0.01) (Table 1). Table 1: Mortality of Myzus persicae larvae with different types of plants extracts Plant Extract X2 P Artemisia herba-alba Etheric extract 146 0.00 Ethanolic extract 2.0 0.4 Aqueous extract 4.0 0.1 Eucalyptus camaldulensis Etheric extract 75.81 0.00 Ethanolic extract 4.0 0.1 Aqueous extract 2 0.4 Rosmarinus officinalis Etheric extract 91.7 0.00 Ethanolic extract 1 0.6 Aqueous extract 1 0.6 We obtained the greatest percentages of mortality of the aphid, 93 % and 100 %, with the two highest concentrations (5 % and 10 %) of A. herba-alba. In the case of E. camaldulensis, the percentage of mortality was almost 53 % at 10% and 60 % for R. officinalis at the same concentration (Figure 1). A. herba-alba Plant E. camaldulensis R. officinalis 120.00100.0080,0060.0040,0020,000,00- 0% 1% 2.5% 5% 10'% 0% 1 % 2.5% 5% 10' Concentration (%) Figure 1: Average mortality (% ± standard error) of Myzus persicae larvae with leaves extracts from A. herba-alba, E. camaldulensis and R. officinalis with several concentrations after 24 hours of exposure However, ethanolic extract of all plants did not show any dependence between mortality and concentrations (Table 1). The mortality of M. persicae obtained was 0% for all plants at a concentration of 5%, and almost 9% at 10 % when E. camaldulensis was used (Figure 1). Also, no dependence between the mortality and concentrations concerning aqueous extract of all plants (P > 0.05) (Table 1) was established. Nearly 8 % was obtained with A. herba-alba at 10 % and 13 % with R. officinalis at the same concentration (Figure 1). From the Logit analyses, the LC50 (Lethal Concentration) was 2.07 % for A. herba-alba, 8.35 % for E. camaldulensis and 6.6 % in the case of R. officinalis. These data proved that A. herba-alba is more toxic than the other two plants etheric extracts (Table 2). л Insecticidal activity of three plants extracts against Myzus persicae (Sulzer, 1776) and their phytochemical screening Table 2: Toxicity of etheric extracts on M. persicae larvae (LC50's [%] calculated by logistic regression) Plant extract B Wald /2 P Odds Ratio LC50 (%) A. herba-alba etheric extract 0.8 67.5 < 0.01 2.2 2.1 % E. camaldulensis etheric extract 0.3 69.0 < 0.01 1.3 8.3 % R. officinalis etheric extract 0.22 48.0 < 0.01 1.2 6.6 % Soliman (2007) reported that Artemisia herba-alba oil gave a high toxicity with LC50 0.023 % and caused 90.44 % reduction in the population on Aphis gossypii (Glover , 1877). Abdel-Shafy et al. (2009) evaluated the crude extracts with different solvents of A. herba-alba against the third instar larvae of Chrysomyia albiceps (Wiedemann, 1819). Results showed that all extracts had toxic effects on larvae. The settling of M. persicae on host plant leaves was strongly deterred by wormwood (Artemisia absinthium L.) (Dancewicz, 2008). Artemisia seiberi Besser oil extract was the most toxic to woolly apple aphid (Eriosoma lanigerum [Hausmann, 1802]) in terms of concentration and time responses compared with other tested oil extracts (Ateyyat et al., 2012). I§ik and Görür (2009) demonstrated that between 7 essential oils used against cabbage aphid (Brevicoryne brassicae [Linnaeus, 1758]), rosemary oil can be considered as an important aphidicide to control aphid population. It can be used also as an acaricide against the two-spotted spider mite (Tetranychus urticae Koch, 1836), causing complete mortality in the laboratory at concentrations that cause no phytotoxicity to host plants (Miresmailli, 2006). According to Rojht et al. (2012), the mortality rate of the Acanthoscelides obtectus (Say, 1831) adults after 7 days using ethanol extract of R. officinalis reached 91.2 % between the concentrations of 50 % and 100 %. The use of rosemary essential oils could significantly affect pest insects as well. In fact, the longevity, fecundity, and fertility of the cowpea weevils (Callosobruchus maculatus [Fabricius, 1775]), (Coleoptera, Bruchinae) were negatively affected by these oils (Douiri et al., 2014). Furthermore, 81.7 % adult mortality at 1 % concentration on sycamore lace bug (Corythucha ciliata [Say, 1832]) (Rojht et al, 2009). The highest mortality percentage against Hyalopterus pruni (Geoffroy, 1762) adults was achieved with extract of E. camaldulensis leaves, reached 92.6 % at 10 % after 48 days of treatment (Haji Younis, 2013). Elbanna (2006) recorded that 20 ml of the eucalyptus seed extract at concentration 1000 ppm caused 80 and 100 % mortality in larvae of Culex pipiens (Linnaeus, 1758) within 14 hours. Phytochemical screening showed the presence of terpenoids in the etheric extract of all plants used in this study (Table 3). Table 3: Phytochemical screening of A. herba-alba, E. camaldulensis and R. officinalis using different solvents Plant species Alkaloids Terpenoids Saponins PE E W PE E W PE E W A. herba-alba - - - + + + - - + E. camaldulensis - - - + + + - - + R. officinalis - - + + + + - - + (+) : positive, (-) : negative Many works showed the richness in terpenoids of A. herba-alba, like monoterpene hydrocarbons (Behtari, 2012), oxygenated monoterpenes (Hudaib and Aburjai, 2006) and sesquiterpenes (Laid, 2008; Paolini, 2010). Qualitative and quantitative analyses of A. herba-alba and Artemisia monosperma Delile essential oils showed that both oils were mainly characterized by high concentration of total terpene compounds (75.281 and 78.69 % respectively) and low concentration of sesquiterpenes (24.357 and 21.023 % respectively) (Soliman, 2007). Miresmailli et al. (2006) and Verma (2012) pointed out the presence of monoterpenes in rosemary whereas Zhang et al. (2014) reported its richness in diterpenoid and triterpenoid glycosides. Terpenoids are abundant also in the foliage of E. camaldulensis, providing the characteristic smell as well as being valuable economically and influencing ecological interactions (Leicach, 2010; Külheim et al., 2015). Moreover, in E. camaldulensis oil, monoterpenes were prevalent while sesquiterpene hydrocarbons and oxygenated sesquiterpenes were less represented (Mediouni Ben Jemäa, 2012). 4 CONCLUSIONS A. herba-alba, E. camaldulensis and R. officinalis leaves etheric extract were efficacious against Myzus persicae. The results obtained suggest that we can make bioinsecticides based on extracts from these plants for use in integrated pest management, which are a good alternative to conventional synthetic insecticides. This study is a first step and its purpose was to compare the effect of several plants leaves crude extracts against aphids. More studies will necessary to test the activity of each identified compounds against aphid species and other pests. 5 REFERENCES Ateyyat M., Abu-Romman S., Abu-Darwish M., Ghabeish I. 2012. Impact of flavonoids against woolly apple aphid, Eriosoma lanigerum (Hausmann) and its sole parasitoid, Aphelinus mali (Hald.). J. Agr. Sci. 4 (2) : 227-236, doi: 10.5539/jas.v4n2p227 Abdel-Shafy S., El-Khateeb R.M., Soliman M.M.M., Abdel-Aziz M.M. 2009. The efficacy of some wild medicinal plant extracts on the survival and development of third instar larvae of Chrysomyia albiceps (Wied) (Diptera: Calliphoridae). Trop. Anim. Health Pro. 41:1741-1753, 10.1007/s11250-009-9373-0 Benmehdi H., Hasnaoui O., Benali O., Salhi F. 2012. Phytochemical investigation of leaves and fruits extracts of Chamaerops humilis L. J. Mater. Environ. Sci. 3 (2) : 320-237 Behtari B., Gholami F., Khalid K.A., Tilaki G.D., Bahari R. 2012. Effect of growth stages and altitude on Artemisia herba-alba Asso essential oil growing in Iran. Jeobp 15 (2): 307 - 313 Capinera J.L. 2011. Green Peach Aphid, Myzus persicae (Sulzer) (Insecta: Hemiptera: Aphididae). Entomology and Nematology Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida, United states of America Ciarla M.V., Mareggiani G., Heit G., Puhl L. 2005. Myzus persicae (Homoptera: Aphididae) and Capsicum annuum (Solanaceae) volatiles: their effect on predators attraction Bol San Veg Plagas 31: 503-507 Dancewicz K., Gabrys B., Przybylska M. 2011. Effect of garlic (Allium sativum L.) and tansy (Tanaceum vulgare L.) extracts and potassic horticultural soap on the probing and feeding behaviour of Myzus persicae (Sulzer, 1776). Aphids and other hemipterous insects 17:129-136 Douiri L.F., Boughdad A., Alaoui M.H., Moumni M. 2014. Biological activity of Rosmarinus officinalisessential oils against Callosobruchus maculatus (Coleoptera, Bruchinae). J. Biol. Agri. Healtc. 4 (2): 5-14 Elbanna M.S. 2006. Larvaecidal effects of eucalyptus extract on the larvae of Culexpipiens mosquito. Int. J. Agri. Biol. 8 (6): 896-897. Haji Younis G. 2013. The Effect of Some Extracts on the Stone Fruit Aphid "Hyalopterus Pruni" in Duhok Region. Int. J. Pure Appl. Sci. Technol. 18 (2): 39-44 Hudaib M.M., Aburjai T.A. 2006. Composition of the essential oil from Artemisia herba-alba grown in Jordan. J. Essent. Oil Res. 18: 301-304, doi: 10.1080/10412905.2006.9699096 I§ik M., Görür G. 2009. Aphidicidial activity of seven essential oils against the cabbage aphid, Brevicoryne brassicae L. (Hemiptera: Aphididae). Munis Ent. Zool. 4 (2): 424-431. Kayani S.A., Masood A., Achakzai A.K.K., Anbreen S. 2007. Distribution of secondary metabolites in plants of Quetta-Balochistan. Pak. J. Bot. 39 (4): 1173-1179. Külheim C., Padovan A., Hefer C., Krause S.T., Köllner T.G., Myburg A.A., Degenhardt J., Foley W.J. 2015. The eucalyptus terpene synthase gene family. BMC Genomics. DOI 10.1186/s12864-015-1598-x, doi: 10.1186/s12864-015-1598-x Laid M., Hegazy M.E.F., Ahmed A.A., Kalla A., Belkacemi D., Ohta S. 2008. Sesquiterpene lactones from Algerian Artemisia herba-alba. Phytochem. Lett. 1: 85-88, doi: 10.1016/j.phytol.2008.04.002 Laznik Ž., Cunja V., Kač M., Trdan S. 2010. Efficacy of three natural substances against apple aphid (Aphis pomi De Geer, Aphididae, Homoptera) under laboratory conditions. Acta Agric. Slov. 97 (1): 19-23 Leicach S.R., Garau A.M., Guarnaschelli A.B., Yaber Grassa M.A., Sztarkera N.D., Datoa A. 2010. Changes in Eucalyptus camaldulensis essential oil composition as response to drought preconditioning. J. Plant Interact. 5 (3): 205-210, doi: 10.1080/17429145.2010.483744 Mediouni Ben Jemaa J., Haouel S., Bouaziz M., Khouja M.L. 2012. Seasonal variations in chemical composition and fumigant activity of five Eucalyptus essential oils against three moth pests of stored dates in Tunisia. J. Stored Prod. Res. 48: 61-67, 10.1016/j.jspr.2011.10.001 Miresmailli S., Bradbury R., Isman M.B. 2006. Comparative toxicity of Rosmarinus officinalis L. essential oil and blends of its major constituents against Tetranychus urticae Koch (Acari: Tetranychidae) on two different host plants. Pest Manag. Sci. 62:366-371, doi: 10.1002/ps.1157 N'guessan K., Kadja B., Zirihi G.N., Traoré D., Aké-assi L. 2009. Screening phytochimique de quelques plantes médicinales ivoiriennes utilisées en pays Krobou (Agboville, Cote-d'Ivoire). Sci. Nat. 6 (1): 1 - 15, doi: 10.4314/scinat.v6i1.48575 Ofuya T.I., Okuku I.E. 1994. Insecticidal effect of some plant extracts on the cowpea aphid Aphis craccivora Koch (Homoptera: Aphididae). Anz. Schädl.kd. Pflanzenschutz Umweltschutz, 67: 127-129, doi: 10.1007/BF01909033 Paolini J., El Ouariachi E., Bouyanzer A., Hammouti B., Desjobert J.M., Costa J., Muselli A. 2010. Chemical variability of Artemisia herba-alba Asso essential oils from East Morocco. Chem. Pap. 64 (5): 550-556, doi: 10.2478/s11696-010-0051-5 Rahim G., Qureshi R., Gulfraz M., Arshad M., Rahim S. 2012. Preliminary phytochemical screening and ethnomedicinal uses of Teucrium stocksianum from Malakand Division. J. Med. Plants Res. 6 (5): 704-707 Rojht H., Košir I.J., Trdan S. 2012. Chemical analysis of three herbal extracts and observation of their activity against adults of Acanthoscelides obtectus and Leptinotarsa decemlineata using a video tracking system. J.Plant Dis.Protect.119 (2) : 59-67 Rojht H., Meško A., Vidrih M., Trdan S. 2009. Insecticidal activity of four different substances against larvae and adults of sycamore lace bug (Corythucha ciliata [Say], Heteroptera, Tingidae). Acta Agric. Slov. 93 (1) : 31 -36, doi: 10.2478/v10014-009-0004-2 Salari E., Ahmadi, K., Dehyaghobi, R.Z., Purhematy, A., Takalloozadeh, H.M. 2012. Toxic and repellent effect of harmal (Peganum harmala L.) acetonic extract on several aphids and Tribolium castaneum (Herbst). Chil. J. Agr. Res. 72 (1): 147-151, doi: 10.4067/S0718-58392012000100023 Salari E., Ahmadi K., Zamani R. 2010. Study on the effects of acetonic extract of Otostegia Persica (Labiatae) on three aphid species and one stored product pest. Adv. Environ. Biol. 4 (3): 346-349 Soliman M.M.M. 2007. Phytochemical and toxicological studies of Artemisia L. (Compositae) essential oil against some insect pests. Arch. Phyt. Plant Prot. 40 (2): 128-138, doi: 10.1080/03235400500355808 Tomescu C.V., Brudea V., Rišca M. 2009. Preliminary research on the efficiency of some vegetal metabolites in fighting the mealy plum aphid (Hyalopterus pruni Geoffroi - Ord. Homoptera). Analele universitatii" Stefan cel mare" suceava sectiunea silvicultura serie noua nr.1 Verma R. S., Rahman L., Mishra S., Verma R.K., Singh A., Chauhan A., Yadav A.K., 2012. Volatile terpenoidcomposition of Rosmarinus officinalis, "Cim-Hariyali": variability in North India during annual growth. J. Chil. Chem. Soc. 57 (2): 1066-1068, doi: 10.4067/S0717-97072012000200001 Zhang Y., Adelakun T. A., Qu L., Li X., Li J., Han L., Wang T. 2014. New terpenoid glycosides obtained from Rosmarinus officinalis L. aerial parts. Fitoterapia, 99 : 78-85, doi : 10.1016/j.fitote.2014.09.004 COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.10 Agrovoc descriptors: setaria, grasses, physiological response, osmotic stress, salt tolerance, sowing depth, germination Agris category code: f60, f62 Effect of pre-chilling and environmental factors on breaking seed dormancy and germination of three foxtail species Vajihe AMINI1, Faezeh ZAEFARIAN1*, Mohammad REZVANI2 Received July 07, 2015; accepted August 25, 2015. Delo je prispelo 07. julija 2015, sprejeto 25. avgusta 2015. ABSTRACT The effect of wet and dry pre-chilling duration, pH, osmotic stress, salt stress and planting depth on seed germination and seedling emergence of three foxtail species (Setaria glauca, S. verticillata and S. viridis) was investigated in a series of laboratory and greenhouse experiments. Both wet and dry pre-chilling for 45 days promoted seed germination of S. glauca compared with the control. Pre-chilling was not significantly effective in seed dormancy breaking of S. viridis and S. verticillata. The maximum germination of foxtails (S. verticillata, S. viridis) was obtained when seeds were treated with pH 7 buffer solution. Increasing of osmotic and salt stress decreased seed germination of foxtails. Setaria verticillata seed germination was more tolerant than those of S. glauca and S. viridis to high water stress condition. Setaria glauca and S. verticillata seed germination were more tolerant to high salinity stress than S. viridis. Seedling emergence decreased with increasing the burial depth and no germination observed at 8 cm soil depth. Key words: osmotic and salt stress, seed depth burial. germination, S. glauca, S. verticillata and S. viridis IZVLEČEK UČINKI HLADNEGA PREDTRETIRANJA IN OKOLJSKIH DEJAVNIKOV NA PREKINITEV DORMANCE IN KALITEV TREH VRST MUHVIČEV Učinki trajanja mokrega in suhega hladnega predtretiranja, pH, ozmotskega in solnega stresa ter globine setve na kalitev in vznik so bili preučevani pri treh vrstah muhviča (sivozeleni muhvič- Setaria pumila (Poir.) Roem. & Schult.( = S. glauca auct.). , vretenčasti muhvič - S. verticillata (L.) P. Beauv. in zeleni muhvič - S. viridis (L.) P. Beauv.) v rastlinjaku in laboratoriju. Mokro in suho hladno predtretiranje v trajanju 45 dni je pospešilo kalitev semen sivozelenega muhviča v primerjavi s kontrolo. Isto obravnavanje ni imelo značilnega vpliva na prekinitev dormance semen pri zelenem in vretenčastem muhviču. Največja kalitev muhvičev (S. verticillata, S. viridis) je bila dosežena pri semenih, tretiranih s pufersko raztopino s pH 7. Povečanje ozmotskega in solnega stresa je zmanjšalo kalitev vseh vrst muhvičev Semena vretenčastega muhviča so bila bolj odporna na večji sušni stress kot semena zelenega in sivozelenega muhviča. Semena sivozelenega in vretenčastega muhviča so bila bolj odporna na velik slanostni stress kot semena zelenega muhviča. Vznik vseh treh vrst muhvičev se je zmanjševal s povečevanjem globine setve, na globini 8 cm kalitve ni bilo. Ključne besede: ozmotski in solni stress, globina setve, kalitev, Setaria pumila, S. verticillata and S. viridis 1 MSc. Student, Department of Agronomy, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran 2 Department of Agronomy, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran Corresponding author: fa_zaefarian@yahoo.com 3 Department of Agronomy, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran 1 INTRODUCTION Foxtail species (Setaria pumila (Poir.) Roem. & Schult. = Setaria glauca auct., S. verticillata (L.) P. Beauv. and S. viridis (L.) P. Beauv.); are member of Poaceae family and native to the Eurasia. Foxtails are the worst weeds that are interfering with world agriculture (Holm et al, 1977) and are considered as problematic in many crops such as corn (Zea mays L.), wheat (Triticum aestivum L.), soybean (Glycine max L.), potato (Solanum tuberosum L.) and sugarcane (Saccharum officinarum L.). Due to high competitive ability and reproductive potential, these species are expected to be a serious threat to summer crops and orchards in north of Iran. Seed germination is one of the critical phases in plant life cycle (Shoab et al., 2012) which is affected by dormancy and environmental factors such as light, soil pH, osmotic potential, salt stress, temperature and burial depth. The foxtails seeds are characterized by dormancy and a long period of survival in soil. Setaria glauca, S. viridis and S. verticillata are able to survive in soil for 13 to 39 years (Dekker, 2003). Dormancy can be defined as an inhibition mechanism of seed germination of intact viable seed to optimize the distribution of germination over time (Bewley and Black, 1983; Hilhorst, 1995) and is one of the survival mechanisms of invasive annual weeds (Baskin et al. 2004). Seed dormancy is categorized as physical, physiologic, morphologic, morpho-physiologic and combined dormancy (Baskin and Baskin, 2004). For breaking dormancy and enhancing of seed germination, moist chilling or cold stratification has been widely used in different plants (Schopmeyer, 1974; AOSA, 1992; ISTA, 1999; Wang and Beijak, 2000). Investigation of germination requirements show how a species germination process is adapted to habitat conditions and regulated by environmental factors (Van Assche et al., 2002). Thus, finding of some information about factors effective in seed dormancy breaking and optimal condition of germination and seedling growth are necessary for management of weeds. The aim of the present study is promotion of seed germination of foxtail species by means of moist and dry chilling and also investigation of effect of environmental factors such as soil pH, water and salt stress on seed germination and burial depth on seedling emergence. 2 MATERIALS AND METHODS 2.1 Plant materials and experimental conditions Laboratory and greenhouse experiments were carried out at Department of Agronomy, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran during 2013. The mature seeds of Setaria glauca, S. verticillata and S. viridis were collected from more than 200 plants in 2012, Qaemshahr, Iran. Seeds were cleaned and stored in paper bags in darkness at room temperature (23±2 °C) until start the experiments. Prior start laboratory experiments, seeds were surface-sterilized by soaking in 1 % sodium hypochlorite (NaOCl) for 1 min and subsequently rinsing with distilled water. Twenty five seeds were placed in Petri dishes (8 cm diameter) lined by two sheets of filter paper (Whatman No. 1). The filter paper was moistened with 5 ml of distilled water or treatment solutions. Petri dishes were sealed with Parafilm to reduce the water loss and placed in germinator with 16/8 h (day/night) photoperiod and 25/15 °C (day/night) fluctuating temperature with a light intensity of 300 (mol m-2 s-1. Germinated seeds with at least 2 mm long seminal root were counted after a period of four weeks. The percentage of germinated seeds was calculated using following equation: number of germinated seeds/number of total seeds x 100. 