ACTA « AGRICULTURAE SLOVENICA Biotehniška fakulteta Univerze v Ljubljani Biotechnical Faculty University of Ljubljana Acta agriculturae Slovenica • ISSN 1581-9175 • 103 - 1 • Ljubljana, marec 2014 Acta agriculturae Slovenica Volume / Letnik 103 • Number / Številka 1 • 2014 VSEBINA / CONTENTS Abdul -Mehdi S. AL-ANSARI, Mohammed A. ABDULKAREEM 5 Some plant extracts retarde nitrification in soil Nekateri rastlinski izvlečki upočasnjujejo nitrifikacijo v tleh Jure ČOP 15 Soil acidification and liming in grassland production and grassland soil fertility in Slovenia Zakisanje tal in apnjenje v travništvu ter rodovitnost travniških tal v Sloveniji Fahimeh DADASHI, Faezeh ZAEFARIAN, Rahmat ABBASI, Mohammad Ali BAHMANYAR, Mohammad REZVANI 27 Response of leaf area and dry matter of crop, weeds and cover crops to competition and fertilizer resources Odziv listne površine in suhe snovi poljščin, vmesnih posevkov in plevelov na kompeticijo in izrabo gnojil Luana FERNANDES, Nuno RODRIGUES, José Alberto PEREIRA, Elsa RAMALHOSA 37 Physico-chemical and sensory characteristics of jellies made from seven grapevine (Vitis vinifera L.) varieties Fizikalno-kemične in senzorične lastnosti želejev narejenih iz sedmih sort grozdja (Vitis vinifera L.) Andrej GREGORI, Franc POHLEVEN 49 Cultivation of three medicinal mushroom species on olive oil press cakes containing substrates Gojenje treh vrst medicinskih gob na substratih vsebujočih oljčne tropine Matjaž HLADNIK, Jernej JAKŠE, Dunja BANDELJ, Irma VUK 55 The characterisation of Vitis vinifera 'Refošk' with AFLP and SSR molecular markers and ampelographic traits Karakterizacija žlahtne vinske trte (Vitis vinifera L.) sorte 'Refošk' z AFLP in SSR molekulskimi markerji in ampelografskimi lastnostmi Matjaž HLADNIK, Dunja BANDELJ, Irma VUK 65 Autografted vines of cultivar 'Refošk' (Vitis vinifera L.) reveal symptoms of the rugose wood disease Pojav znamenj razbrazdanja lesa na cepljenkah s spojenimi lastnimi deli trsov sorte Vitis vimfern'Refoskk Mohsen JANMOHAMMADI, Zahed SUFI-MAHMOUDI, Amin AHADNEZHAD, Saeed YOUSEFZADEH, Naser SABAGHNIA 73 Influence of chemical and organic fertilizer on growth, yield and essential oil of dragonhead (Dracocephalum moldavica L.) plant Vpliv mineralnih in organskih gnojil na rast, pridelek in vsebnost eteričnih olj kačjeglavke (Dracocephalum moldavica L.) Niko PAVLIN, Zlata LUTHAR 83 The impact of plasmid on regeneration and expression efficiencies of gfp gene in tobacco (Nicotiana tabacum L.) Vpliv plazmida na uspešnost regeneracije in izražanja gfp gena v tobaku (Nicotiana tabacum L.) Maja PODGORNIK, Marina PINTAR 89 The effect of land use on phosphorus dynamics in golf course soil Vpliv rabe tal na dinamiko fosforja v tleh golfišč Naser SABAGHNIA, H.A. ASADI-GHARNEH, Mohsen JANMOHAMMADI 101 Genetic diversity of spinach (Spinacia oleracea L.) landraces collected in Iran using some morphological traits Genetska raznolikost akcesij špinače (Spinacia oleracea L.) zbranih v Iranu, določena z nekaterimi morfološkimi znaki Naser SABAGHNIA, Rahmatollah KARIMIZADEH, Mohtasham MOHAMMADI 113 Graphic analysis of yield stability in new improved lentil (Lens culinaris Medik.) genotypes using nonparametric statistics Grafična analiza stabilnosti pridelka novih izboljšanih genotipov leče (Lens culinaris Medik.) z uporabo neparametrične statistike Mojca VIRŠČEK MARN, Irena MAVRIČ PLEŠKO, Denise ALTENBACH, Walter BITTERLIN 129 Sensitivity of field tests, serological and molecular techniques for Plum Pox Virus detection in various tissues Občutljivost hitrih testov, seroloških in molekularnih tehnik za detekcijo virusa šarke v različnih tkivih Blaž GERMŠEK, Tatjana UNUK 137 Kakovost jabolk sort 'Gala Brookfield' in 'Fuji Kiku 8' pod in izven protitočne mreže Quality of cv. 