2.2 Pre-treatment by cold stratification To verify the effectiveness of the pre-chilling treatments, moisturized seeds with distilled water and dry seeds were placed in refrigerator at temperature of 4 °C for 15, 30 and 45 days. After the pre-chilling period; seed germination was tested as in the plant materials and experimental conditions section described. The best pre-treatment of wet or dry pre-chilling that promoted the maximum germination was considered as pre-treatment for further experiments (pH, osmotic stress, salt stress and seed burial depth). 2.3 Effect of pH on seed germination The effect of pH on seed germination was determined by using different buffer solutions of pH 3, 5, 7, 9 and 11 prepared according to the method described by Chachalis and Reddy (2000). Seed germination tested by method described in the plant materials and experimental conditions section. 2.4 Effect of osmotic stress on seed germination To evaluate the effect of osmotic stress, different levels of osmotic potential including 0, -0.1, -0.25, -0.5, -1 and -1.5 MPa were prepared by dissolving of 0, 99.4, 157.1, 222.2, 314.2, 384.8 g polyethylene glycol 6000 (Merck, Germany) in 1 L distilled water, respectively. Five ml of polyethylene glycol 6000 solution was added to the Petri dishes. Seed germination was tested according to the plant materials and experimental conditions section. 2.5 Effect of salt stress on seed germination The effects of salt stress on seed germination were evaluated by soaking seeds in solution of 0, 10, 20, 40, 80, 160 and 320 mM sodium chloride (NaCl) (Merck, Germany). Germination was tested according to the plant materials and experimental conditions section. 2.6 Effect of seed burial depth on seedling emergence Fifty seeds of foxtails were planted in soil in 16-cm-diameter plastic pots (30 cm height) at the depths of 0, 2, 5 and 8 cm in greenhouse. Soil used for experiment was a clay soil (clay, 61.4 %; silt, 7.9 %; sand, 30.7 %) with 7.49 pH and 2.58 % organic carbon. The temperature of the greenhouse was set at 28/20 °C (day/night) with a natural photoperiod. Pots were irrigated as needed to maintain soil moisture in field capacity. Seedling emergence was recorded as coleoptiles appeared. Seedling emergence counted every 7 days for 28 days. 2.7 Statistical analysis All experiments were conducted in a complete randomized design with four replicates. Analysis of variance was performed on transformed (Arcsine transformation) data. Significant difference of means were identified by protected LSD test (p = 0.05) and standard error bars. The SAS program (SAS Institute Inc., Cary, NC, USA) was used for the statistical analyses. 3 RESULTS AND DISCUSSION 3.1 Effect of wet and dry pre-chilling pretreatment on seed dormancy breaking of foxtails Germination of foxtails seeds was significantly affected by wet and dry pre-chilling durations. Initial germination (control treatment) of S. glauca, S. verticillata and S. viridis was 41.54 %, 47.89 % and 53.78 %, respectively (Table 1). Both wet and dry pre-chilling for 45 days increased seed germination of S. glauca about 32.35 % and 48.61 % compared with the control, respectively (Table 1). In contrast, seed germination of S. verticillata and S. viridis did not significantly increase by both wet and dry pre-chilling in comparison with control (Table 1). Therefore, for continuing the experiments just S. glauca seeds were dry pre-chilled for 45 days prior pH, osmotic potential, salt stress and seed burial depth experiments. Positive effects of wet and dry pre-chilling on seed germination of different weed species was previously reported by Wartidiningsih et al. (1994) and Baskin et al. (1992). For Poaceae family it is well known that the duration of stratification from 3 days to 6 weeks improve seed germination (Williams 1983, Smith-Jochum and Albrecht 1988, Matus-Càdiz et al. 2001, Matus-Càdiz and Hucl 2003). The cold pre-chilling may change the hormonal balance of seed and increase germination through enhancement of gibberellic activate the hydrolytic enzymes that make seeds acid and cytokinin activity and/or the decline of ready to germinate once they were moved to the abscisic acid (Copeland and McDonald, 2001). The warm temperature. wet pre-chilling provides enough moisture to Table 1: Effect of wet and dry pre-chilling duration on germination of foxtail seeds Germination (%) Wet pre-chilling Dry pre-chilling S. glauca S. verticillata S. viridis S. glauca S. verticillata S. viridis 41.54±0.81c 47.89±0.99a 53.78±0.91a 41.54±0.81ь 47.89±0.99a 53.78±0.91a 52.60±1.03 b 48.45±0.47a 60.35±1.59a 46.16±1.42b 33.08±1.12b 49.70±1.75ab 56.83±0.64ab 39.22±0.48b 34.43±1.50b 52.92 ±3.27b 29.83±1.22b 41.94±2.15b 61.40±0.65a 34.28±1.38b 57.00±1.50a 80.83±2.68 a 19.53±1.70c 59.22±2.19b Notes: Mean±Se; Values in each column followed by different superscripted letters indicate significant differences (p< 0.05). 3.2 Effect of pH on seed germination of foxtails Seed germination of foxtails was significantly influenced by pH solution. Approximately, 40 % of seeds of S. glauca germinated at pH 3, 5 and 7 (Fig. 1a). The maximum seed germination of S. verticillata and S. viridis occurred at pH 7 (Fig. 1b and 1c). The pH 9 and 11 had an inhibitory effect on both S. glauca and S. verticillata seed germination (Fig. 1a, 1b) However, about 25 % of S. viridis seeds germinated at pH 9 (Fig. 1c). Inhibition of germination at pH 9 and 11 shows that soil pH is a limiting factor for seed germination. Wilson (1979) and Singh and Achhireddy (1984) indicated that a narrow range of pH from 6 to 7 was needed for germination of canadian thistle (Cirsium arvense L.) and strangler vine (Mor reni a odorata Lindl.). Chachalis and Reddy (2000) showed that trumpet creeper (Campsis radicans L.) germination was limited by extreme pH range (pH 4 or 10). In contrast, Chachalis et al. (2008), Fani Yazdi et al. (2013) and Rezvani and Fani Yazdi (2013) reported that seed germination of venice mallow (Hibiscus trionum L. HIBTR), sheep sorrel (Rumex acetosella L.) and black nightshade (Solanum nigrum L.) occurred over a wide range of pH, that shows pH should not be a limiting factor for germination of some plants. 60 o4 40 i 20 u CD 3 5 7 9 11 pH 0 60 о4 40 20 CD 60 . s 40 is Й S CD 20 [b] d d 3 5 7 9 11 pH Figure 1: Effect of pH on germination of foxtails seed. Setaria glauca (a), S. verticillata (b) and S. viridis (c). The columns with the same letter are not significantly different. Vertical bars are standard error of the means. 3.3 Effect of osmotic stress on seed germination of foxtails Osmotic stress significantly affected seed germination of Setaria glauca, S. verticillata and S. viridis. With increasing osmotic stress a decline in seed germination of foxtails was recorded (Fig. 2a, 2b and 2c). At osmotic stress -0.5 MPa, S. verticillata seed germination was higher than those of S. glauca and S. viridis (Fig. 2a, 2b and 2c). Seed germination of S. verticillata was more tolerant to high water stress than S. glauca and S. viridis. About 40.35 % of S. verticillata seeds germinated at -0.5 MPa (Fig. 2b). Seed germination of S. glauca and S. viridis was 33.05 % and 29.09 % at -0.5 MPa osmotic potential, respectively (Fig. 2a and 2c). Germination of foxtail seeds was inhibited when seeds were exposed to osmotic potential lower than -0.5 MPa. These results show that foxtails seeds are sensitive to high osmotic stress and germination is favored by a moist environment. Therefore, low moisture of soil from mid spring up to summer could be a limiting factor of emergence of foxtails in the north of Iran. Manthey and 0 0 Nalewaja (1987) showed that germination of S. glauca and S. viridis was reduced by water stress and S. viridis germinated more rapidly than S. glauca. Germination of horseweed (Conyza canadensis (L.) Cronquist) decreased as osmotic potential increased from 0 (distilled water) to -0.8 MPa (Nandula et al., 2006). Our results are in agreement with the work of Shaw et al. (1991) on redvine (Bunnichia sp.) and Reddy and Singh (1992) on hairy beggarticks (Bidens pilosa L.). Low osmotic potential was found to inhibit germination of trumpet creeper (Chachalis and Reddy, 2000), texasweed (Caperonia palustris (L.) A. St. Hil.) (Koger et al, 2004) and cadillo (Urena lobata) (Wang et al, 2009). Rezvani and Fani Yazdi (2013) and Fani Yazdi et al. (2013) reported that low water stress significantly reduced the germination of both black nightshade and sheep sorrel. 60 g . 2 40 "ce _ Ö 1 20 О 0 0.1 0.25 0.5 1 1.5 Osmotic stress (—MPa) 0 ö о Ö О 80 60 - 40 20 [c] d 0.1 0.25 0.5 1 Osmotic stress (—MPa) 1.5 Figure 2: Effect of osmotic stress on germination of foxtail seeds. Setaria glauca (a), S. verticillata (b) and S. viridis (c). The columns with the same letter are not significantly different. Vertical bars are standard error of the means d 0 0 3.4 Effect of salt stress on seed germination of foxtails The germination of S. glauca seeds was not significantly differed among treatments in the range of 10 to 80 mM NaCl concentration. When seeds were treated with 320 mM NaCl, seed germination was inhibited (Fig. 3a). Similarly, seed germination of S. verticillata was not significantly differed in comparison with the control as salt stress increased from 10 to 80 mM NaCl. No germination occurred as seeds were treated with 320 mM NaCl (Fig. 3b). The germination of S. viridis decreased significantly as salt concentrations increased and no seed germination was observed at 160 mM NaCl (Fig. 3c). These data show that foxtails seeds were fairly tolerant to salt stress. Zia and Khan (2004), Koger et al. (2004), Nandula et al. (2006) and Lu et al. (2006) also reported negative effect of salt stress on seed germination of different plants. Rao et al. (2008) showed that germination of American sloughgrass was inhibited at 300 mM NaCl concentration. 100 g 80 H .2 60 te ■S 40 ü 20 [a] 0 10 20 40 80 160 320 NaCl concentrations (mM) d 0 60 [b] J40 "S с g 20 Щ C ШШ 0 10 20 40 80 160 320 NaCl concentrations (mM) 0 0 10 20 40 80 160 320 NaCl concentrations (mM) Figure 3: Effect of NaCl concentration on germination of foxtail seeds. Setaria glauca (a), S. verticillata (b) and S. viridis (c). The columns with the same letter are not significantly different. Vertical bars are standard error of the means 3.5 Effect of seed burial depth on seedling emergence of foxtails Seed burial depth markedly influenced on seedling emergence of Setaria glauca, S. verticillata and S. viridis. The maximum seedling emergence of foxtails was found where seeds were sown on the soil surface. The lowest seedling emergence was obtained where planting depth was 8 cm (Fig. 4a, 4b, 4c). Decreasing in seedling emergence due to increasing burial depth could be linked primarily to seed energy reserves (Mennan and Ngouajio, 2006). Seeds of bigger size have higher energy reserve than those of smaller seed size; therefore can emerge from higher depth. Chauhan et al. (2006) indicated that light and seed size generally limit seedling emergence from deep in the soil. Also, low emergence from bigger depths because of the lack of oxygen diffusion and the presence of CO2 deriving from soil biological activity has been reported by Benvenuti and Macchia (1995). Decreased emergence by increasing in planting depth has been reported in several weed species, including hairy beggarticks (Reddy and Singh, 1992), horse purslane (Trianthema portulacastrum L.) (Balyan and Bhan, 1986), stranglervine (Singh and Achhireddy, 1984), and horseweed (Nandula et al., 2006). 100 Ž 80 .2 60 I 40 3 20 [a] c 1 a d 0 0 2 5 8 Burial depth (cm) 100 [b] g 80 .2 60 I 40 CU Ü 20 0 c i 0 2 5 Burial depth (cm) 100 g 80 .2 60 at min40 Ü 20 0 Figure 4: Effect of burial depth on germination of foxtail seeds. Setaria glauca (a), S. verticillata (b) and S. viridis (c). The columns with the same letter are not significantly different. Vertical bars are standard error of the means a - a Ujl 0 2 5 8 Burial depth (cm) 4 CONCLUSIONS Seed dormancy of foxtails species showed different responses to pre-chilling treatments. However, dry pre-chilling was only significantly effective in seed dormancy breaking of S. glauca. Moreover, pH, salt and osmotic stress and seed planting depth significantly altered seed germination of foxtails. The results of the experiments could be effective in understanding the distribution of foxtails in agricultural ecosystems in the future. High seedling emergence of these species on the soil surface could be suggesting light requirements. Therefore, spreading of foxtails would be higher in fields with no-tillage or minimum-tillage practices. Our results suggest that increasing of tillage depth could be an effective weed management strategy to reduce seedling emergence of foxtails. 5 REFERENCES AOSA (Association of Official Seed Analysts). 1992. Rules for testing seeds. Journal of Seed Technology, 6: 1-125 Balyan, R.S., Bhan, V.M., 1986. Germination of horse purslane (Trianthema portulacastrum) in relation to temperature, storage conditions, and seedling depths. Weed Science, 34: 513-5 Baskin, C.C., Baskin, J.M., Hoffman, G.R., 1992. Seed dormancy in the prairie forbs Echinacea angustifolia var. angustifolia (Asteaceae): after-ripening pattern during cold stratification. International Journal of Plant Science, 153: 239243, DOI: 10.1086/297027 Baskin, C.C., Milberg, P., Andersson, L., Baskin, J.M., 2004. Germination ecology of the annual weeds Capsella bursa-pastoris and Descurainia sophia originating from high northern latitudes. Weed Research, 44: 60-68, DOI: 10.1046/j.1365-3180.2003.00373.x Baskin, J.M., Baskin, C.C., 2004. A classification system for seed dormancy. Seed Science Research, 14: 1-16, DOI: 10.1079/SSR2003150 Benvenuti, S., Macchia, M., 1995. Hypoxia effect on buried weed seed germination. Weed Research, 35: 343-351, 10.1111/j.1365-3180.1995.tb01629.x Bewley, J.D., Black, M., 1983. Physiology and Biochemistry of Seeds In Relation to Germination. Development, germination, and growth. Vol. 1. pp. 81-100. Berlin, Heidelberg, New York, Springer Verlag. Chachalis, D., Reddy, K.N., 2000. Factors affecting Campsis radicans seed germination and seedling emergence. Weed Science, 48: 212-216, DOI: 10.1614/0043- 1745(2000)048[0212:FACRSG]2.0.ra;2 Chachalis, D., Korres, N., Khah, E.M., 2008. Factors affecting seed germination and emergence of venice mallow (Hibiscus trionum). Weed Science, 56: 509-515, DOI: 10.1614/WS-07-144.1 Chauhan, B. S., Gill, G., Preston, C., 2006. Seedling recruitment pattern and depth of recruitment of 10 weed species in minimum tillage and no-till seeding systems. Weed Science, 54: 658-668, DOI: 10.1614/WS-05-135R.1 Copeland, L.O., McDonald, M., 2001. Principles of seed science and Technology. Kluwer Academic Publisher, Norwell, MA, USA, DOI: 10.1007/9781-4615-1619-4 Dekker, J., 2003. The Foxtail (Setaria) species-group. Weed Science, 51: 611-656, DOI: 10.1614/P2002-IR Fani Yazdi, S.A., Rezvani, M., Rashed Mohassel, M.H., Ghanizadeh, H., 2013. Factors affecting seed germination and seedling emergence of sheep sorrel (Rumex acetosella). Romanian Agricultural Research, 30: 373-380 Hilhorst, H.W.M., 1995. A critical update on seed dormancy. I. Primary dormancy. Seed Science Research, 5: 61-73, DOI: 10.1017/S0960258500002634 Holm, L.G., Plucknett, D. L., Pancho, J.V., Herberger, J. P., 1977. The world's worst weeds-distribution and biology. The East-West Food Institute, Honolulu, HI. ISTA (International Seed Testing Association). 1999. International rules for seed testing, Seed Science and Technology. Koger, C.H., Reddy, K.S., Poston, D.H., 2004. Factors affecting seed germination, seedling emergence and survival of Texasweed (Caperonia palustris). Weed Science, 52: 989-995, DOI: 10.1614/WS-03-139R2 Manthey, D.R., Nalewaja, J.D., 1987. Germination of two foxtail (Setaria) species. Weed Technology, 1: 302-304 Matus-Cadiz, M., Hucl, P., Munasinghe, G., 2001. Seed dormancy and germination in three annual canarygrass (Phalaris canariensis L.) cultivars relative to spring wheat (Triticum aestivum L.). Seed Science Technology, 29: 523-531 Matus-Cadiz, M., Hucl, P., 2003. Comparison of pre-treatments for inducing germination in highly dormant wheat genotypes. Canadian Journal Plant Science, 83: 729-735, DOI: 10.4141/P03-008 Mennan, H., Ngouajio, M., 2006. Seasonal cycles in germination and seedling emergence of summer and winter populations of catchweed bedstraw (Galium aparine) and wild mustard (Brassica Kaber). Weed Science, 54: 114-120, DOI: 10.1614/WS-05-107R1.1 Nandula, V.K., Eubank, T.W., Poston, D.H., Koger, C.H., Reddy, K.N., 2006. Factors affecting germination of horseweed (Conyza Canadensis). Weed Science, 54: 898-902, DOI: 10.1614/WS-06-006R2.1 Rao, N., Dong, L., Jun, L., Zhang, H., 2008. Influence of environmental factors on seed germination and seedling emergence of American slough grass (Beckmannia syzigachne). Weed Science, 56: 529533, DOI: 10.1614/WS-07-158.1 Reddy, K.N., Singh, M., 1992. Germination and emergence of hairy beggarticks (Bidens pi losa). Weed Science, 40: 195-199 Rezvani, M., Fani Yazdi, S.A., 2013. Factors affecting seed germination of black nightshade (Solanum nigrum). Acta Botanica Hungarica, 55(3-4): 397408, DOI: 10.1556/ABot.55.2013.3-4.15 Schopmeyer, C.S., 1974 Tech. Coordinator. Seeds of woody plants in the United States. USDA, Forest Service, Agriculture Handbook No. 450. Washington, DC: US Government Printing Office. Shaw, D.R., Mack, R.E., Smith, C.A., 1991. Redvine (Brunnichia avata) germination and emergence. Weed Science, 39: 33-36 Shoab, M., Tanveer A., Khaliq A., Haider Ali H. 2012. Effect of Seed Size and Ecological Factors on Germination of Emex spinosa. World Applied Science Journal, 17: 964-969 Singh, M., Achhireddy, N.R., 1984. Germination and ecology of milkweedvine (Morrenia odorata). Weed Science, 32: 781-785 Smith-Jochum, C., Albrecht, M.L., 1988. Transplanting or seeding in raised beds aids field establishment of some Echinacea species. Horticultural Science, 23 : 1004-1005 Van Assche, J., Van Nerum, D., Darius, P., 2002. The comparative germination ecology of nine Rumex species. Plant Ecology, 159: 131-142, DOI: 10.1023/A:1015553905110 Wang, B.S.P., Berjak, P., 2000. Beneficial effects of moist chilling on the seeds of black spruce (Picea mariana (Mill.) B. S. P.). Annals of Botany, 86: 2936, DOI: 10.1006/anbo.2000.1150 Wang, J., Ferrell, J., MacDonald, G., Sellers, B., 2009. Factors affecting seed germination of Cadillo (Urena lobata). Weed Science, 57: 31-35, DOI: 10.1614/WS-08-092.1 Wartidiningsih, N., Geneve, R.L., Kester, S.T., 1994. Osmotic priming or chilling stratification improves seed germination of purple coneflower. Horticultural Science, 29: 1445-1448 Williams E.D. 1983. Effects of temperature, light, nitrate and pre-chilling on seed germination of grassland plants. Annals Applied Biology 103: 161172, DOI: 10.1111/j.1744-7348.1983.tb02752.x Wilson, R.G., 1979. Germination and seedling development of Canada thistle (Cirsium arvense). Weed Science, 27: 146-151 Zia, S., Khan, M.A., 2004. Effect of light, salinity and temperature on seed germination of Limonium stocksii. Canadian Journal of Botany, 82: 151-157, DOI: 10.1139/b03-118 COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.11 Agrovoc descriptors: agrometeorology, Dactylis glomerata, grasses, herbage crops, crop yield, drought, growth, simulation models, meteorological factors Agris category code: p40, u30, f01 Simulation of herbage yield and growth components of Cock's foot (Dactylis glomerata L.) in Jablje using the calibrated LINGRA-N model Tjaša POGAČAR1, Lučka KAJFEŽ-BOGATAJ2 Received June 03, 2015; accepted August 20, 2015. Delo je prispelo 03. junija 2015, sprejeto 20. avgusta 2015. ABSTRACT In the study the previously calibrated LINGRA-N model was used for a long term simulation (1964-2013) of the herbage dry matter yield (GRASS) and growth analysis of Cock's foot (Dactylis glomerata L.) in Jablje. Changes in the yearly GRASS variability are reflected in the appearance of outliers in the second half of the study period. The biggest reductions in GRASS are seen in the years 1992, 1993 and 2003. These are the driest years according to meteorological variables (high maximum and minimum air temperatures, low precipitation) and also according to the simulations, with the lowest reduction factor for crop growth due to drought. The potential yield (YIELD) is not linearly dependent on meteorological variables. Some growth components were compared on a daily basis in a dry year (1993) and an average year (1994). In 1993, for instance, 53 % of photosynthetically active radiation was intercepted, against 75 % in 1994. Seasonal development of the actual soil moisture content was linked to the development of the leaf area index and consequently to the mass of green leaves, to the roots mass, to the mass of dead leaves and to GRASS. The results highlight the need for further research, on field and with simulations. As regards the latter, we have to keep in mind that they inevitably involve various uncertainties. Key words: simulation, LINGRA-N, cock's foot, herbage yield, drought, growth analysis IZVLEČEK SIMULACIJA PRIDELKA ZELINJA IN KOMPONET RASTI NAVADNE PASJE TRAVE (Dactylis glomerata L.) V JABLJAH Z UMERJENIM MODELOM LINGRA-N Predhodno umerjen model LINGRA-N smo uporabili za simulacijo pridelka suhega zelinja (GRASS) in komponent rasti navadne pasje trave (Dactylis glomerata L.) v 50-letnem obdobju (1964-2013) v Jabljah. Izkazalo se je, da so se v drugi polovici obravnavanega obdobja pri simulacijah GRASS na letni ravni začeli pojavljati osamelci. GRASS je bil najmanjši v letih 1992, 1993 in 2003. To so tudi najbolj suha leta, tako na podlagi meteoroloških spremenljivk kot tudi na podlagi simuliranega faktorja zmanjšanja rasti zaradi suše. Potencialni pridelek (YIELD) ni linearno odvisen od meteoroloških spremenljivk. Določene komponente rasti smo na dnevni skali primerjali v sušnem letu 1993 in povprečnem 1994. V letu 1993 je bilo na primer prestreženega fotosintetsko aktivnega sevanja 53 %, v letu 1994 pa 75 %. Razvoj stanja vode v tleh tekom leta smo povezali z razvojem indeksa listne površine ter posledično z razvojem mase zelenih listov, mase korenin, mase odmrlih listov in GRASS. Rezultati opozarjajo na pomembnost nadaljnjih raziskav, tako poljskih poskusov kot tudi modelskih simulacij. Pri slednjih se moramo zavedati, da nosijo s seboj negotovosti iz različnih virov. Ključne besede: modeliranje, LINGRA-N, navadna pasja trava, pridelek travne ruše, suša, analiza rasti 1 univ. dipl. meteorol., University of Ljubljana, Biotechnical Faculty, Jamnikarjeva 101, SI-1000 Ljubljana, tjasa.pogacar@bf.uni-lj.si 2 prof. dr., University of Ljubljana, Biotechnical Faculty, Jamnikarjeva 101, SI-1000 Ljubljana, lucka.kajfez.bogataj@bf.uni-lj.si This article is based on research undertaken for a doctoral dissertation by Tjaša Pogačar. Supervisor: Prof. Dr. Lučka Kajfež-Bogataj. Članek je nastal na osnovi raziskav v okviru doktorske disertacije Tjaše Pogačar. Mentorica: prof. dr. Lučka Kajfež-Bogataj. 1 INTRODUCTION Annual grass production varies widely, even under standard management conditions (Laidlaw, 2009). The considerable year-to-year and seasonal variation in grassland production is of major importance, as production systems must allow for the risk of unfavourable weather conditions (Trnka et al., 2006). The dependence of grassland herbage dry matter (DM) production on weather factors and their interaction with soil conditions, sward composition and management have been shown in many analyses (Trnka et al., 2006; Barrett et al., 2005; Čop, 1992). Even individual variables important in the description of grassland growth like leaf area index (LAI) are strongly weather dependent. For example, when there are sufficient mineral nutrients in the soil, the development of the canopy (with LAI < 4) of a perennial ryegrass crop during regrowth after winter or after a cut in spring time, essentially depends on the temperature (Lambert et al., 1999). Drought is one of the most important weather phenomena, having a major impact on grass sward growth and herbage yield. In contrast to majority field crops, grasses which constitute major part of seminatural grasslands are perennial plants and grow for several years. According to Tehnološka priporočila ... (2008), the consequences of severe droughts affect grassland sward productivity over the next years through the changes in the botanical composition of the sward, which is adapting to new growth conditions. This effect is long term and it is not obvious in monocultures, which are sown every few years. Another problem is that when rain returns after a period of drought precipitation may not be in excess of evapotranspiration so soil moisture content may not increase significantly (Laidlaw, 2009). So grassland sward makes use of periods when enough water is available and the abundant spring growth is often followed by summer hibernation. Laidlaw (2009) states that early summer droughts may not have a long term impact on yield. In Slovenia, periods of drought are becoming increasingly problematic for forage production in summer months, especially on lighter soils (Dolničar, 2013). For example, in 2006 74 % of agricultural area damaged by drought was under permanent grasslands and pastures (Sušnik, 2006). According to climate change scenarios for Slovenia by the middle of the century (Prihodnje ... , 2014) we can expect continuous problems with drought stress due to higher air temperatures and, at least in the southern part of the country, lower summer precipitation rates. Appropriate knowledge and understanding of the impact of climate variability on agricultural production is therefore essential for devising an adaptation strategy (Ceglar and Kajfež-Bogataj, 2012). From this point of view, crop modelling is very important for studies of the impacts of weather and climate on production. In this paper the work with the calibrated LINGRA-N model (Wolf, 2012), is described. The aim was to use the model for a long term simulation (50-year period) of the herbage dry matter (DM) yield of a grass monoculture, which brings the opportunity to observe the year-to-year variability and yield declines in years of drought. Furthermore, the growth analysis was undertaken with the intention of better understanding the interactions between growth components. This has an important role in grassland management science, as growth analyses of grass crop are rare in Slovenia, on the field or in the lab. Even if there is one, the experiment cannot be maintained for such a long period of time. Additionally, some variables of water balance were studied - their influence on the yield, its year-to-year variability or their development during average and dry years. The comparison was made with year-to-year variability of meteorological data for the central Slovenia (meteorological station Brnik). 2 METHODS AND DATA The simulations were made with the LINGRA-N model, which was previously calibrated with herbage DM yield data for cock's foot (Dactylis glomerata L.) in Jablje from the experiment (KIS, 2014) that was performed in the periods 1998— 2003 and 2008-2013. The average measured herbage DM yield for both periods together was 9525 kgDM ha-1 with the standard deviation of 1742 kgDM ha-1 (Figure 1). The performance of LINGRA-N was good, with RMSE% = 12 % and with the index of agreement (Willmott, 1982) d = 0.84 (Pogačar et al., 2015). _1 зооэ -, i 12000 Jnooo ^10000 9000 s O sooo g" 7000 ® 6000 - 5000 -I-,-,-,-,-,-,-,-,-,-,-,-,-,-,-, cocDO-t-гмп^тюг-соазо^гчп СЛСЛООООООООООт-^-т-т-OJCDDOOOOOOOOOOOOO Figure 1: Average measured yearly herbage DM yield o 2013 (data: KIS, 2014) Slika 1: Povprečni izmerjen letni pridelek suhega zelin 2008-2013 (podatki: KIS, 2014) 2.1 Input data The 50-year period of the simulation was set to 1964-2013 due to the availability of the meteorological data. For Jablje, the most representative meteorological station is Airport Ljubljana (Brnik). However, the distance of 12 km between the two brings some uncertainty to the modelling results, especially in the case of summer local convective events. The input for LINGRA-N includes daily data on minimum and maximum air temperatures (°C), precipitation (mm), mean wind speed (m s-1), global radiation (kJ m-2) and early morning vapour pressure (kPa), all obtained from the Slovenian Environment Agency (ARSO, 2014). Air temperatures were lower at the beginning of the 50-year period (Figure 2, left) and so was global radiation (Figure 2, right). For the whole period, the average of average minimum daily air temperatures for the vegetation period (AprilSeptember) (TminVP) is 9.3°C, the average of average summer (June-August) minimum daily air temperatures (TminS) is 12.1°C, the average of average maximum daily air temperatures for the vegetation period (TmaxVP) is 22°C, and the average of average summer maximum daily air ock's foot in Jablje for the periods 1998-2003 and 2008-navadne pasje trave v Jabljah za obdobji 1998-2003 in temperatures (TmaxS) is 25°C. In the second half of the period TmaxS dropped below this average in just seven years. TmaxS was extremely high in the years 2003, 2013, 2012, 1992 and 1983. It is clear that not only air temperatures but also their year-to-year variability are increasing. Something very similar holds true for the other presented air temperatures. However, the year-to-year variability of TminVP and TminS was higher in the first half of the period, due to a possibly non-climatic jump around the year 1978. Global radiation is increasing even more notably. Very high values were all reached after the year 2000: in 2011, 2003, 2009, 2000, 2007, 2012 and 2013. The 50-year average of precipitation during the vegetation period (RRvp) is 734 mm, of which on average 396 mm fell in the summer time (RRs) (Figure 2, right). The decrease in precipitation is not obvious, but the variability increased in the second half of the 50-year period in both cases. There have lately been more years with low RRvp and especially with low RRs. RRvp was less than 500 mm in the years 1992, 2003, 1983 and 1993, while RRs was less than 250 mm in the years 1983, 1992, 2001, 2003,2013 and 1993. Figure 2: Left: Average minimum daily air temperature for the vegetation period (TminVP), average summer minimum daily air temperature (TminS), average maximum daily air temperature for the vegetation period (TmaxVP) and average summer maximum daily air temperature (TmaxS) in the period 1964-2013. Right: Precipitation during the vegetation period (RRvp), summer precipitation (RRs), and global radiation sum for the vegetation period (RDvp) in the period 1964-2013 Slika 2: Levo: Povprečna minimalna dnevna temperatura zraka za vegetacijsko obdobje (TminVP), povprečna poletna minimalna dnevna temperatura zraka (TminS), povprečna maksimalna dnevna temperatura zraka za vegetacijsko obdobje (TmaxVP) in povprečna poletna maksimalna dnevna temperatura zraka (TmaxS) v obdobju 1964-2013. Desno: Količina padavin v vegetacijskem obdobju (RRvp), poletna količina padavin (RRs) in vsota globalnega obsevanja v vegetacijskem obdobju (RDvp) v obdobju 1964-2013 The used soil type in Jablje is pseudogley-gley, deep and moderate, the texture is silty clay. The description can be found in Tajnšek (2003). Soil moisture content at saturation is 0.5 cm3 cm-3, soil moisture content at field capacity is 0.36 cm3 cm-3 and soil moisture content at wilting point is 0.14 cm3 cm-3. The initial soil water content is set to field capacity (Pogačar et al., 2015). The rooted zone is changing with the growth of roots, every year from 30 to 40 cm. Four mowings are assumed and are set on fixed dates: 12 May, 1 July, 30 August and 17 October. The grass sward is fertilized on 1 April (60 kgN ha-1) and on the first day after the first (50 kgN ha-1) and the second (46 kgN ha-1) mowing. Furthermore, calibrated crop and soil parameters are required as input. There are 27 of them, the most influential (Pogačar et al., 2015) are the thresholds for reductions of radiation use efficiency due to low minimum temperature (TMNFTB = -3°C) or high soil temperature (TMPFTB = 25°C), the leaf area index after mowing (CLAI = 0.8 m2 m-2), the maximum light use efficiency (RUETB = 2.6 gDMMJ-1PAR), the fraction of precipitation lost by surface runoff (RUNFR = 0.08), the initial number of tillers (TILLI = 7000 m-2), the mineral soil nitrogen (N) available at the start of the growth period (NMINS = 400 kgN ha-1), the fraction of total biomass to roots under stressed conditions (FRT = 0.2) and the recovery fractions of fertiliser N applications (NRFTAB = 0.7). 2.2 Overview of output variables in the LINGRA-N model From each simulation run two output files are obtained. One gives the daily results (as model time step is 1 day) for each simulated year (Table 1). The other contains yearly cumulative or average (depending on the characteristics of the variable) values for most of the variables (exceptions are marked grey in Table 1). Table 1: Output variables of LINGRA-N simulated for each day (DM: dry matter, N: nitrogen). Variables for which model does not calculate yearly cumulative or average values are marked grey Preglednica 1: Izhodne spremenljivke modela LINGRA-N, simulirane za vsak dan (DM: suha snov, N: dušik). S sivo so označene spremenljivke, za katere model ne izračuna letnih povprečij oz. vsot Variable Unit Description Water balance variables DRAIN mm cumulative drainage ESOIL mm cumulative soil evaporation IRR mm cumulative irrigation RAIN mm cumulative precipitation RUNOF mm cumulative runoff SMACT 3 -3 cm cm actual soil moisture content in rooted zone WAVT mm available water in rooted zone WTOT mm water in rooted zone TRANS mm cumulative crop transpiration Variables based on nitrogen NLIV kgN ha-1 amount of N in living crop organs NLOSS kgN ha-1 N loss in dead crop organs and cut grass NMIN kgN ha-1 amount of organic N potentially available by mineralization from the soil NMINT kgN ha-1 mineral N directly available from soil and fertiliser NNI / nitrogen nutrition index (range 0-1) NUPT kgN ha-1 N uptake by crop from soil Crop variables DVS - development stage LAI 2 -2 m m leaf area index PAR MJ m-2d-1 daily amount of photosynthetically active radiation PARAB MJ m-2d-1 daily amount of PAR as intercepted by the crop canopy TILLER m-2 number of tillers TRANRF / reduction factor for crop growth due to drought/wetness (range 0-1) WLVD kgDM ha-1 mass of dead leaves in the field WLVG kgDM ha-1 mass of green leaves in the field WRE kgDM ha-1 mass of reserves (storage carbohydrates) WRT kgDM ha-1 roots mass TSUML °C temperature sum from emergence TADRW kgDM ha-1 mass of green and dead leaves in the field plus herbage DM yield GRASS kgDM ha-1 herbage DM yield YIELD kgDM ha-1 mass of harvestable leaves in the field plus herbage DM yield In the second output file there are also yearly values of nitrogen use efficiency (NUE, kgDM kg-1N), radiation use efficiency (RUE, gDM MJ-1PAR) and water use efficiency (WUE, gDM kg -1water). In this paper some of the simulated variables are studied. In the first place the herbage DM yield of grassland (GRASS) and the potential yield (YIELD), in connection with input weather variables and the reduction factor for crop growth due to drought (TRANRF) on a yearly basis. The dependence of RUE on TRANRF is shown. To further describe the water status, the yearly development of the actual soil moisture content in the rooted zone (SMACT) is examined during a dry year (1993) and an average year (1994), in which GRASS is very close to the average GRASS for the whole period. Also, the daily amount of photosynthetically active radiation (PAR) and the daily amount of PAR as intercepted by the grass crop canopy (PARAB) are compared with each other in the two years. This kind of a comparison is also made for the variables of the daily growth of the grass crop like the mass of green leaves (WLVG), the roots mass (WRT) and the mass of dead leaves (WLVD). Furthermore, the leaf area index (LAI) progress during dry and average years is presented. To better understand the simulation of those variables there is a short description based on Wolf (2012) of how they are calculated in the LINGRA-N model (sections 2.3 to 2.5). 2.3 Growth variables Growth variable PARAB (MJ m-2d-1) is calculated as the daily amount of incoming PAR (MJ m-2d-1) times the fractional light interception: PARAB = PAR(1 - e-Kdif 'lai ) (1) where KDIF is the extinction function for visible incoming radiation with the calibrated value of 0.6. The daily assimilate production of the crop (GTWSO1, kgDM ha-1d-1) is dependent on PARAB, RUE, correction factors for temperature, high radiation levels, and atmospheric CO2, and reduction factors for water and N stress (via TRANRF and nitrogen nutrition index NNI). The sum of GTWSO1 and the available amount of reserves (WRE, kgDM ha-1) is labeled as GTWSO2 (kgDM ha-1d-1). The sink limited increase in leaf area (GLAISI, ha ha-1d-1) is calculated from the number of tillers and the leaf elongation rate. The sink limited increase in total biomass (GTWSI, kgDM ha-1d-1) is calculated as GTWSI= GLAISI (2) SLA - (1 - FRT) v ' where SLA (with the calibrated value of 0.0025 ha kg-1DM) is a specific leaf area and 1-FRT (with the calibrated value of 0.8) is the above ground allocation fraction. The actual grass growth may switch between sink and source limited growth limitation. If GTWSO2 > GTWSI, the growth rate (GTW, kgDM ha-1d-1) is equal to GTWSI and the additional amount of assimilates results in an increase in reserves. If GTWSO2 < GTWSI then GTW is equal to GTWSO2. The increase in leaf mass (GLV, kgDM ha-1d-1) is calculated from the total growth rate GTW and the partitioning factor (1-FRT), to determine the mass of green leaves (WLVG, kgDM ha-1). With the FRT factor the roots mass is obtained (WRT, kgDM ha-1). The daily increase in LAI (GLAI, d-1) is simulated as GLAI = GLV - SLA, (3) with SLA as in (2). Furthermore, the relative death rates of the leaves (RDR, d-1) due to N shortage (with NNI < 1; RDRn, d-1) and due to ageing as dependent on the mean daily temperature (RDRtb, d-1), due to shading (with high LAI values; RDRsh, d-1) or due to drought (as dependent on TRANRF; RDRdr, d-1) are determined: RDR = RDRn + max(RDRb, RDRsh, RDRdr ). (4) Next, the death rate of leaves (DLV, kgDM ha-1d-1) is calculated from RDR, followed by the calculation of the mass of the dead leaves (WLVD, kgDM ha-1). The decrease in LAI (DLAI, d-1) is calculated practically in the same way as the leaf death rate. Only to allow regrowth after, for example, a period of severe drought stress, LAI (m2 m-2) remains during the growth period always at least on the value of predefined CLAI. The change in the leaf area (RLAI, d-1) is equal to GLAI minus DLAI 2.4 Herbage DM yield, potential yield and crop efficiency For the calculation of the herbage DM yield (GRASS, kgDM ha-1), the harvestable leaf mass (HRVBL, kgDM ha-1) has to be determined first. It is equal to the green leaf mass in the field (WLVG) minus the leaf mass that remains in the field after SMACT= mowing: HRVBL = WLVG - CLAI SLA (5) where CLAI is the leaf area index after mowing (0.8 m2 m-2) and SLA is as in (2). GRASS increases at every mowing by the value of HRVBL on the mowing day. Potential yield (YIELD, kgDM ha-1) is determined by the equation YIELD = GRASS + HRVBL. (6) For the crop efficiency simulations another variable TADRW (kgDM ha-1) is determined as TADRW = GRASS + WLVG + WLVD. (7) It presents the mass of green and dead leaves in the field together with the herbage DM yield. Radiation use efficiency (RUE, gDM MJ-1PAR) is derived at the end of the growth period from TADRW divided by the total intercepted solar radiation during the growth period. The calculation of water use efficiency (WUE, gDM kg-1water) is similar: at the end of the growth period TADRW is divided by the total water amount used by evapotranspiration during the growth period. 