'Gala Brookfield' and 'Fuji Kiku 8' apples grown under and outside hail net Tomaž BARTOL, Karmen STOPAR 145 Content analysis of the papers in the Acta agriculturae Slovenica Vsebinska obdelava prispevkov v Acta agriculturae Slovenica let. 103 št. 1 149 In memoriam: Jože Korošec (1930-2013) 153 Navodila avtorjem Notes for authors DOI: 10.14720/aas.2014.103.1.01 Agrovoc descriptors: plant extracts, nitrification, nitrification inhibitors, soil, urea COBISS Code 1.01 Agris category code: p33, p35 Some plant extracts retarde nitrification in soil Abdul -Mehdi S. AL-ANSARI1, Mohammed A. ABDULKAREEM1 Received May 11, 2013; accepted August 27, 2013. Delo je prispelo 11. maja 2013, sprejeto 27. avgusta 2013. ABSTRACT An incubation experiment was conducted to evaluate the effect of aqueous extracts of 17 plant materials on nitrification inhibition of urea- N in soil as compared with chemical inhibitor Dicyandiamide (DCD). Plant materials used in study were collected from different areas of Basrah province, south of Iraq. Aqueous extracts were prepared at ratio of 1:10 (plant material:water) and added at conc. of 0.05, 0.10 and 0.20 ml g - 1 soil to loamy sand soil. DCD was added to soil at rate of 50 ^g g-1 soil . Soil received urea at rate of 1000 ^g N g-1 soil. Treated soils were incubated at 30OC for 40days. Results showed that application of all plant extracts, except those of casuarina, date palm and eucalyptus to soil retarded nitrification in soil. Caper, Sowthistle ,bladygrass and pomegranate extracts showed highest inhibition percentage (51,42,40 and 40% Respectively) and were found to be more effective than DCD (33%). Highest inhibition was achieved by using those extracts at conc. of 0.1 ml g-1 soil after 10 days of incubation . Data also revealed that treated soil with these plant extracts significantly increased amount of NH4+-N and decreased amount of NO3--N accumulation in soil compared with DCD and control treatments. Results of the study suggested a possibility of using aqueous extracts of some studied plants as potent nitrification inhibitor in soil. Key words: nitrification inhibitor, plant extract , inorganic nitrogen IZVLEČEK NEKATERI RASTLINSKI IZVLEČKI UPOČASNJUJEJO NITRIFIKACIJO V TLEH V inkubacijskem poskusu je bil ovrednoten vpliv 17 vodnih rastlinskih izvlečkov na inhibicijo nitrifikacije dušika v urei primerjalno s kemijskim inhibitorjem diciandiamidom (DCD). Uporabljen rastlinski material je bil nabran na različnih območjih province Basrah v južnem delu Iraka. Vodni izvlečki so bili pripravljeni v razmerju 1:10 (rastlinski material:voda) in dodani v koncentracijah 0.05, 0.10 in 0.20 ml g - 1 ilovnato-peščenim tlem. DCD je bil dodan tlem v razmerju 50 ^g g-1 tal, urea pa v razmerju 1000 ^g N g-1 tal. Tretirana tla so bila inkubirana pri 30O C 40 dni. Rezultati so pokazali, da je uporaba rastlinskih izvlečkov upočasnila nitrifikacijo v tleh, razen pri izvlečkih kazaurine, dateljeve palme in evkalipta. Izvlečki kaprovca, škrbinke, trave (Imperata cylindrica (L.) P.Beauv) in granatnega jabolka so se izkazali za bolj učinkovite inhibitorje (51, 42, 40 in 40 % inhibicija) kot DCD (33 %). Največja inhibicija je bila dosežena z uporabo izvlečkov v koncentraciji 0.1 ml g-1 tal, pri inkubaciji 10 dni. Rezultati so tudi pokazali, da se je v tleh obravnavanih s temi izvlečki značilno povečala količina NH4+-N in zmanjšala količina NO3--N v primerjavi s tlemi, obravnavanimi z DCD in kontrolo. Rezultati te raziskave nakazujejo možnost uporabe izvlečkov preučevanih rastlin kot potencialnih inhibitorjev nitrifikacije v tleh. Ključne besede: inhibitorji nitrifikacije, rastlinski izvlečki, anorganski dušik 1 INTRODUCTION Prilled urea is the main source of N fertilizer applied to soil. In tropical agriculture, it accounts for about 49% of total fertilizer N use (Byrnes and Freney , 1995 ). Urea applied to soil, is hydrolyzed by urease enzyme to form NH4 + which is subsequently converted to nitrate (NO3-)through nitrification process (Kiran and Patra,2003) . The