2.5 Water balance LINGRA-N calculates evapotranspiration and water balance in the same way as the WOFOST model (Supit and Van der Goot, 2003). The processes directly affecting the root zone soil moisture content are percolation, surface runoff, infiltration, crop transpiration and soil evaporation. The actual soil moisture content (SMACT, cm3 cm-3) can be established according to Driessen (1986 op. cit. Supit and Van der Goot, 2003): INup + ( INIow - T a ) RD At where the rate of net influx through the upper root zone boundary (INup, cm d-1) is INup = P + Ie - Es - SR (9) and the rate of net influx through the lower root zone boundary (INlow, cm d-1) is INow = - PERC (10) and Ta (cm d-1) is the calculated actual transpiration rate of crop, RD (cm) the calculated actual rooting depth, At the determined time step (1 d), P (cm d-1) input daily precipitations, Ie (cm d-1) from input recalculated effective daily irrigation (not used - it is not a common practice to irrigate grass swards), Es (cm d-1) the calculated soil evaporation rate, SR (cm d-1) the calculated rate of surface runoff and PERC (cm d-1) the calculated percolation rate. The method, introduced by Penman (1956, 1948 op. cit. Supit and Van der Goot, 2003) and adapted according to Choisnel et al. (1992 op. cit. Supit and Van der Goot, 2003), is used for daily totals of canopy transpiration and soil evaporation and is described in Supit and Van der Goot (2003). The reduction of the grass growth rate and the transpiration rate due to drought stress is calculated via: TRANRF= T /T= SMACT- SMW (11) a p SMCR - SMW v У where Ta and SMACT are defined as in (8), Tp (cm d-1) is the potential transpiration rate of crop, SMW (cm3 cm-3) soil moisture content at wilting point and SMCR (cm3 cm-3) critical soil moisture content. SMCR is defined as the quantity of stored soil moisture below which water uptake is impaired and the plant closes its stomata. TRANRF affects RUE and the growth rate of the crop, the leaf death rate and the distribution of assimilates to the roots. 3 RESULTS AND DISCUSSION As previously mentioned, there is great year-to-year variation of grassland herbage DM yields. Coefficient of variation for experimental herbage DM yield data in Jablje is 18 %. For instance, measured annual grassland herbage DM yields in Austria tend to vary within ±10-20 %, but during some years (e.g. 2003) these deviations can be much greater (Schaumberger et al., 2007). In the period 1995-2004, the average coefficient of variation for experimental grassland herbage DM yields in France was about 16 % (Smit et al., 2008). The simulated GRASS (Figure 3) has about the same variability throughout the 50-year period, however, in the second half outliers start to appear, which can be alarming in terms of the negative effect of climate change. Figure 3: Upper: Boxplots of simulated yearly herbage DM yield (GRASS) of cock's foot in Jablje for the first (1964-1988) and the second (1989-2013) half of the 50-year period. Lower: Simulated yearly herbage DM yield (GRASS) of cock's foot in Jablje for the whole period 1964-2013 Slika 3: Zgoraj: Okvirja z ročaji za simuliran letni pridelek suhega zelinja (GRASS) navadne pasje trave v Jabljah v prvi (1964-1988) in drugi (1989-2013) polovici obravnavanega 50-letnega obdobja. Spodaj: Simuliran letni pridelek suhega zelinja (GRASS) navadne pasje trave v Jabljah za celotno obdobje 1964-2013 The biggest reductions in the simulated herbage DM yield are seen in the years 1992, 1993 and 2003 (approximately 4 t ha-1year-1). As it is seen in Figure 2, these are also years with very low precipitation in the summer and in the vegetation period. Only 47 % of average summer precipitation for the period 1964-2013 was measured in 1992, 53 % in 2003 and 59 % in 1993. For the vegetation period proportions were a little higher, 55, 59 and 62 %, respectively. Also, in the years 1992 and 2003 extremely high minimum and maximum daily air temperature averages were recorded for both the summer and the vegetation period. As regards global radiation, it was extremely high in the vegetation period of 2003. Altogether, it is clear that the GRASS reductions were due to drought conditions. Sušnik and Pogačar (2010) studied indicators like the number of dry days and soil moisture deficit to define drought years for grass sward in six locations across Slovenia for the period 19732009, and compared them to drought reports published in Agrometeorological bulletins, which can be found in the archive of the Slovenian Environment Agency. In years 1992, 1993 and 2003 the most intense and the longest droughts were detected in all locations, which correspond to the simulation results. Furthermore, the observed connections led to the testing of YIELD dependence on weather variables. YIELD was used in this case instead of GRASS to avoid a direct influence of the mowing dates on the final result. Among all input weather variables, calculated as the average or sum for the summer and for the vegetation period, there is none linearly related to YIELD. However, it can be again seen (Figure 4) that very low YIELD is connected to very high (maximum) air temperatures and very low precipitation. Smit et al. (2008) claim the grass sward production in Europe to be strongly correlated with the annual precipitation and less with the annual temperature sum or the length of the growth period. On the other hand, the 20-year experiment on permanent grassland in Ljubljana also showed only very small positive correlation between the annual precipitation and the herbage DM yield (Lekšan, 1995). 12000 ta 10000 SZ E 8000 О) * 6000 □ щ 4000 2000 о 12000 -10000 ta 8000 § 6000 g 4000 ш >= 2000 0 22 24 26 28 Maximum daily air temperature ( С) 30 300 500 700 900 Precipitation (mm) 1100 Figure 4: Scatterplots of the potential yield (YIELD) versus the summer average of maximum daily air temperature (left) and YIELD versus the vegetation period sum of precipitation (right) for cock's foot in Jablje for the whole period 1964-2013 Slika 4: Razsevna diagrama, ki prikazujeta potencialni pridelek (YIELD) v odvisnosti od poletnega povprečja maksimalne dnevne temperature zraka (levo) in v odvisnosti od količine padavin v vegetacijskem obdobju (desno) za navadno pasjo travo v Jabljah za celotno obdobje 1964-2013 The given years with the lowest GRASS were also the years with the lowest TRANRF (Figure 5). As TRANRF is the model's measure of drought conditions, these were detected as the driest years in the simulation. Also, in the years 1971, 1983, 1994, 2001, 2006, 2007, 2011, 2012 and 2013 TRANRF fell under 0.95, denoting dry years. Figure 5: Simulated reduction factor for crop growth due to drought (TRANRF) for cock's foot in Jablje for the whole period 1964-2013 Slika 5: Simuliran faktor zmanjšanja rasti zaradi suše (TRANRF) navadne pasje trave v Jabljah za celotno obdobje 1964-2013 Smit et al. (2008) also claim that are herbage DM yields especially affected by droughts. Also similar as in our case, in Ireland, herbage DM yield reductions of 1.4 to 4.0 t ha-1year-1 have been estimated to be lost for intensively managed grassland in the driest regions due to limiting soil moisture availability (Brereton and Keane, 1982 op. cit. Laidlaw, 2009). Drought stress has a major influence on RUE (Bonesmo and Belanger, 2002). This can be seen in Jablje as the course of RUE is very similar to the course of TRANRF (Figure 6). For RUE versus TRANRF (not presented) the coefficient of determination is r2 = 0.84, which means that 84% of RUE variability can be explained with the changing TRANRF. Figure 6: Simulated radiation use efficiency (RUE) of cock's foot in Jablje for the whole period 1964-2013 Slika 6: Simulirana učinkovitost izrabe sončnega obsevanja (RUE) navadne pasje trave v Jabljah za celotno obdobje 1964-2013 Water status can be also monitored as actual soil moisture content on a daily scale with variable SMACT. Figure 7 (upper right) shows a pattern of SMACT in the dry year of 1993 and in the average year of 1994. In 1993 SMACT stayed on a very low level from the beginning of May to the end of the August, while in 1994 it only fell to this level twice in the whole year. This is reflected very strongly in other variables. YIELD (Figure 7, upper left) was not increasing at all in the dry period of 1993, the same happened in 2003. In contrast, for example in the years 1994 and 2010 YIELD was increasing almost steadily throughout the vegetation period, only a little more slowly in the summer time. Naturally, YIELD depends on LAI (Figure 7, lower left), which remained under 2 m2 m-2 during the dry period of 1993. In 1994 LAI was below this value just at the beginning and at the end of the year, and on mowing days (four extreme falls of LAI can be seen). Otherwise it rose as high as 5 to 9 m2 m-2. Cumulative PARAB in Jablje was 1100 MJPAR m-2year-1 in the dry year of 1993, which is 53 % of PAR, and 1650 MJpar m-2year-1 in 1994, which is 75 % of PAR (Figure 7, lower right). For example, in the research of Wolf (2006), who made simulations of rye grass growth with LINGRA for five years for optimal water and nutrient supply, YIELD appears to increase from Wageningen (The Netherlands) to Bologna (Italy) to Sevilla (Spain). He claims this was caused by the length of the growing season and by cumulative PARAB, which increased for the three locations from 1200-1600 MJpar m-2year-1 to 1700-2000 MJpar m-2year-1 and 2700-2800 MJpar m-2year-1, respectively. 0.4 СЧ CD CD CD CD О CM СЧСМСЧСЧСЧПППП day of year 10 _ 7 È e 1 5 < 4 3 2 1 0 0 35 ST- 0.3 È O 0.25 E C_J 0 2 1— 0 < 0.15 S 0.1 то 0.05 0 ■ 1993 -1994 смч-щсоогчч-сссоосм ^ ^ t- ^ т- CN day of year -P ARAB 1993 ---PAR 1993 -P ARAB 1994 ---PAR 1994 day of year day of year Figure 7: Simulated potential yield (YIELD, upper left), soil moisture content (SMACT, upper right), leaf area index (LAI, lower left), cumulative amount of photosynthetically active radiation (PAR) and cumulative amount of PAR as intercepted by the crop canopy (PARAB) (lower right) of cock's foot in Jablje in the dry year of 1993 and the average year of 1994 (YIELD also in 2003 and 2010) Slika 7: Simuliran potencialni pridelek (YIELD, zgoraj levo), vsebnost vode v tleh (SMACT, zgoraj desno), indeks listne površine (LAI, spodaj levo) ter kumulativno fotosintetsko aktivno sevanje (PAR) in prestreženo fotosintetsko aktivno sevanje (PARAB) (spodaj desno) za navadno pasjo travo v Jabljah za suho leto 1993 in povprečno leto 1994 (YIELD tudi za leti 2003 in 2010) According to Wolf (2006), the increase in PARAB results in a higher YIELD and in a much higher WLVD, because the higher biomass production results on average in a higher LAI and thus in more leaf senescence due to self-shading. The same can be said for the simulations in Jablje (Figure 7, Figure 8). Figure 8: Simulated mass of green leaves (WLVG), mass of dead leaves (WLVD) and roots mass (WRT) of cock's foot in Jablje in the dry year 1993 (left) and in the average year of 1994 (right) Slika 8: Simulirana masa zelenih listov (WLVG), masa odmrlih listov (WLVD) in masa korenin (WRT) navadne pasje trave v Jabljah v suhem letu 1993 (levo) in v povprečnem letu 1994 (desno) As expected from the definition, the shape of the WLVG curve is the same as the shape of the LAI curve, due to constant SLA. In 1993, during the long summer drought WLVG was almost 0 all the time, so two intermediate mowings cannot be seen (Figure 8, left). On the other hand, four mowings are clearly seen in four extreme decreases of WLVG in 1994 (Figure 8, right). Because of the drought, roots also grew very slowly in 1993 and at the end of the growth period reached only half of the WRT that was reached at the end of 1994. What is more, the mass of dead leaves (WLVD) in 1993 was only 44 % of the WLVD in 1994, due to low available green biomass. 4 CONCLUSIONS Fundamentally, this research shows the value of applying the calibrated LINGRA-N model for a 50-year (1964-2013) herbage yield simulation and growth analysis. It provides insights in the interactions between several weather and crop variables or their seasonal development and herbage yield variability. It is important to have an opportunity to better understand the growth components, and simulations can reveal their dynamics and impacts on herbage yield, based on weather and soil conditions. Overall, crop models are a very useful and important tool for this kind of research. As regards the simulated herbage DM yield (GRASS), recent changes in its variability are reflected in the appearance of outliers in the second half of the study period. The biggest reductions in GRASS were detected in the years 1992, 1993 and 2003. These years were also recognised as years with very low precipitation and very high minimum and maximum daily air temperature averages in the summer and in the vegetation period, so we were able to conclude that the GRASS reductions were due to drought conditions. The given years with the lowest GRASS were also the years with the lowest reduction factor for crop growth due to drought (TRANRF). As the latter is the model's measure of drought conditions, these were detected as the driest years in the simulation, too. Radiation use efficiency variability was strongly dependent on TRANRF. Drought had a major impact on the cumulative amount of PAR as intercepted by the crop canopy (PARAB), which reached just 53 % of PAR in the dry year of 1993. Seasonal development of the actual soil moisture content (SMACT) was linked to the development of the leaf area index and consequently to the mass of green leaves, to the roots mass, to the mass of dead leaves and to GRASS. However, some of the obtained results remain indicative without confirmation of the simulated values through field measurements. Angulo et al. (2013) also recommend that future work should focus on obtaining more comprehensive, high quality data allowing application of improved methods for model calibration. For modelling it would be of great importance to plan grassland field experiments multiple years in advance that would, in addition to measurements of herbage yield, include measurements of variables or parameters like leaf area index, specific leaf area, leaf appearance rate, tiller density or mass of green leaves. Measurements of soil moisture content would also be useful. Further important factors include the vicinity of the meteorological station, the availability of soil data and, possibly, swards to be one to two years old. Naturally, this would be a major project with a great need of financial support. The results highlight the need for further research, on field and with simulations. As regards the latter, we have to keep in mind that they inevitably involve various uncertainties. These uncertainties originate from input (meteorological, soil, management) data, from calibrated (for a specific period) model parameters, from model structure and concept. In order to identify potential problems caused by seasonal weather variability, which is increasing due to climate change, and to objectively assess its impact on the grassland production, it is necessary to perform various different simulations. For Slovenia, it would be of greater importance to make such simulations for permanent grasslands, but as for now the calibration has not been successful (Pogačar et al., 2015) we need to first obtain results for various grass monocultures and various locations, and try to proceed from there. 5 REFERENCES ARSO. 2014. Slovenian Environment Agency (http://www.arso.gov.si/): Climatological data -database output Angulo C., Rötter R., Lock R., Enders A., Fronzek S., Ewert F. 2013. Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe. Agricultural and Forest Meteorology, 170: 32-46, doi: 10.1016/j.agrformet.2012.11.017 Barrett P.D., Laidlaw A.S., Mayne C.S. 2005. GrazeGro: a European herbage growth model to predict pasture production in perennial ryegrass swards for decision support. European Journal of Agronomy, 23: 37-56, doi: 10.1016/j.eja.2004.09.006 Bonesmo H., Belanger G. 2002. Timothy yield and nutritive value by the CATIMO model; I. Growth and nitrogen. Agronomy Journal, 94: 337-345, doi: 10.2134/agronj2002.0337 Ceglar A., Kajfež-Bogataj L. 2012. Simulation of maize yield in current and changed climatic conditions: addressing modelling uncertainties and the importance of bias correction in climate model simulations. European Journal of Agronomy, 37, 1: 83-95, doi: 10.1016/j.eja.2011.11.005 Čop J. 1992. Sezonska razporeditev rasti zelinja štirih vrst trav avtohtonega izvora v predalpskem območju Slovenije. Master thesis. Ljubljana, University of Ljubljana, Biotechnical Faculty, Department for Agronomy: 82 p. Dolničar J. 2013. Poznavanje travne ruše za gospodarno pridelovanje krme. Glas dežele, junij 2013. http://www.glasdezele.si/articles/2013/poznavanje-travne-ru%C5%A1e-za-gospodarno-pridelovanje-krme (16. 10. 2013) KIS. 2014. Agricultural Institute of Slovenia (http://www.kis.si/): herbage yield data of grass monocultures - database output Laidlaw A.S. 2009. The effect of soil moisture content on leaf extension rate and yield of perennial ryegrass. Irish journal of agricultural and food research, 48: 1-20 Lambert R., Peeters A., Toussaint B. 1999. LAI evolution of a perennial ryegrass crop estimated from the sum of temperatures in spring time. Agricultural and Forest Meteorology, 97: 1-8, doi: 10.1016/S0168-1923(99)00059-3 Lekšan D. 1995. Vpliv vremena na pridelek različno gnojenega travnika. Graduation thesis. Ljubljana, University of Ljubljana, Biotechnical Faculty, Department for Agronomy: 34 p. Pogačar T., Ipavec D., Verbič J., Kajfež-Bogataj L. 2015. Calibration of the LINGRA-N model to simulate herbage yield of grass monocultures and permanent grassland in Slovenia. Acta agriculturae Slovenica, 105, 1: 111-123, doi: 10.14720/aas.2015.105.1.12 Prihodnje spremembe podnebja v Sloveniji. 2014. Ljubljana, Ministry of the environment and spatial planning, Slovenian environment agency: 3 p. http://meteo. arso .gov.si/uploads/probase/www/clim ate/PSS/scenariji/podnebni_scenariji.pdf (21. 5. 2015) Schaumberger A., Trnka M., Eitzinger J., Formayer H., Bartelme N. 2007. Agrometeorological monitoring of Austrian grasslands using GIS based modeling. Geophysical Research Abstracts, 9, poster: 3 p. http://meetings.copernicus.org/www.cosis.net/abstr acts/EGU2007/10449/EGU2007-J-10449.pdf (20. 1. 2014) Smit H.J., Metzger M.J., Ewert F. 2008. Spatial distribution of grassland productivity and land use in Europe. Agricultural Systems, 98: 208-219, doi: 10.1016/j.agsy.2008.07.004 Supit I., Van der Goot E. (eds.). 2003. Updated system description of the WOFOST crop growth simulation model as implemented in the CGMS applied by the European Commission. Joint Research Centre of the European Commission, Luxembourg: http://www.treemail.nl/download/treebook7/index.h tm Sušnik A. 2006. Vodni primanjkljaj v Sloveniji in možni vplivi podnebnih sprememb. Master thesis. Ljubljana, University of Ljubljana, Biotechnical Faculty, Department for Agronomy: 147 p. Sušnik A., Pogačar T. 2010. Modeliranje vodne bilance travinja kot orodje pri analizi suše v obdobju 19732009. In: Novi izzivi v poljedelstvu 2010. Rogaška Slatina, 2.-3. 12. 2010. Kocjan Ačko D., Čeh B. (eds.). Ljubljana, Slovensko agronomsko društvo: 299-306 Tajnšek A. 2003. Deset let trajnih poskusov IOSDV v Sloveniji, Jable in Rakičan 1993-2003. In: Namen in cilj trajnih poljskih poskusov IOSDV Jable in IOSDV Rakičan. Žalec, 12. 12. 2003. Tajnšek A., Čeh Brežnik B., Kocjan Ačko D. (eds.). Proceedings of the conference, Slovensko agronomsko društvo: 7-24 Tehnološka priporočila za zmanjšanje občutljivosti kmetijske pridelave na sušo: poljedelstvo, travništvo, zelenjadarstvo in hmeljarstvo. 2008. Ljubljana, Ministry of Agriculture, Forestry and Food: 44 p. http://www.arsktrp.gov.si/fileadmin/arsktrp.gov.si/p ageuploads/Aktualno/Aktualno/2013/Tehnoloska_p riporocila_za_zmanjsanje_obcutlj ivosti_na_suso.pd f (18. 11. 2013) Trnka M., Eitzinger J., Gruszczynsk G., Buchgraber K., Resch R., Schaumberger A. 2006. A simple statistical model for predicting herbage production from permanent grassland. Grass and forage science, 61: 253-271, doi: 10.1111/j.1365-2494.2006.00530.x Willmott C.J. 1982. Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63: 1309-1313, doi: 10.1175/1520- 0477(1982)063<1309:SC0TE0>2.0.C0;2 Wolf J. 2006. Grassland data from PASK study and testing of LINGRA in CGMS. ASEMARS Project report no. 2. Wageningen, Alterra: 38 p. http://models.pps.wur.nl/sites/models.pps.wur.nl/fil es/LINGRA-PASK_report_Wolf-2006.pdf (8. 1. 2010) Wolf J. 2012. LINGRA-N: Simple generic model for simulation of grass growth under potential, water limited and nitrogen limited conditions. User guide for LINGRA-N. Wageningen, Wageningen University: 65 p. http://www.wageningenur.nl/en/Publication-details.htm?publicationId=publication-way-343434373232 (28. 3. 2013) COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.12 Agrovoc descriptors: soybeans, glycine max, weed control, Abutilon theophrasti, spacing, population dynamics, seed production, biological comptition Agris category code: h01, h60, f03 Study of relationship between soybean (Glycine max (L.) Merr.)planting spatial arrangements and velvetleaf (Abutilon theophrasti L.) population dynamic Hamid SALEHIAN1*, Maryam NAJAFIAN1 Received July 20, 2015; accepted September 02, 2015. Delo je prispelo 20. julija 2015, sprejeto 02. septembra 2015. ABSTRACT IZVLEČEK The velvetleaf is an important annual weed in the Mazandaran province, Iran. Seeds are the only way of propagation and renewal of this weed. More knowledge was gained regarding soil seed bank and its seed production to improve the management of the velvetleaf weed in the future. There is a minimal information concerning the impact of the soybean planting pattern on the dynamics of the velvetleaf population. For this reason two different fields have been studied with the cooperation of the Agriculture Discipline of the Islamic Azad University, in Qaemshahr, Iran, during 2009 and 2012. In this study the effect of two types of soybean row spacing were used, 50 cm-wide and 36 cm - narrow, and three emergences of the velvetleaf weed population (periods 0-10, 10-20 and 2030 days after soybean sowing were implemented) were studied. Seed production, leaf area and dry matter increased in each plant population of the velvetleaf weed in the 50-cm soybean rows. Mortality rates were decreased in velvetleafs seedling population in the wider spaced rows. By observation it was seen an increased production of seeds in the first batch of seedlings. It appears that we must remove the first weed emergence flushes within three to four weeks after the soybean emergence to prevent reduced yields in the soybean crop and further increase of the velvetleaf seed bank. Key words: row spacing, cohort, velvetleaf, soybean PREUČEVANJE RAZMERJA MED PROSTORSKO UREDITVIJO SETVE SOJE (Glycine max (L.) Merr.) IN POPULACIJSKO DINAMIKO BRŽUNASTEGA OSLEZOVCA (Abutilon theophrasti L.) Bržunasti oslezovec je pomemben enoletni plevel v provinci Mazandaran, Iran. Njegovo razmnoževanje je izključno s semeni. V raziskavi so bila pridobljena nova spoznanja o semenski banki in produkciji semena za izboljšanje uravnavanja bržunastega oslezovca v bodoče. Malo je informacij, ki se nanašajo na vpliv načina setve soje na dinamiko polpulacij bržunastega oslezovca. V ta namen sta bili v sodelovanju z Agriculture Discipline of the Islamic Azad University, Qaemshahr, Iran, v letih 2009 in 2012 preučevani dve polji, na katerih sta bila preučevana načina setve soje v vrstah s širšim razmikom, 50 cm, in v vrstah z ožjim razmikom, 36 cm, na vznik populacij bržunastega oslezovca v treh različnih obdobjih po setvi soje (0-10, 10-20 in 20-30 dni). Produkcija semena, listna površina in vsebnost suhe snovi so se povečali v vsaki naslednji populaciji bržunastega oslezovca pri setvi soje v vrstah s širšim, 50 cm razmikom. Mortaliteta kalic bržunastega oslezovca se je pri tem načinu setve soje iz populacije v populacijo zmajševala. Pri tem smo opazili povečano produkcijo semena rastlin bržunstega oslezovca, ki so vzkalile v prvem obdobju po setvi soje. Iz tega lahko zaključimo, da je potrebno zatiranje plevelov v prvem obdobju po setvi soje, to je v treh do štirih tednih po vzniku soje, če hočemo preprečiti zmanjšanje pridelka soje in nadaljne povečevanje semena bržunastega oslezovca v semenski banki. Neupoštevanje širine razmika med vrstami pri setvi soje kaže na pomen tega dejavnika pri uravnavanju populacij te plevelne vrste. Ključne besede: razporeditev vrst setve, kohorte, bržunasti oslezovec, soja Department of Weed Science. Faculty of Agriculture and Natural Resources, Islamic Azad University, Qaemshahr Branch, Iran; Email hamisalehian@gmail.com as correspondence 1 INTRODUCTION Several new methods and technologies were used to reduce the population of the weed to adequate levels. However for preserving the existing environment and other natural resources it is essential the use of various methods and techniques such as integrated weed management control (IWM). The purpose of this method in this part is to reduce our reliance on chemical weed control which can be accomplish through development and utilization of integrated weed management (IWM) as well as integrating other preventive measures (Knezevic and Horak, 1998). Integrated weed management (IWM) emphasizes the health of the product, and a crucial understanding of this method and its accurate application (Swanton et al., 2008). This approach has demonstrated the relevance and importance of weed mortality and decline of the weeds fitness (Williams et al., 1998). It is a combination of various methods by cultural, chemical and mechanical means (Swanton et al., 2008) as well as agronomical operations which also play a vital role (Pylon et al., 1997; Hock et al., 2005). Articles on the timing and placement of fertilizer, seeding rate and reducing crop row spacing have been studied and reported by Walker and Buchanan, (1982). Planting the soybean with a smaller distance between the plant rows leads to acceleration in canopy closure thus increasing its relative competitiveness and weed suppression particularly in the final weed cohorts (Knezevic et al., 2003b; Mickelson and Renner, 1997; Mulugeta and Boerboom, 2000; Nice et al., 2001; Yelverton and Coble, 1991; Yong et al., 2001). Knezevic et al (2003 a, b) demonstrated in his study that with decrease in row spacing of the soybean the toleration of the crop was increased to constrain the weed competition at the onset of the season. The critical weed free period was delayed and in general severity of weed damage declined. Other studies have shown that by increasing the plant dry mass, the seed production per bush were increased (Martens and Jansen, 2002; Thompson et al., 1991; Samson and Werk, 1986). Therefore, it can be purposed that the crop planting pattern affects the production ability of velvetleaf seed. It is insufficient research regarding the influence of the planting pattern on the velvetleaf seed production. Effective, logical and long term weed management is based on the constant reduction of weeds' population and seed bank density. One of the most important factors in this area is to minimize seed production per plant. This result has been done by reduction of weed density or by mean of diminishing the seed production. Process of emergence is a critical event in the life cycle of the velvetleaf weed (Forcella et al., 2000). Period of weed emergence and dynamics of weed emergence flushes play a critical role on loss of the crop yield (O'Donovan et al., 1985; Swanton et al., 2008). The growth of the velvetleaf seedlings which emerge at the beginning of the season is often compared with the later ones. The seedlings developed in the early part of the season demonstrate more competitiveness, produce a higher biomass and number of seeds, and furthermore have added impact on the crops' yield ability (Massinga et al., 2001; Norsworthy et al., 2007; Steckel and Sprague, 2004). The low competitiveness of the seedlings which emerge later in the season is mainly due to the interspecies competition and their mortality rate under the canopy. This was noted to occur most likely in the dense row spacing and it was as a consequence of shading by crop (Buehring et al., 2002; Norsworthy et al., 2007). For the future success and development of integrated weed management (IWM), further biological studies of the various weeds inhibiting the soybean culture is necessary. Velvetleaf is a serious and troublesome weed of the soybean in the north of Iran and a global dilemma (Shafigh et al., 2006; Rezvani et al., 2008; Sadeghi et al., 2003; Warwick and Blank, 1988; Hock et al., 2005; Zeinali and Ehteshami 2003). The majority of the velvetleaf seedlings sprouted at the beginning of the season and some emerged mid-season (Egley and Williams, 1991). Velvetleaf seedlings are able to complete their life cycle in the crop canopy (Mitch, 1991) and can produce as much as 17000 seeds per plant (Warwick and Black, 1988). The goal of this study is to see the interactions between the various velvetleaf cohorts during (0- 10, 10-20, and 20-30 days after crop planting) in cm row spacing). the disparate soybean planting patterns (36 and 50- 2 MATERIAL AND METHODS This experiment has been done in the scientific-research fields of the Islamic Azad University in Qaemshahr, Iran; formatted and randomized in complete block design, in three replications in the two season crops of 2009 and 2012. Treatments for this study were different planting patterns in the soybean culture. Soybean seeds were planted in two different row spacing in order to achieve a 45 plants per m-2 on 15 April 2009 and 18 April 2012. At the first plant-group, the distance between rows was 36 cm (narrow spaces) and the seedlings intervals were 6 cm in the rows and in the second plant-group the distances between rows were 50 cm (wide spaces) and 4 cm intervals between the seedlings in the row, respectively. The soybean seeds ('JK' variety) were disinfected with Benomyl fungicide (2000 ppm), and then planted at a depth of 2 cm. A segment of the university's research-field was selected which was known to be positive for contamination of the velvetleaf seed. Experimental units were 7 m long and 3.2 m up to 4.5 m wide with 10 rows. The field was tillaged twice (the autumn in previous year and prior to planting after the next year). According to the soil tests there were no need to apply potassium (K2O), however, phosphorus (P2O5) and nitrogen (urea) fertilizers were used at 80 kg h-1 and 5 kg h-1, respectively. By Auger, five soil samples were taken from each plot, prior to sowing the soybean seeds, the diameter and depth of each sample was 6 cm and 10 cm, respectively. The purpose of these samples were to confirm the presence and removal of the velvetleaf seeds (Abutilon theophrasti Medik), all samples were taken to the university laboratory. Soil samples were put into plastic bowls which contained potassium hexametaphosphate (5 %), then were mixed with distilled water disintegrating soil structures, then the solution of soil solid particles was filtered through a sieves of 1 mm diameter, at last following confirmation and identification of the velvetleaf seeds, the seeds were collected. Subsequent to counting the seeds in the augered sectioned areas, the seeds' density per unit soil surface was estimated. For recording and sampling during the growth season two quadrats, 1m * 1m, were selected in the center of each plot. For determination of the effects of the velvetleaf seedlings emergence stages their appearance were divided into three cohorts: zero to 10, 10 to 20 and 20 up 30 days after soybean sowing. Calculations for the number of seed per unit soil volume and surface, rate of recruitment was measured. The seedling mortality was also calculated in the form of percentage. The other undesirable weeds were controlled by hand-hoeing. Developmental stages were based on the number of fully expanded leaves per plant (Fehr and Cavines, 1977). Velvetleaf bushes were clipped at the soil surface, divided into 40 - cm segments, then leaves, stems and capsules were separated from each other at physiological maturity of the soybean. The leaf area (LA) of the velvetleaf was measured with a leaf area meter (LTD AM 200). Different plant components were then dried at 80 C° in the oven (Memmert DIM 40050) and weighed. Seeds that had scattered on the ground before or at the final harvest were not collected, and seeds losses were not estimated. Analysis of variance was performed using PROC MIXED (SAS, 1999) to test data normality and significance (P < 0.05) of growing scenario, soybean row spacing and velvetleaf relative emergence. 3 RESULTS AND DISCUSSION The average number of velvetleaf seed in the soil was 943 and 991 seeds m-2 at the 2009 and 2012, respectively. This amount was in agreement with other studies (Lindquist et al., 1995; Munger et al., 1987). This result could have risen from the intense contamination of soil with this weed or was caused by a lack of continual crop planting. Initially, the rate of the velvetleaf seedlings emergence cannot be influenced by a soybean planting pattern. Differences in the velvetleaf seedlings emergence in two different rows spacing's can be related to their content on the weed seed bank (Table 1). The mean of the velvetleaf seed density during two years of study in the soil seed bank in wide and narrows rows were 1215 and 720 seed per m-2.Therefore higher number of velvetleaf seedlings in wider rows soybean planting appears to be a logical outcome. The lack of necessity to light for velvetleaf seed germination may explain this result (Bello et al., 1995). Table 1: Velvetleaf seed rate in seed bank, emergence seedlings density and recruitment percentage in various soybean row spacing for 2009 and 20121 Year Seed bank (sb) (seed/m2) Row spacing (cm) Seedling density (sd) (p/m2) Row spacing (cm) Recruitment sd/sbx100 Row spacing (cm) 36 50 36 50 36 50 2009 2012 708 732 1179 1251 10 12 22 25 1.4 1.6 1.8 2.0 1- Within a row the same letter indicates that the values did not differ significantly by LSD test, according to P=0.05 Velvetleaf population recruitment was insignificant regarding planting pattern (averaging 26 %, Table 1). In comparison with other experiments our study gave results with smaller values of this parameter (Puricelli et al., 2002). Lindquist et al (1995) also found this consistency in his study. This information can be used to predict the approximate amount of emergence percentage from the weed seed bank. Of course, in the majority of weed species more differences are recorded between the content in weed seed bank and emerging seedlings (Forcella et al., 1997). These variations maybe caused by the sizes of the sampling areas or the time of samplings (Derksen and Watson, 1998). The rate of the velvetleaf seedlings mortality was lower in the wide-rows (Table 2). Despite slower growth of velvetleaf seedlings in the narrow rows, they were able to survive relative to their condition (higher in the second cohort). Puricelli et al (2002), in his study regarding the interference between Anoda cristatae L. and the soybean, reported similar results. However, Scursoni et al (1999) observed mortality of Avena fatua L. plants in the densest stands of barley, due to the acceleration in the canopy closure. Nonetheless, in this study, further delay in the emergence of the velvetleaf population relative to the soybean caused the decrease in their survival. High survival of early cohorts of velvetleaf seedlings in both row spacing of soybean indicated important role on information of their soil seeds bank. Observation of the velvetleaf seedling population in the last cohorts, during the soybean harvest it has shown that they did not survive. Therefore it was noted that the control measures must be predominantly focused on the removal of the early cohorts. Therefore the results were demonstrated that the loss of the soybean yield was a result of the competition with the first cohorts of velvetleaf seedlings (Cowan et al., 1998; Dielman et al., 1996; Steckel and Sprague, 2004). Researches have showed that velvetleaf plants which emerged 35 days after soybean planting did not decrease crop yield significantly (Zimdahl, 1988). This indicates the importance of time of velvetleaf seedlings emergence for their survival (Hock et al, 2005), the same was proved also for Digitaria sanguinalis (L.). (Gallart et al, 2010; Oreja and dela Funte. 2005) and some other weed species (Lindquist et al., 1995). Table 2: Emerged seedlings number, mortality and survival percentage of velvetleaf in cohorts and planting patterns for 2009 and 2012 ! Emerged seedling number (p/m2) Mortality (%) Survival (%) Year Cohorts row spacing row spacing row spacing 36 cm 50 cm 36 cm 50 cm 36 cm 50 cm 2009 1 5 b1 14 c 43 c 40 c 57 c 60 c 2 3 a 5 b 60 b 66 b 40 b 34 b 3 2 a 3 a 100 a 100 a 0 a 0 a 2012 1 7 c 18 c 40 c 37 c 60 c 63 c 2 4 b 9 b 51 b 60 b 49 b 40 b 3 2 a 4 a 98 a 100 a 2 a 0 a 1-It means emergence date of velvetleaf at 10 th intervals after soybean planting (for details refer to the text in table 3) 2-Within a top column, the same letter indicates that the values did not differ significantly by LSD test, according to P=0.05 Dry matter accumulation in the velvetleaf population was affected by the planting pattern (Table 3). The velvetleaf populations benefited more in their biomass in the wide soybean row spacing. Seedlings that emerged in the first cohort in 50-cm row generated almost four times higher plants with respect to the second cohort. Similarly the velvetleaf populations in the narrow soybean row spacing as with the first cohort in comparison with the second cohort had 200 % more dry matter. Overall the seedlings that were emerged earlier produced additional biomass. These outcomes were confirmed by the findings of Massinga et al. 2001, Puricelli et al. 2002 and Hock et al., 2005. Leaf areas of velvetleaf plants accumulated in the third and fourth layer 77 % and 71 % for the 50-cm-row and 36-cm-row soybean respectively, an average in both years. The highest leaf accumulation area in the upper strata's of the velvetleaf canopies indicates higher efficiency in competition for intercepting the light in comparison with the soybean. Other experiments have reported similar reactions during mixed culture between soybean with velvetleaf (Heindl and Burn, 1983; Hock et al., 2005) and the redroot pigweed (Legere and Schreiber, 1989). Hock et al (2005) reported that velvetleaf population had low leaf area in the lower layers when it was located with soybean in mixed cultures. Table 3: Velvetleaf seed production and plant dry mass in cohorts at different planting patterns different for 2009 and 2012 season Row Emergence date Leaf stage Seed number Plant dry mass Year spacing of velvetleaf of soybean per plant (g) 2009 36 May 15 May 25 VE 1098 (143) 18.4 May 26 Jun 4 V1 509 (143) 9.6 Jun 5 Jun 14 V2 0 0 50 May 15 May 25 VE 2372 (143) 39.96 May 26 Jun 4 V1 683 (143) 10.0 2012 Jun 5 Jun 14 V2 0 0 36 May 19 May 29 VE 716 (26) 17.9 May 30 Jun 9 V1 264 (29) 6.6 Jun 10 Jun 19 V2 0 0 50 May 19 May 29 Ve 1881 (169) 37.6 May 30 Jun 9 V1 527 (47) 7.9 Jun 10 Jun 19 V2 90 (8) 0 1- Standard error based on least square means (P=0.05) The velvetleaf leaf area was influenced by the soybean-planting pattern and its' relative time of emergence (P < 0.05) (Figure 1). Leaf area of velvetleaf plants within the soybean showed more reduction in 36-cm-row planting at the second cohort. In the narrow-row spacing on average in both years the leaf area of velvetleaf population in the first and second cohort were reduced up to 24 % and 30 %, respectively. With a further-decline of the leaf area in 36-cm-row; expressing further competition for the light, more so in the second cohort. The time of emergence plays an important part in the velvetleaf seedlings survival, in so far as those emerging early produced a higher seed population and increased further soil seed banks, as illustrated in Table 3. The variations are demonstrated and can be justified by the unsymmetrical competition for plants in different cohorts (Schwinning and Weiner, 1998). Thus, the bushes which were emerged early had a longer growing period and also were larger. Hock et al (2005) and Gallart et al (2010) demonstrated the importance of time emergence for seed production in velvetleaf and orchard grass weed populations. Thus the dynamics of the seed bank can be influenced by each cohort and were resulted in producing seeds with different dormancy's and reactions of their environmental conditions (Baskin and Baskin, 2001). Seed production in the velvetleaf populations were reduced in the narrow-row spacing and due to their delayed time of emergences (Table 3). Seedlings that emerged in the first cohort in wide rows generated twice the amount of seeds on each of the plants. These differences were smaller in the later cohorts. Furthermore, the seed production in different flushes in the wide rows had a higher variance. The competition for light accounts for the decline in seed productions (Puricelli et al., 2002; Buehring et al., 2002; Benvenuti et al., 1994). It appears that the first flushes must be removed to prevent further weed population from the seed banks, and planting pattern of the crops should be considered as well. For both soybean planting patterns an increase in weed mass were observed, with the increase of dry matter in each plant, seed production was raised (Figure 2). For this reason the mean of seed numbers in the remaining plants at the end of the seasons' growth for the first flush were measured. Higher seed production in each velvetleaf bush in the wide-rows can be correlated to the differences in biomass and percentage of mortality in both planting patterns. It was used a simplest linear model for calculation of the seed productions where the independent variable was the weight of each plant (Mertens and Jansen, 2002). Intercept of regression model for seed production was increased when seedling size rose, this situation was seen in the wide-rows. For this reason the number was 181 in the wide rows spacing (as it was compared to 102 in narrow-rows). Similar trends were seen during various other studies, such as the effect different row spacing's for wheat on the seed production in a three weed species study (Mertens and Jansen, 2002). The treatments in this study demonstrated that the narrow - row spacing resulted in less seed production and bigger seedling mortality. Dry matter and seed production was estimated for each plant (as an alternative of per area unit). This method has some advantages. At first, it revealed the weed community increase or decrease. Moreover, the velvetleaf population had no even distribution in the field. Therefore we should not compare our results on the dry matter and seed density of velvetleaf with those obtained per unit area, the comparisons would have been incorrect. Year 2009 2012 2009 2012 Soybean row spacing 50 cm 36 cm Velvetleaf Emerg Cohort 1 □ Total Plant LA (cm2) Velvetleaf Emerg Cohort 2 1971.6 210 1.5 1 0 2 121 1 0 1 12 1209 □ 401 1150 640 □ 324 □ 410 0.1 □ 253 1 0 0 D 180 1 0 1158 195 1813 140 1.7 2 13 203 181 155 137 689 143 Total Plant LA (cm2) 216 201 141.7 146 0 0 0 0 4 0 0 0 2 6 3 0 0 0 0 0 0 0 0 Figure 1: Velvetleaf leaf area (LA) distribution at soybean maturity for years 2009 and 2012 as influenced by crop row spacing and time of velvetleaf emergence in velvetle af-soybean plots. Each rectangle represents a 40 - cm height increment. Total LA is shown at the bottom each symbolic plant. This study emphasizes the importance of integrated weed management through the method of weed emergence control time and using an inexpensive planting patterns. Furthermore, the data on leaf area, total of dry matter and seed production also suggested the greater need for control of early emerging rather than late-emerging velvetleaf of populations. Ì d Plant dry mass (g) Figure 2: Relationship between the number of seeds produced by velvetleaf plant and plant dry mass in various soybean planting patterns for years 2009 and 2012 4 CONCLUSIONS A long term integrated weed management plan should be considered for early control of the velvetleaf population rather than the late-emerging population. The data collected in this study on the leaf area, total dry matter and seed production confirm the need for better control techniques of the velvetleaf population. Furthermore, this study has demonstrated a necessity for further studies and research for successful results such as reduction and effective control of the weed seed stocks in the soil. These methods and techniques would not degrade the environment, quality of the land or agricultural crops and most of all it is very important their cost effect. 5 REFERENCES Baskin C.C., Baskin J.M. 2001. Seeds: Ecology, Biogeography and Evolution of Dormancy and Germination. Academic Press, Sandi ego. Bello I.A., Owen M.D.K., Valenti H.M.H. 1995. Effect of shade on Velvetleaf (Abutilon theophrasti) growth, seed production, and dormancy. Weed Technology, 3:452-45 Benvenuti M., Macchia S., Stefani A. 1994. Effects of shade on reproduction and some morphological characteristics of Abutilon theophrasti medicus, Dutura stramonium L. and Sorghum halepense L.pers.s. Weed Research, 34:283-288; DOI: 10.1111/j. 1365-3180.1994.tb01996.x Buehring N.W., Nice G.R.W., Shaw D.R. 2002. Sicklepod (Senna obtusifolia) control and soybean (Glycine max) response to soybean row spacing and population in three weed management systems. Weed Technology, 16: 131-141; DOI: 10.1614/0890-037X (2002)016 Cowan P, Weaver S.E., Swanton C.J.1998 .Interference between pigweed (Amaranthus spp.), and Barnyard grass (Echinochloa crus-galli) and Soybean (Glycine max). Weed Science, 46:539-533; DOI: 10.1614/WS-03-004R Derksen D.A., Watson D.R. 1998. Weed community composition in seed banks ,seedlings, and mature plant communities in a multi-year trial in western Canada. Aspects of Applied Biology, 51:43-50 Dielman A., Hamill A.S., Fox G.C., Swanton C.J. 1996. Decision rules for post emergence control of pigweed (Amaranthus spp.) interference in Soybean(Glycine max).Weed Science, 44:126-132 Egley G.H., Williams R.D. 1991. Emergence periodicity of six summers annual weed species. Weed Science, 4: 595-600 Fehr, W.R., Caviness.C.E. 1977.Stages of soybean develpment. Spec .Rep. 80. Iowa Agric .Home Econ.Exp.Stn., Iowa State Uni. Ames Forcella F.,Wilson R.G., Dekker J. 1997. Weed seed bank emergence across the Corn Belt .Weed Science, 45:67-76 Forcella F., Benech Arnold R.L., Sanchea R., Ghersa C. 2000. Modeling seedling emergence. Field Crops Research, 67: 123-1, doi: 10.1016/S0378-4290(00)00088-5 Gallart M., Mas M.T.,Verdu A.M.C. 2010. Demography of Digitaria sanguinalis :effect of the emergence time on survival, reproduction, and biomass. Weed Biology and Management, 10:132-140; DOI: 10.1111/j. 14456664.2010.00375 Heindl J.C., Burn W.A.1983. Light and shade effects on abscission and C- photaassimilate partitioning among reproductive structures in soybean. Plant Physiology, 73:434-439; DOI:10.1104/pp.73.2.434 Hock S.M., Knezevic S.Z., Martin A.R., Lindquist J.L. 2005. Influence of soybean row width and velvetleaf emergence time on velvetleaf (Abutilon theophrasti). Weed Science, 53: 160-165; DOI: 10.1614/WS-04-122R Knezevic S.Z., Horak M.J. 1998. Influence of emergence time and density on redroot pigweed (Amaranthus retroflexus).Weed Science, 46: 665-672 Knezevic S.Z., Evans S.P., Mainz M. 2003a. Row spacing influences the critical timing for weed removal in soybean (Glycine max). Weed Technology, 17: 666673; DOI: 10.1614/WT02-49 Knezevic S.Z., Evans S.P., Mainz M. 2003b. Yield penalty due to delayed weed control in corn and soybean. [Crop Management Journal Online] www.plantmanagementnetwork.org/pub/cm/research/ 2003/delay./ Legere A., Schreiber M.M.1989.Competition and canopy architecture as affected by Soybean (Glycine max) row width and density of redroot pigweed (Amaranthus retroflexus ) .Weed Science, 37:84-92 Lindquist J.L., Max Well B.D., Buhler D.D., Gun Solus J.L. 1995. Velvetleaf (Abutilon theophrasti): Recruitment, survival,seed production, and interference in Soybean (Glycine max).Weed Science, 43:226-232 Martens S.K., Jansen J.H. 2002.Weed seed production, crop planting pattern, and mechanical weeding in wheat. Weed Science, 50:748-756; DOI: 0043-1745(2002)050 Massinga R.F., Currie R.S., Horak M.J., Boyer J. 2001. Interference of Palmer Amaranth in corn. Weed Science, 49: 202-208.; DOI: 0043-1745(2001)049 Mickelson J.A., Renner K.A. 1997. Weed control using reduced rates of post emergence herbicides in narrow and wide row soybean. Journal of Production Agriculture, 12: 35-43 Mitich L.W. 1991.Velvetleaf. Weed Technology, 5: 253255 Mulugeta D., Boerboom C.M. 2000. Critical time of weed removal in glyphosate -resistant soybean (Glycine max). Weed Science, 48: 35-42, doi: 10.1614/0043-1745(2000)048[0035:CTOWRI]2.0.ra;2 Munger P.H., Chandler J.M., Cothren J.T., Hons F.M. 1987. Soybean (Glycine max) velvetleaf (Abutilon theophrasti) interspecific competition. Weed Science, 35: 647- 653 Nice G.R.W., Buehrin N.W., Shaw D.R. 2001. Sicklepod response to shading ,soybean (Glycine max) row spacing and population in three management systems. Weed Technology, 15: 155-162; DOI: 0890-037X (2001)015 Norsworthy J.K., Jha P., Bridges W. 2007. Sicklepod survival and fecundity in wide- and narrow-row glyphosate-resistant soybean (Glycine max). Weed Science, 55: 252-259; DOI: 10.1614/WS-06-155 O'Donovan J.T., Remy E.A., O'Sullivan P.A., Dew D.A., Sharma A.K. 1985. Influence of the relative time of emergence of wild oat (Avena fatua) on yield loss of barley (Hordeum vulgare) and wheat (Triticum aestivum).Weed Science, 33: 498- 503 Oreja F.H., dela Fuente E.B.2005. Population dynamics of Digitaria sanguinalis L. scop. In soybean in the Pampa.Proc.XVII Congreso of the Latinoamerican Weed Science Associations (ALAM).Varadero.Cuba.1-5. Puricelli E., Oriolli G., Sabbatini M.R. 2002. Demography of Anoda cristata in wide-and narrow row soybean. Weed Research, 42:456-463; DOI: 10.1046/j. 13653180.2002.00307 Pyon J.Y., Guh J.O., KU Y.C. 1997. Environment-friendly cultural and mechanical practices for weed management.Korean Journal Weed Science, 17: 124134 Rezvani H., Latifi N., Zeinali E. 2008. Determination of critical period for velvetleaf (Abutilon theophrasti) control in summer seeded soybean, Williams's cultivar. Electronic Journal Crop Production, 1(2): 4565 Sadeghi H., Baghestani M.A., Akbary G.A., Hegazy A. 2003. Evaluation of soybean (Glycine max) and some weed species growth indices under competition condition. Plant Pest and Disease Journal, 71: 87-106 Samson D.A., Werk K.S .1986.Size - dependent effects in the analysis of reproductive effort in plants. American Naturalist, 127:667-680, doi: 10.1086/284512 SAS Institute .2001. S AS/ST AT user's guide .Version 8.Vols.1-3.Cary, NC: SAS Institute 1028 p. Schwinning S., Weiner J. 1998. Mechanisms determining the degree of size asymmetry in competition among plants. Oecologia, 113:447-455, doi: 10.1007/s004420050397 Scursoni J., Benech Arnold R., Hirchoren H. 1999. Demography of wild oat in barley crops: effect of crop, sowing rate, and herbicide treatment. Agronomy Journal, 91: 479-485, doi: 10.2134/agronj 1999.00021962009100030020x Shafigh M., Rashed Mohassel M.H., Nassiri Mahallati M. 2006. The competitive aspect of soybean (Glycine max) and Velvetleaf (Abutilon theophrasti) in response to population density and planting date. Jour. Iranian. Field Crops Research, 4:71-81 Steckel L.E., Sprague C.L. 2004. Late-season common water hemp (Amaranthus rudis) interference in narrow- and wide-row soybean. Weed Technology, 18: 947-952; DOI: 10.1614/WT-03-131R Swanton C.J., Weise S.W. 1991. Integrated weed management: the rationale and approach. Weed Technology, 5: 663-687 Swanton C.J, Mahoney K.J., Chandler K., Gulden R.H. 2008. Integrated weed management: Knowledge-Based weed management systems. Weed Science, 56: 168-172; DOI: 10.1614/WS-07-126.1 Thompson B.K., Werner J., Warwick S.I. 1991. Size-dependent reproduction output in agricultural weeds. Canadian Journal of Botany, 69:442-446, doi: 10.1139/b91-061 Walker R.H. and Buchanan G.A. 1982. Crop manipulation in integrated weed management systems. Weed Science, 30 (Suppl.1): 17-23 Warwick S.I., Black L.D. 1988. The biology of Canadian weeds. 90. Abutilon theophrasti. Canadian Journal of Plant Science, 68: 1069-1085, doi: 10.4141/cjps88-127 Williams M.M., Mortensen D.A., Doran J.W. 1998. Assessment of weed and crop fitness in cover crop residues for integrated weed management. Weed Technology, 46: 595-603 Yelverton F.H., Coble H.D. 1991. Narrow row spacing and canopy formation reduces weed resurgence in soybeans (Glycine max). Weed Technology, 5:169174 Young B.G., Young J.M., Gonzani L.C., Hart S.E., Wax L.M., Kapusta G. 2001. Weed management in narrow and wide-row glyphosate-resistant soybean (Glycine max). Weed Technology, 15: 112-121; DOI: 0890-037X (2001)015 Zeinali E., Ehteshami M.R. 2003. Biology and control of important weed species .Gorgan University of Agricultural Science and Natural Resources. Gorgan, Iran .pp.412 Zimdahl. R.L.1988. The Concept and application of the critical weed-free period. CRC Press. Boca Raton, FL, USA COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.13 Agrovoc descriptors: Daucus carrota, varieties, chemical compounds, polyphenols, antioxidants Agris category code: q04 chemical composition, carotenes, carotenoids, Carrot (Daucus carota L. ssp. sativus (Hoffm.) Arcang.) as source of antioxidants Judita BYSTRICKÀ1, Petra KAVALCOVÀ2, Janette MUSILOVÀ1, Alena VOLLMANNOVÀ3, Tomaš TÓTH4 Marianna LENKOVÀ4 Received June 16, 2015; accepted September 08, 2015. Delo je prispelo 16. junija 2015, sprejeto 08. septembra 2015. ABSTRACT IZVLEČEK Carrot (Daucus carota L. ssp. sativus (Hoffm.) Arcang.) is a significant source of vitamins (A, B, C) and beta carotene. Further it contains vitamins B, C, E, H, folic acid and pantothenic acid. Carrot is an important source of trace elements (K, Na, Ca, Mg, P, S, Mn, Fe, Cu and Zn). Consumption of carrot improves eyesight, lowers cholesterol and improves digestion. In this work we evaluated and compared content of total polyphenols, ß-caroteneand antioxidant activity in five varieties of carrot ('Jitka', Kardila', Katlen ', 'Rubina' and Koloseum ) Samples of carrot were collected at full maturity stages from area of Bardejov. Samples of fresh carrot were homogenized (25 g) in 50 ml 80 % ethanol and analysed after sixteen hours. The content of the total polyphenols was determined by using the Folin-Ciocalteu reagent (FCR). The content of ß-carotene was determined spectrophotometricaly at 450 nm. Antioxidant activity was measured using a compound DPPH' (2.2-diphenyl-1-picrylhydrazyl) at 515.6 nm using spectrophotometer. Total polyphenols content in samples ranged from 81.25 ± 13.11 mg/kg to 113.69 ± 11.57 mg/kg and content of ß-carotenes ranged from 24.58 ± 2.38 mg/kg to 124.28 ± 3.54 mg/kg. We also evaluated and compared the antioxidant activity in selected varieties of carrot, which varied from 6.88 ± 0.92 % to 9.83 ± 0.62 %. Statistically significant the highest value of total polyphenols was recorded in variety of Koloseum (113.69 ± 11.57 mg/kg). This variety is also characterized by the highest content of ß-carotene (124.28 ± 3.54 mg/kg )as well as the highest value of antioxidant activity (9.83 ± 0.62 %). Key words: carrot, cultivar, ß-carotenes, polyphenols, antioxidant activity KORENJE (Daucus carota L ssp. sativus (Hoffm.) Arcang.) KOT VIR ANTIOKSIDANTOV Korenje (Daucus carota L. ssp. sativus (Hoffm.) Arcang.) je pomemben vir vitaminov (A, B, C) in beta karotena. Dodatno vsebuje vitamine B, C, E, H, folno in pantotentsko kislino. Korenje je tudi pomemben vir elementov v sledeh kot so K, Na, Ca, Mg, P, S, Mn, Fe, Cu in Zn. Uživanje korenja izboljšuje vid, zmanjšuje količino holesterola in izboljšuje prebavo. V tej raziskavi smo ovrednotili in primerjali vsebnost celokupnih polifenolov, beta karotena in antioksidacijsko aktivnost v petih sortah korenja ('Jitka', 'Kardila', 'Katlen ', Rubina' and 'Koloseum'). Vzorci korenja so bili nabrani ob tehnološki zrelosti na območju Bardejova. Vzorci svežega korenja so bili homogenizirani (25 g) v 50 ml 80 % etanola in analizirani po 16 urah. Vsebnost celokupnih polifenolov je bila določena z uporabo Folin-Ciocalteu reagenta (FCR). Vsebnost beta karotena je bila določena spektrofotometrično pri 450 nm. Tudi antioksidacijaka aktivnost je bila izmerjana spektrometrično z uporabo DPPH' (2.2-difeenil-1-pikcrilhidrazil) pri 515.6 nm. Vsebnost celukopnih polifenolov v vzorcih je bila med 81.25 ± 13.11 mg/kg in 113.69 ± 11.57 mg/kg, vsebnost ß-karotena pa med 24.58 ± 2.38 mg/kg in 124.28 ± 3.54 mg/kg. Ovrednotili in primerjali smo tudi antioksidacijsko aktivnost v izbranih sortah korenja, ki je bila med 6.88 ± 0.92 % in 9.83 ± 0.62 %. Največjo, statistično značilno vsebnost polifenolov smo izmerili pri sorti Koloseum (113.69 ± 11.57 mg/kg). Ta sorta je bila značilna tudi po največji vsebnosti ß- karotena (124.28 ± 3.54 mg/kg) kot tudi po največji antioksidacijski aktivnosti (9.83 ± 0.62 %). Ključne besede: korenje, sorta, ß-karoten, polifenoli, antioksidacijska aktivnost 1 Assoc. Prof. Ing., Ph.D, Dept. of Chemistry, Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra; Slovak Republic 2 Ing., Dept. of Chemistry, Dept. of Chemistry, Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra; Slovak Republic 3 Prof., RNDr., Ph.D, Dept. of Chemistry, Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra; Slovak Republic 4 Assoc. Prof. RNDr. Ing., Ph.D, Dept. of Chemistry, Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra; Slovak Republic 1 INTRODUCTION Carrots in Slovak Republic are among most popular root vegetables. It is the most important crop of Apiaceae family. Member of this family have small, mostly white, 5-parted flowers arranged in umbrella-like inflorescence called umbel (Essig, 2013).Carrots were first used for medical purposes and gradually used as food (Carlos and Dias, 2014). This vegetable is an important source of bioactive compounds with beneficial effect for the consumer health.Carrots are consumed in different ways, they can be eaten raw or cooked. Fruits and vegetables are an important part of our diet. They provide, not only the major dietary fiber component of food, but also a range of micronutrients, including minerals, vitamins and antioxidant compounds, such as carotenoids and polyphenols (Augspole et al., 2014). Increased consumption of fruits and vegetables containing high levels of phytochemicals has been recommended to prevent chronic diseases related to oxidative stress in the human body (Liu 2003; Rao and Rao, 2007; Pandey and Rizvi, 2009. Fruits and vegetables are valuable sources of health-promoting substances active in neutralization of reactive oxygen species (Augustynowicz et al., 2014). Among them carrot belongs to horticultural crops of high recognition and importance due to its nutritional value and high concentration of bioactive constituents (Leja et al., 2013). Carrot is one of the most important vegetables in the world; its bioactive constituents may be beneficial to a vast number of consumers. It is rich in pro-healthy antioxidants both of lipophilic (carotenoids) and hydrophilic (phenolic compounds) characters (Hager and Howard, 2006; Sharma et al., 2012; Leja et al., 2013). Carrots are a good source of carbohydrates and minerals like Ca, P, Fe and Mg (Sharma et al., 2012). This root vegetable contains valuable phytochemicals. The presence of phytochemicals, in addition to vitamins and provitamins, in fruits and vegetables has been recently considered of crucial nutritional importance in the prevention of chronic diseases, such as cancer, cardiovascular disease, and diabetes (Nambia et al., 2010; Jamuna et al., 2011; Myojin et al., 2008). The complex mixture of phytochemicals in fruits and vegetables provides a better protective effect on health than single phytochemicals. Carrot could release approximately half of their phytochemical contents in the colon (Chu et al., 2002). Carrots are noted for their rich antioxidants, especially ß-carotene. In recent years, worldwide consumption of carrots has been steadily increasing because of their nutritional benefits. Carrots have potentially beneficial health effects, anti-carcinogenic, antioxidant, and immune-boosting properties, as well as the pro-vitamin activity of some carotenoids (Fiedor and Burda, 2014; Tanaka et al., 2012). The most important micronutrient is ß-carotene, which is a lipid-soluble carotenoid. Its typical chemical structure, consisting of a polyene chain with 11 conjugated double bonds and ß-ring at each end of the chain (Augspole et al., 2014). Oxygen is a highly reactive atom that is capable of becoming part of potentially damaging molecules commonly called "free radicals." Free radicals are capable of attacking the healthy cells of the body, causing them to lose their structure and function (Gupta et al., 2012; Pandey et al., 2012; Prasad and Rajkumar, 2014). Antioxidants are our first line of defence against free radical damage, and are critical for maintaining optimum health and wellbeing. Antioxidants can scavenge free radicals and protect the human body from oxidative stress, which is the main cause of some cancers and heart diseases (Sun et al., 2003). Vitamin C, vitamin E, and beta carotene are among the most widely studied dietary antioxidants. Vitamin C is important water-soluble antioxidant in extracellular fluids. It is capable of neutralizing free radicals in the aqueous phase. Vitamin E, a major lipid-soluble antioxidant, is the most effective chain-breaking antioxidant within the cell membrane where it protects membrane fatty acids from lipid peroxidation. Vitamin C regenerates vitamin E. Beta carotene and other carotenoids are also believed to provide antioxidant protection to lipid-rich tissues (Shukla et al., 2014; Kumari et al., 2014). Polyphenols can be characterized as products of plants secondary metabolism of. The phenolic compounds contain aromatic ring with one or more substituent -OH groups. Polyphenols are formed by many and very diverse group of substances, simple phenolic and polymerized phenolic compounds. Therefore they are often called polyphenols (Balasundram, 2006). Phenolic compounds can act as antioxidants by interfering with oxidation processes through chainbreaking reaction activities (primary oxidation) or through scavenging of free radicals (secondary oxidation) (Ndhlala et al., 2010; Augspole et al., 2014). Antioxidants are capable of stabilizing, or deactivating, free radicals before they attack cells (Kumari et al., 2014; Agarwal, 2012). The presented work is a part of a broader topics dealing with polyphenolic compounds and carotenes with antioxidant effects in selected varieties of carrot. The main purpose of this study was to determine the influence of cultivar on the content of the total polyphenols, carotenes as well as antioxidant activity in carrot. 2 MATERIALS AND METHODS 2.1 Climate conditions of location This study was carried out in area of Bardejov, area without negative influences and i mission sources. It is located in the north-eastern Slovakia of region Šariš, with 49.1357, 20.4335 coordinates. The attitude of the village is in the middle of 276 m a.s.l. Average annual air temperature is 7.4 °C, and annual rainfall is 700 mm. 2.2 Plant samples Five carrot (Daucus carota L. ssp. sativus (Hoffm.) Arcang.) cultivars (Jitka', Kardila', Katlen ', 'Rubina ' and Koloseum ) were obtained from a local producer in are Bardejov, Slovak Republic. All cultivars were cultivated conventionally under the same condition. Only NPK fertilization has been used for the achievement of favourable soil macroelements content. The soils on which the carrots were grown, can be characterized as acidic to neutral (pH/KCl = 5.51 - 6.60), with medium to high content of humus (% Hum. = 2.98 to 3.76), very high phosphorus (P = 257.50 -310.15 mg/kg), potassium (K = 321.19 -387.6 mg/kg) and magnesium content (Mg = 221.30 - 276.53 mg/kg). Samples offive cultivars of carrots were collected at full maturity stages. From the same places, from the arable layer (0 - 20 cm), soil samples were also taken with pedological probe GeoSampler fy. Fisher. 2.3 Characteristics of varieties Jitka is medium-late varieties of carrot. It is well storable and suitable for industrial processing. Kardila is a late variety, suitable for winter storage. Koloseum is late variety of carrot, well storable and suitable for eating. The variety has high dry matter content and long shelf life. Katlen is late variety, very profitable for the storage and industrial processing. Rubina is late, traditional variety of carrot. 2.4 Sample preparation Samples of selected varieties of carrot were homogenized (25 g) in 50 mL 80 % ethanol for sixteen hours.Samples were kept under laboratory room temperature in dark bottles and dark light conditions until pre-analytical operations. These extracts were used for analyze. The experiment was based on four replications. 2.5 Determination of total polyphenols Total polyphenols were determined by the method of Lachman et al. (2003) and expressed as mg of gallic acid equivalent per kg fresh mater. Gallic acid is usually used as a standard unit for phenolics content determination because a wide spectrum of phenolic compounds. The total polyphenol content was estimated using Folin-Ciocalteau assay. The Folin-Ciocalteau phenol reagent was added to a volumetric flask containing 100 ml of extract. The content was mixed and 5 ml of a sodium carbonate solution (20 %) was added after 3 min. The volume was adjusted to 50 ml by adding of distilled water. 2.7 Determination of antioxidant activity Antioxidant activity was measured by the BrandWilliams et al. (1995) method-using a compound DPPH' (2. 2-diphenyl-1 -pikrylhydrazyl). 2.2-diphenyl-1-pikrylhydrazyl (DPPH ) was pipetted to cuvette (3.9 ml) then the value of absorbance which corresponded to the initial concentration of DPPH' solution in time Ao was written. Then o.1 ml of the followed solution was added and then the dependence A = f(t) was immediately started to measure. The absorbance of 1, 5 and 10 minutes at 515.6 nm in the spectrophotometer Shimadzu UV/VIS - 1240 was mixed and measured. The percentage of inhibition reflects how antioxidant compound are able to remove DPPH' radical at the given time. Inhibition (%) = (Ao - At / Ao) x 100 2.8 Statistical analysis Results were statistically evaluated by the Analysis of Variance (ANOVA - Multiple Range Tests, Method: 95.0 percent LSD) using statistical software STATGRAPHICS (Centurion XVII, USA). 3 RESULTS AND DISCUSSION In this work the content of total polyphenols in carrot was watched and evaluated. The results are shown in Table 1. Table 1: Average content of total polyphenols (mg/kg) in selected varieties of carrots vegetable variety TPC (mg/kg) Jitka 81.25 ± 13.11a Kardila 88.71 ± 7.47ab Katlen 97.10 ± 11.38ab Rubina 102.18 ± 6.68bc Koloseum 113.69 ± 11.57d HD0,05 15.8749 HD0,01 21.9469 LSD Test on the significance: a: < 0.05 After 2 hours, the samples were centrifuged for 10 min. and the absorbance was measured at 765 nm of wave length against blank. The concentration of polyphenols was calculated from a standard curve plotted with known concentration of gallic acid. 2.6 Determination of carotens ß-carotene after releasing by ethanolic hydroxide and after extraction into petrolether could be determined by spectrophotometry at wavelength 450 nm. Content of ß-carotene in carrot was assessed by method of calibration curve with measuring of absorbance of standard solutions of potassium dichromate. Carrot (1 g) was put in flask and added 20 ml of ethanolic solution NaOH, then 20 ml of HCl (1:1) was added. The flask content was quantitatively put on filter and washed by acetone till its non-soluble part was colourless. Filtrate was put into separating funnel (500 mL), added 40 ml petrolether and filled to % water content. The procedure is 2 - 3 times repeated till the water ethanolic phase is colourless. Total polyphenols content in samples ranges from 81.25 ± 13.11mg/kg to 113.69 ± 11.57 mg/kg. Statistically significant the highest value of total polyphenols was recorded in variety of Koloseum (113.69 ± 11.57 mg/kg). The lowest content of total polyphenols was recorded in variety of Jitka (81.25 ± 13.11 mg/kg). Based on the measured values of total polyphenols varieties of carrot can be classified as follows: Koloseum (113.69 mg/kg) > Rubina (102.18 mg/kg) > Katlen (97.10 mg/kg) > Kardila (88.71 mg/kg) > Jitka (81.25 mg/kg) Algarra et al. (2014) reported that the content of polyphenols in carrot was 94 mg/kg. Bembem a Sadana (2014) determined higher content of polyphenols in carrot. in comparison with our results. Their value was 320 mg/kg. The highest levels of polyphenols in carrots recorded Leahu et al. (2013). namely 652 ± 0.85 mg/kg. Jamada et al. On the basis of gained results we can conclude. that statistically significant the highest value of ß-carotenes was recorded in variety Koloseum (124.28 ± 3.54 mg/kg). The lowest content of ß-carotenes was detected in variety Jitka (24.58 ± 2.38 mg/kg). In variety Koloseum the average content of ß-carotenes was 5.05 times higher than in the variety Jitka. Karnjanawipagul et al. (2010) reported that the content of ß-carotenes in carrot samples was in the range from 72.3 - 145.9 mg/kg. Ullah et al. (2011) indicated 112.1 mg/kg ß-carotenes in carrot. Rebecca et al. (2014) published a higher value of (2011) referred that the content of total polyphenols was in interval from 455 to 697 mg/kg. Polyphenols are the most widespread and most numerous group of plant secondary metabolites and are an integral part of the diet of all living organisms. Natural polyphenolic compounds are ranked among the most abundant substance exhibiting antioxidant activity in our diet. Another indicator that has been evaluated and compared was the content of ß-carotenes in varieties of carrot. Carrot is considered one of the most important source of carotenoids. especially ß-carotene. The results of the determinations of ß-carotenes in the samples of carrot are shown in Table 2. ß-carotenes in carrot. Their value represented 183 mg/kg ß-carotenes in carrot. Carotenoids with polyphenols are a phytochemicals that are responsible for the antioxidant activity of carrots. They protect human body against cardiovascular disease. arteriosclerosis and cancer (Ciccone et al.. 2013; Relevy et al.. 2015). In the present work it was detected. that antioxidant activity in samples of carrot ranges from 6.88 ± 0.92 % (in variety of Jitka) to 9.83 ± 0.62 % (in variety of Koloseum) (Table 3). Table 2: Average content of ß-carotenes (mg/kg) in selected varieties of carrots vegetable variety ß-carotenes (mg/kg) Jitka 24.58 ± 2.38a Kardila 47.42 ± 3.97b Katlen 44.19 ± 3.01b Rubina 29.19 ± 3.76a Koloseum 124.28 ± 3.54c HD0,05 5.10442 HD0,01 7.05682 LSD Test on the significance: a: <0.05 Table 3: Average values of antioxidant activity (% inibition) in carrot vegetable variety AOA (% inhibition) Jitka 6.88 ± 0.92a Kardila 9.42 ± 0.68c Katlen 8.75 ± 0.78bc Rubina 7.54 ± 0.94ab Koloseum 9.83 ± 0.62c HD0,05 1.20821 HD0,01 1.67034 LSD Test on the significance: a: <0.05 In the variety Koloseum the average value of antioxidant activity is 1.4- times higher than that of the variety Jitka (6.88 %) and 1.3- times higher than in the variety Rubina (7.54 %). Our obtained results are in accordance with findings Algarra et al. (2014), who also determined the values of antioxidant activity in carrot in the interval from 1.4 % to 17.6 %. Bembem et al. (2014) also determined the value of antioxidant activity in carrot (11.2 %). In this paper also relations among content of polyphenols, ß-carotenes and antioxidant activity were evaluated (Figure 1 - 6). Our work was in coherence with the findings of Čiž et al. (2010), Hu (2012) who indicated correlations between content of polyphenols in the onion, carrot, potato, cabagge and antioxidant activity. .0 cv. Rubina ♦ ■ ' ♦ * ♦ ♦ У у-0,1 .TMS-6,711 к' -o,m 05 100 1[K lift 115 TPC (tllg/kjl Figure 1: Relathionship between TPC and AOA in carrot Rubina' Figure 2: Relathionshipbetween TPC and AOA in carrot Koloseum' Figure 3: Relathionship between TPC and AOA in carrot Katlen' с v. Rubina ♦ ♦ y = O .TfilMy- n.nftSF 20 22 Л 20 2B äCJ content of ß-carotenes r i-r/к ; ,1 32 34 Figure 4: Relathionship between content of ß-carotenes and AOA in carrot Rubina' Figure 5: Relathionship between content of ß-carotenes and AOA in carrot Koloseum' ♦ cv. Katie ri > ♦ у - Q,7?6Qx- 1,?7ft B2 - О.ЯЛЯЯ 11 П 13 11 "15 16 <17 1S ronlent of ß-carotenes (mg/kg) Figure 6: Relathionship between content of ß-carotenes and AOA in carrot Katlen' 4 CONCLUSION Vegetable generally is a source of substances of high biological and nutritional value. Carrot is important in human nutrition and also in animal nutrition. Carrot is very popular vegetable for its important vitamins (group B, provitamin A, vitamin C), sugars and minerals in particular Ca, F, Se and Mg. It is also a rich source of chemoprotective compounds that protect the body against many diseases of civilization. The content of biologically active substances (polyphenols) in carrot root depends on various factors such as: area in which the carrot is grown (agrochemical characteristic of soil), climatic conditions in the region during the growing season, cultivation technology but also the variety. The obtained results suggest that the carrot is a rich source of carotenes. We determined the highest content in 'Koloseum' 113.69±11.57 mg/kg and also there was determined the highest value of antioxidant activity 9.83±0.62. 5 ACKNOWLEDGEMENT This work was supported by scientific grant VEGA 1/0290/14, VEGA 1/0456/12. This work was co-funded by European Community under project no 26220220180: Building Research Centre „AgroBioTech". 6 REFERENCES Agarwal S. 2012. Lycozen-gt: a super anti-oxidant multivitamin, multimineral formulation with goodness of lycopene, green tea & grape seed extract for excellent protection. International Journal of Research in Pharmacology and Pharmacotherapeutics, 1: 103-120 Algarra M., Fernandes A., Mateus N., Freitas V., Joaquim C.G., Silva E., Casad CH. 2014. Anthocyanin profile and antioxidant capacity of black carrots (Daucus carota L. ssp. sativus var. atrorubens Alef.) from Cuevas Bajas, Spain. Journal of Food Composition and Analysis, 33: 71-76, doi: 10.1016/j.jfca.2013.11.005 Augspole I., Rackejeva T., Kruma Z., Dimins F. 2014. Shredded carrots quality providing by treatment with Hydrogen peroxide. 9th Baltic Conference on "Food for Consumer Well - Being" FOODBALT 2014, 150-154 Augustynowicz J., Dlugosz-Grochowska O.G., Kostecka-Gugata A.M., Leja M., Kruszek M.K., Swiderski A. 2014. Callitriche cophocarpa - a new rich source of active phenolic compounds. Central European Journal of Chemistry, 12: 519-527, doi: 10.2478/s11532-013-0404-3 Balasundram N. 2006. Phenolic compounds in plants and agri-industrial by-products: Antioxidant activity, occurence, and potential uses. Food Chemistry, 99: 191-203, doi: 10.1016/j.foodchem.2005.07.042 Bembem K., Sadana B. 2014. Effect of different cooking methods on the antioxidant components of Carrot. Bioscience Discovery, 5: 112-116 Brand-Williams W., Cuvelier M.E., Berset C. 1995. Use of a free radical method to evaluate antioxidant activity. Lebensmittel-Wissenschaft and Technologie, 28: 25-30, doi: 10.1016/S0023-6438(95)80008-5 Carlos J., Dias S. 2014. Nutritional and Health Benefits of Carrots and Their Seed Extracts. Food and Nutrition Sciences, 5: 2147-2156, doi: 0.4236/fns.2014.522227 Chu Y., Sun J., Wu X., Liu R.H. 2002. Antioxidant and Antiproliferative Activities of common Vegetables. Journal of Agricultural and Food Chemistry, 50: 69106916, doi: 10.1021/jf020665f Ciccone M.M., Cortese F., Gesualdo M., Carbonara S., Zito A., Ricci G., De Pascalis F., Scicchitano P., Riccioni G. 2013. Dietary intake of carotenoids and their antioxidant and anti-inflammatory effects in cardiovascular care. Mediators of Inflammation, Volume 2013, 11 pages. Ciž M., Cižova H., Denev P., Kratchanova M., Slavov A., Lojek A. 2010. Different methods for control and comparison of the antioxidant properties of vegetables. Food Control, 21, 518-523, doi: 10.1016/j.foodcont.2009.07.017 Essing F.B. 2013. What's in a Family? The Apiaceae. Florida Gardening, 18: 36-37 Fiedor J., Burda K. 2014. Potential Role of Carotenoids as Antioxidants in Human Health and Disease. Nutriens, 6: 466-488, doi: 10.3390/nu6020466 Gupta V., Kunari S., Kumar A. 2012. Mechanism of oxygen free radical generation and Endogenous Antioxidants. The Journal of Phytopharmacology, 1: 89-100 Hager T.J., Howard L.R. 2006. Processing Effects on Carrot Phytonutriens. Horticultural Science, 41: 74-79 Hu Ch. 2012. Factors affecting phytochemical composition and antioxidant activity of Ontario vegetable crops. (A thesis presented to the University of Guelphl). Guelphl, Ontario, Canada. P. 194 Jamada M., Yamauchi J., Hosoyamada Y. 2011. The properties of the components of carrot leaf, and their effect on serum lipids in cholesterol-fed rats. Journal for the Integrated Study of Dietary Habits, 22: 148-152, doi: 10.2740/jisdh.22.148 Jamuna K.S., Ramesh C.K., Srinivasa T.R., Raghu K.L. 2011. In vitro antioxidant studies in some common fruits. International Journal of Pharmacy and Pharmaceutical Sciences, 3: 60-63 Karnjanawipagul P., Nittayanuntawech W., Rojsanga, P., Suntornsuk, L. 2010. Analysis of ß-carotene in carrot by spectrophotometry. Journal of Pharmaceutical Science, 37: 8-16 Kumari S., Maguddajao A.V.Z., Prashar S, Kumar C.J.S. 2014. The antioxidant revolution - to protect against diseases & to maintain optimum health and wellbeing. International Journal of Pharmacology Research, 4: 47-51 Lachman J., Pronèk D., Hejtmànkovà A., Pivec V., Faitovà K. 2003. Total polyphenol and main flavonoid antioxidants in different onion (Allium cepa L.) varieties. Scientia Horticulturae, 30: 142-147 Leahu A., Damian C., Carpiuc N., Oroian M., Avramiuc M. 2013. Change in colour and physicochemical quality of carrot juice mixed with other fruits. Journal of Agroalimentary processes and technologies, 19: 241-246. Leja M., Kaminska I., Kramer M., Maksylewicz-Kaul A., Kammerer D., Carle R., Baranski R. 2013. The Content of Phenolic Compounds and Radical Scavenging Activity Varies with Carrot Origin and Root Color. Plant Foods Human Nutrition, 68: 163-170, doi: 10.1007/s11130-013-0351-3 Liu R.H. 2003. Health benefits of fruit and vegetables are from additive and synergistic combinations of phytochemicals. American Society for Clinical Nutrition, 78: 517-520 Myojin C., Enami N., Nagata A., Yamaguchi T., Takamura H., Matora T. 2008. Changes in the Radical-Scavenging Activity of Bitter Gourd (Momordica charantia L.) during Freezing and Frozen Storage with or without Blanching. Journal of Food Science, 73: 546-550, doi: 10.1111/j.1750-3841.2008.00886.x Nambia V.S., Daniel M., Guin P. 2010. Characterization of Polyphenols from Coriander leaves (coriandrum sativum), red amaranthus (a. paniculatus) and green amaranthus (a. frumentaceus) using paper chromatography: and their health implications. Journal of Herbal Medicine and Toxicology, 4: 173-177 Ndhlala A.R., Moyo M., Van Staden J. 2010. Natural Antioxidants: Fascinating or Mythical Biomolecules? Molecules, 15: 6905-6930, doi: 10.3390/molecules15106905 Pandey R.B., Rizvi S.I. 2009. Plant polyphenols as dietary antioxidants in human health and disease. Oxidative Medicine and Cellular Lengevity, 2: 270-278, doi: 10.4161/oxim.2.5.9498 Pandey S., Kumar P, Verna S. 2012. Comparing of antioxidant and DPPH induced free radical scavenging activity of Sesbania grandiflora and Acacia nilotica plants. The Journal of Phytopharmacology, 1: 33-42 Prasad M.P., Rajkumar R. 2014. In vitro antioxidant assay of citrus species using DPPH method. Indian Journal of Advances Plant Research, 1: 01-03 Rao A.V., Rao L.G. 2007. Carotenoids and human health. Pharmacological research, 55: 207-213, doi: 10.1016/j.phrs.2007.01.012 Rebecca L.J., Sharmila S., Das M.P., Seshiah C. 2014. Extraction and purification of carotenoids from vegetables. Journal of Chemical and Pharmaceutical Research, 6: 594-598 Relevy N.Z., Rühl R., Harari A., Grosskopf I., Barshack I., Ben-Amotz A., Nir U., Gottlieb H., Kamari Y., Harats D., Shaish A. 2015. 9-cis ß-carotene Inhibits Atherosclerosis Development in Female LDLR-/-Mice. Functional Foods in Health and Disease, 5: 67-79 Sharma K.D., Karki S., Thakur N.S., Attri S. 2012. Chemical composition, functional properties and processing of carrot. Journal of Food Science and Technology, 49: 2232, doi: 10.1007/s13197-011-0310-7 Shukla G., Sarika M., Saritha D., Kumar C.J.S. 2014. Lycotenforte capsules: a multiple nutrient antioxidant, anti-microbial, anti-inflammatory protection with anti-aging benefits. International. Journal of Innovative Drug Discovery, 4: 25-30 Silva Dias J.C. 2014. Nutritional and Health Benefits of Carrots and Their Seed Extracts. Food and Nutrition Sciences, 5: 2147-2156, doi: 10.4236/fns.2014.522227 Sun T., Powers J.R., Tang J. 2003. Evaluation of the antioxidant activity of asparagus broccolia their juices. Food Chemistry 105: 101-106, doi: 10.1016/j.foodchem.2007.03.048 Tanaka T., Shnimizu M., Moriwaki H. 2012. Cancer Chemoprevention by Carotenoids. Molecules, 17: 32023242, doi: 10.3390/molecules17033202 Ullah N., Khan A., Khan F.A., Khurram M., Hussan M., Khayam M.U., Amin M., Hussain J. 2011. Composition and isolation of beta carotene from different vegetables and their effect on human serum retina level. Middle-East Journal of Scientific Research, 9: 496-502 COBISS Code 1.01 DOI: 10.14720/aas.2015.105.2.14 Agrovoc descriptors: soybeans, Glycine max, phosphate fertilizers, biofertilizers, spacing, planting, weed control, crop management, crop yield Agris category code: f01, f04, f08, h01 The effects of planting arrangement and phosphate biofertilizer on soybean under different weed interference periods G. R. MOHAMMADI1*, S. CHATRNOUR1, S. JALALI1 and D. KAHRIZI1 Received November 11, 2014; accepted August 24, 2015. Delo je prispelo 11. novembra 2014, sprejeto 24. avgusta 2015. ABSTRACT IZVLEČEK This study was conducted to evaluate the effects of planting arrangement and phosphate biofertilizer on soybean yield and yield components under different weed interference periods at the Agricultural Research Farm of Razi University, Kermanshah, west Iran. The experiment was a factorial with three factors arranged in a randomized complete block design with four replications. The first factor was planting arrangement (50 and 5 cm (P1) or 25 and 10 cm (P2) for inter-row and inter-plant spacings, respectively), the second factor was phosphate biofertilizer (no-inoculation (I0) and inoculation (I1)) and the third factor was weed treatment (full season weed-free condition (W0), weedy condition until soybean 4-trifoliate stage (W1), weedy condition until soybean flowering stage (W2) and full season weedy condition (W3)). Results revealed that the highest soybean yield occurred when weeds were controlled throughout the growing season and soybean was planted at the inter-row and inter-plant spacings of 25 and 10 cm, respectively (P2) whether phosphate biofertilizer was used or not. For both planting arrangements, full season weedy condition at the lack of the biofertilizer led to the lowest soybean yield produced. Weed biomass was not significantly affected by use of biofertilizer. The highest weed biomass was established in plots without weed control throughout the whole growing season and soybean was planted in a wider row spacing and a less uniform spatial arrangement (P1). Moreover, For W2 and W3 treatments, soybean planted in a narrower row spacing and a more uniform spatial arrangement (P2) produced a notable lower weed biomass, so that, this planting arrangement reduced weed biomass by 31.8 and 31.7 % in W2 and W3, respectively as compared to the P1 planting arrangement. It can be concluded that soybean planting in a more uniform spatial arrangement via a narrower row spacing can significantly improve soybean yield and suppress weeds. Phosphate biofertilizer had no significant effect on soybean yield when soybean was planted as the P2 and weeds were controlled throughout the growing season. Key words: Glycine max, phosphate biofertilizer, planting arrangement, soybean yield, weed control UČINKI NAČINOV SETVE IN UPORABE FOSFORJEVIH BIO-GNOJIL NA PRIDELEK SOJE OD ČASOVNO RAZLIČNIH ZATIRANJ PLEVELOV V raziskavi, ki je bila izvedena na Agricultural Research Farm, Razi University, Kermanshah, zahodni Iran, so bili ovrednoteni učinki prostorske razporeditve rastlin (načinov setve) in uporabe fosforjevih bio-gnojil na pridelek soje in njegove komponente pri različnih zapleveljenostih. Poskus je bil zasnovan kot naključni bločni, trifaktorski poskus s štirimi ponovitvami. Prvi preučevani dejavnik je bila razporeditev rastlin v odvisnosti od načina setve, 50 in 5 cm (P1) ali 25 in 10 cm (P2), kot razdalji setve med vrstami in znotraj vrste. Drugi dejavnik je bila uporaba fosforjevih bio-gnojil (brez inokulacije (I0) in z inokulacijo (I1)) in tretji je bilo obravnavanje s pleveli (cela sezona brez plevelov (W0), zapleveljeno do stopnje razvoja, ko ima soja 4 trojnate liste (W1), zapleveljeno do začetka cvetenja soje (W2) in zapleveljeno celo rastno sezono (W3). Rezultati so pokazali, da je bil pridelek soje največji pri zatiranju plevelov skozi celo rastno sezono in ko je bila soja posejana v vrstah s 25 cm razmikom in z 10 cm razdaljo med rastlinami v vrsti (P2), ne glede na uporabo fosforjeva bio-gnojila. Zapleveljenost celo sezono in odsotnost gnojenja z bio-gnojili je dala ne glede na način setve najmanjši pridelek. Uporaba bio-gnojil ni značilno vplivala na biomaso plevelov. Največja biomasa plevelov je bila, kadar ti niso bili zatirani celo rastno sezono in, ko je bila soja posejana v vrstah s širšim razmikom, torej z manj enakomerno prostorsko razporeditvijo (P1). Pri obravnavanjih W2 in W3, ko je bila soja posejana v vrstah z manjšim razmikom in so bile rastline bolj enakomerno razporejene (P2), so imeli pleveli opazno manjšo biomaso. Takšni razporeditvi rastlin soje (W2 in W3) sta zmanjšali biomaso plevelov za 31.8 in 31.7 %, v primerjavi z raporeditvijo pri obravnavanju P1. Zaključimo lahko, da setev soje v vrstah z ožjim razmikom značilno poveča njen pridelek in zavre rast plevelov. Uporaba fosforjevih bio-gnojil ni imela značilnega vpliva na pridelek soje, kadar je bila ta posejana v vrstah z ožjim razmikom, P2, in če so bili pleveli nadzorovani celo rastno sezono. Ključne besede: Glycine max, fosforjeva bio-gnijila, razporeditev rastlin, pridelek soje, nadzor plevelov Dept. of Crop Production and Breeding, Faculty of Agriculture and Natural Resources, Razi University, Kermanshah, Iran Corresponding author: mohammadi114@yahoo.com 1 INTRODUCTION Soybean (Glycine max L.) is an important two-purpose crop which is extensively grown as a source of edible oil and protein for human nutrition in Iran. In soybean, weed infestation is considered a persistent and complex constraint in many regions of the world, as it influences soybean growth and development through competition for nutrients, water and light (Vollmann et al. 2010) as well as the production of allelopathic compounds (Rice 1984; Bhowmik and Doll 1982). Weeds are a serious constraint to easy harvesting in soybean and can reduce yield and economic returns. Thus, weed control is considered a key factor for successful soybean production, and various weed management systems have been developed for that purpose (Buhler and Hartzler, 2004). Weed control in soybean can be labor intensive or involve the intensive use of herbicides in Iran. Intensive herbicide use can increase costs, pose a threat to the environment and may promote the development of herbicide resistancein weeds. The implementation of an integrated weed management (IWM) system is seen by many weed scientists as a means of achieving the goal of reducing the amount of herbicide used while still maintaining crop yield (Swanton and Weise 1991). According to Johnson et al. (1997) there is a trend towards reducing crop row width as a means of increasing crop competition to suppress weeds. Early results in narrow-row soybean show that this method can provide adequate weed control and soybean yield (Steckel et al. 1990; Prostko and Meade 1993). Narrow rows make more efficient use of available resources and should allow quicker canopy closure and thus quicker shading of the ground thereby improving weed control (Fernandez et al. 2002). In general, crop competitive ability can also be increased by improving planting uniformity. Olsen et al (2005a; 2005b) reported that wheat produced more biomass and had less weed biomass as crop planting uniformity increased. According to Weiner et al. (2001) a more uniform planting distribution should enable crops to compete more successfully with weeds. In Iran, soybean is usually planted in a wide row spacing (50 cm). This row spacing can reduce potential crop yield and economic return due to less efficient use of available resources such as light, water and nutrients by the soybean plants and increase weed infestation. Moreover, the competitive relationship between crop and weeds is highly dependent on many factors including the characteristics of the crop and the weeds, the environmental variables, the cultural practices (Knezevic et al. 2002) and supply and availability of nutrients (Evans et al. 2003; Di Tomaso 1995). The availability of nutrients can influence the timeliness and extent of early season competition from weeds (Weaver et al. 1992). Phosphorus is an important element which can affect the competitive interactions between a crop and weeds. It is only second to nitrogen as a mineral nutrient required for plant growth (Ogbo 2010). Most of the soils in Iran are phosphorous deficient or marginally deficient and a massive increase in the rate of application of chemical fertilizers has been adopted to ameliorate this deficiency (Cox et al. 1993). However, a large proportion of the phosphorous content of chemical fertilizers is quickly transformed to the insoluble form such as calcium phosphate, thereby making them unavailable to plants. In addition, there are global concerns that the un-balanced use of chemical fertilizers has a role in environmental degradation and climate change (Day and Quinn 1989; Daynard et al. 1971). However, nutrients applied to soils are also available for weeds and these un-wanted plants are better able to utilize added nutrients than crops (Carlson and Hill 1986; Peterson and Nalewja 1992). Therefore, in an attempt to reduce environmental risk and cost with chemical fertilizer use and increase crop nutrient use efficiency, phosphorous biofertilizers (phosphate-solubilizing microorganisms) has been considered as possible substitutes for traditional mineral P fertilizer. These microorganisms have been distinguished by their relative ability to dissolve calcium phosphate and apatite in association with plant roots. This activity was attributed to organic acid and chelating metabolites produced by these microorganisms (Deinum et al. 1996; Dong and Pierdominici 1995). However, phosphate biofertilizer have shown variation in their performance in related to their environmental condition. This study was carried out to investigate the effects arrangement on soybean under different weed of phosphorus biofertilizer and planting pressure treatments in Kermanshah, west Iran. 2 MATERIALS AND METHODS The study was carried out in 2009 at the Agricultural Research Farm of Razi University, Kermanshah, west Iran. The soil type was a silty clay with a pH of 7.8 and 0.8 % organic matter. The land was plowed and disked before planting. The soybean cultivar was 'Williams' (a cultivar that is commonly planted in the region). All soybean seeds were inoculated with Bradyrhizobium japonicum Kirchner bacterium prior to sowing. The crop was planted on 9 May 2009 at a constant density of 40 plants m-2. Soybean is a summer and irrigated crop in western Iran; therefore, it is not dependent on seasonal rainfall. Irrigations were carried out at 7-9 day intervals throughout the growing season in term of crop need. The experiment was a factorial with three factors arranged in a randomized complete block design with four replications. The first factor was planting arrangement (50 and 5 cm (P1) or 25 and 10 cm (P2) for inter-row and inter-plant spacings, respectively), the second factor was phosphate biofertilizer (no-inoculation (I0) and inoculation (I1)) and the third factor was weed treatment (full season weed-free condition (W0), weedy condition until soybean 4-trifoliate stage (W1), weedy condition until soybean flowering stage (W2) and full season weedy condition (W3)). Each plot consisted of six soybean rows of 8 m long with predetermined inter-row and inter-plant spacings. Before planting, the seeds were also inoculated with phosphate biofertilizer (Barvar 2) containing the phosphate solubilizing microorganisms Pantoea agglomerans Eving and Fife and Pseudomonas putida Trevisan. Weed removal was carried out by hand. At maturity, soybean plants located at 4 m2 from each plot were harvested by hand and allowed to dry to a constant mass and weighed and biological yield (total aboveground dry mass) was determined. Subsequently, they were threshed and cleaned and seed yield was calculated. Then harvest index (HI) was calculated according to the following equation: HI = (Seed yield / Biological yield) x100 Additionally, 100-seed weight were determined according to the recommendations of the International Seed Testing Association (ISTA) (Draper, 1985). Before harvesting, the number of pods per plant and the number of seeds per pod were measured on 5 randomly selected plants in the centre rows of each plot, except from the rows that were used for yield measurement. Weed biomass was also measured by harvesting weeds at the ground level in three random 0.5^0.5 m quadrats in each plot at the end of the growing season for the W3 treatment and before each weed removal for the W1 and W2 treatments. Then weeds dried at 75° C to constant mass and weighed. Data analyses were carried out using SAS (SAS Institute 2003). 3 RESULTS AND DISCUSSION Analysis of variance (Table 1) revealed that all of the traits under study including soybean seed yield (SY), the number of pods per plant (PPP), the number of seeds per pod (SPP), 100-seed weight (SW), harvest index (HI) and weed biomass (WB) were significantly affected by weed treatments (at the 0.01 level of probability). There was a significant three-way interaction (weed treatmentxplanting arrangementxphosphate biofertilizer) for SY, PPP and SPP. The significant two-way interactions including weed treatmentxplanting arrangement, weed treatmentx phosphate biofertilizer and planting arrangementxphosphate biofertilizer were observed for HI. However, SW was significantly affected by the two-way interactions including weed treatmentxplanting arrangement, weed treatmentxphosphate biofertilizer. However, WB was influenced by a two-way interaction (weed biofertilizer alone or in combination with other treatmentXplanting arrangement) and phosphate factors had no significant effect on this trait. Table 1: Analysis of variance of the traits under study Source of Variance Mean Square Seed yield Pod/plant Seed/pod 100-seed weight Harvest index Weed biomass Replication 309.03 ns 7.80 ns 0.04 ns 0.33 ns 1.24 ns 672420.05 ns Weed Interference (WI) 94876.00 ** 6854.90 ** 0.19 ** 1.80 ** 314.09 ** 2231939.50 ** Phosphate Biofertilizer (PB) 1407.20 * 172.50 ** 0.01 ns 0.94 * 285.30 ** 150.60 ns Planting Arrangement (PA) 5682.70 ** 3719.40 ** 0.03 ns 1.02 * 3.77 ns 3226900.00 ** WIXPB 2124.90 ** 752.40 ** 0.09 ** 0.91 * 42.80 ** 236226.10 ns WIXPA 113.50 ns 658.60 ** 0.06 ** 1.09 ** 57.30 ** 926873.05 * PBXPA 989.40 ns 516.90 ** 0.08 ** 0.02 ns 147.80 ** 74342.09 ns WIxPBxPA 3973.90 ** 204.12 ** 0.06 ** 0.57 ns 25.15 ns 53670.50 ns Error 335.60 17.23 0.01 0.23 9.32 257976.06 ns, * and **: Non significant and significant at the 0.05 and 0.01 level of probability, respectively The highest SY was obtained when weeds were controlled for all of the growing season (W0) and soybean was planted at the inter-row and inter-plant spacings of 25 and 10 cm, respectively (P2) whether phosphate biofertilizer was used or not (Table 2). For both planting arrangements, full season weedy condition (W3) and at the lack of the biofertilizer (I0) led to the lowest SY (Table 2). It seems that in weed free condition and a more uniform planting arrangement soybean yield is not significantly affected by phosphate biofertilizer due to a lower competition for this essential element. However, in the presence of weeds, phosphate biofertilizer could reduce the harmful effects of these unwanted plants. In general, soybean seed yield decreased when the weed interference period increased. Although, in most cases, the reductions were lower when soybean was planted as the P2 planting arrangement when compared with the P1 planting arrangement (Table 2). Row spacing and spatial uniformity can play important roles to manage weeds in cropping systems. Mohammadi et al. (2012) reported that corn yield was improved and weed biomass was decreased in response to decreasing row spacing. Moreover a more uniform crop spatial (as seen at the P2 planting arrangement) decreases competition within the crop population early in the growing season (Olsen and Weiner 2007) and maximizes the total shade cast by the crop by reducing self shading (Weiner et al. 2001). According to Kristensen et al. (2008) in the presence of weeds the highest yields were obtained with high spatial uniformity. The highest PPP was occurred in the plots in which weeds were removed throughout the growing season, phosphate biofertilizer was applied and soybean was planted as the P2 planting arrangement (Table 2). This can be attributed to the lack of weed harmful effects on the crop, more crop spatial uniformity and consequently a lower competition among the soybean plants. Moreover, many researchers have reported an improve in growth and P-uptake by crops through the inoculation of phosphate solubilizing microorganisms in pot experiments (Vassilev et al. 2006; Omar 1998) and under field conditions (Valverde et al. 2006; Duponnois et al. 2005; De Freitas et al. 1997). In a study, Mittal et al. (2008) observed two-fold increase in seed number of chickpea due to the use of phosphate solubilizing microorganisms. О 1 /Г The effects of planting arrangement and phosphate biofertilizer on soybean under different weed interference periods Table 2: Soybean plant traits as influenced by weed treatment, planting arrangement and phosphate biofertilizer Weed Planting Phosphate Soybean plant traits treatment arrangement biofertilizer Seed yield (g m-2) Pods/plant Seeds/pod W0 P1 I0 305.6 b 86.6 c 2.1 ef I1 319.3 b 66.3 d 2.3 cde P2 I0 323.3 ab 101.7 b 2.3 cde I1 346.9 a 117.1 a 2.4 abc W1 P1 I0 189.5 ef 55.3 fg 2.5 ab I1 206.9 de 63.5 de 2.4 abc P2 I0 239.3 c 68.8 d 2.5 ab I1 200.1 de 82.5 c 2.1 ef W2 P1 I0 161.3 gh 56.2 fg 2.1 ef I1 191.9 ef 43.2 i 2.2 def P2 I0 220.1 cd 63.0 de 2.4 abc I1 173.7 fg 52.4 gh 2.2 def W3 P1 I0 134.3 ij 49.2 h 2.1 ef I1 141.6 hi 38.4 ij 2.1 ef P2 I0 114.9 j 36.7 j 2.1 ef I1 182.9 efg 58.5 ef 2.2 def LSD (0.05) 26.1 5.9 0.2 Dissimilar letters at each column indicate the significant difference at the 0.05 level of probability (LSD test). Abbreviations: W0, W1, W2 and W3: full season weed free condition, weedy condition until soybean 4-trifoliate stage, weedy condition until soybean flowering stage and full season weedy condition, respectively. P1: soybean planted at the inter-row and inter-plant spacings of 50 and 5 cm, respectively; P2: soybean planted at the inter-row and inter-plant spacings of 25 and 10 cm, respectively. I0 and I1: no inoculation and inoculation with phosphate biofertilizer, respectively. The number of seeds per pod didn't show an obvious response to the treatments under study, although, in most cases, full season weedy condition and weedy condition until soybean flowering stage led to the lowest values of this trait (Table 2). Weed interference until 4-trifoliate stage didn't significantly influence 100-seed weight when compared with full season weed free condition, although, the longer weed interference reduced this yield component, notably (Fig. 1). However, for all of the weed treatments, the use of phosphate biofertilizer didn't significantly affect soybean 100-seed weight (Fig. 1). Moreover, for all weed treatments, 100-seed weight was higher when soybean was planted as the P2 planting arrangement (Fig. 2). Although, the positive effect of this planting arrangement on soybean seed mass was more obvious in the plots in which weeds were controlled throughout the growing season (Fig. 2). □ Without biofertilizer ■ With biofertilizer W0 W1 W2 W3 Weed treatments Figure 1: The effect of phosphate biofertilizer on soybean 100-seed weight under different weed treatments. Abbreviations: W0, W1, W2 and W3: full season weed free condition, weedy condition until soybean 4-trifoliate stage, weedy condition until soybean flowering stage and full season weedy condition, respectively. 12 10 Г 8 JZ 5? О ^ 6 ■a