NO3" is subject to losses either through percolation of soil water or as nitrogen gases or nitrogen oxides through denitrification process (Mikkelsen et.al.,1978;Katyal et al.,1985). Excessive loss of N due to NO3" leaching or loss through 1 Dept.Soil and Water Resources,Coll. Agric.,Univ.Basrah, Basrah,IRAQ, Corresponding author :ansari 542000@yahoo.com denitrification in addition to other ways of N losses from soil environment results in very poor recovery of applied nitrogen (Yadav and Mohan,1982). To increase nitrogen fertilizer use efficiency, several approaches have been tried. These include: use of slow release fertilizers (Malhi et al., 2003), addition of salts and acids with urea (Sloan and Anderson , 1995) and use super granules urea (Shah and Wolfe,2003). In addition to that, several chemicals such as N-serve(nitrapyrin), dicyandiamide(DCD) and many other chemicals have been applied to retard urea hydrolysis or nitrification in soil (Kiran and Patra,2003) . In spite of the encouraging results obtained with the use of these chemicals in retarding urea hydrolysis and nitrification their use is limited to experimental one due to high cost, and risk of adverse effect on beneficial soil micro flora (Vyas et al.,1993) and risk of soil and water pollution(Kiran and Patra,2003). Erickson et al. (2000) reported that plant in mature stages produce numerous organic compounds that can inhibit autotrophic nitrifiying organisms, even at low concentration in soils. Other workers reported experimental evidence for roles of root exudates and leachates of plants under climate vegetation inhibit nitrification in soil (Paavolainen et al., 1998; Jafari and Kholdebarin,2002). On the other hand, Purchase(1974)and Johnson and Edwards(1979)found no evidence of nitrification inhibition from root exudates or variety of plant extracts. Literatures reviewed above showed inconsistent results of the effect of plants extract on nitrification in soil. Hence, a comprehensive study was conducted to investigate effect of aqueous extracts of 17 natural plant materials on urea N transformations in soil as compared with the synthetic chemical nitrification inhibitors (i. e. DCD). The purpose of this paper is to report effect of these extracts on nitrification of urea - N. 2 MATERIALS AND METHODS Soil and plant materials : Soil used in the experiment was loamy sand collected from tomato field, located at AL-Burjsia area, Basrah province, south of Iraq. The soil classified as Entisol; Typic Torripsamment. Soil samples were collected from surface layers (0-30cm), air dried and sieved (2 mm). Some physical and chemical properties of the soil were determined following procedures described in Page et al. (1982) and presented in table (1). Plant materials used in study were collected from different areas from Basrah province and described in in table (2). Selected plant materials were cleaned, air dried and grounded to pass 1mm sieve then kept in plastic bags at room temperature (25 C) and humidity (35%) until use. To get aqueous extract, 10 g of ground dry material was mixed with 100 ml of distilled water and horizontal shake for six hours. The homogenate was filtered through tissue paper to separate large particles, and then the filtrate was filtered further using Whatman filter paper No. 1. This process was repeated several times to collect enough quantity of extract. The filtrate was used as stock solution. Some plant extracts retarde nitrification in soil Table 1. Some physical , chemical and biological properties of soil used. Prop. Symbol Value pH (1:1 in water) - 8.05 E. C. dS m-1 2.30 CaCO3 g kg-1 75.00 CEC Cmole (+) kg-1 3.40 P (NaHCO3) mg kg-1 5.60 Total N g kg-1 0.03 Organic C g kg-1 0.40 Organic matter g kg-1 0.70 C:N Ratio - 13.3 Urease activity ^g NH4+/g Soil/2h 2.3 NH,+ - N ^g g-1 1.57 NO3- N 0.61 NO2- N 0.00 Ca+2 m M L-1 5.40 Mg+2 3.00 Na+ 6.50 K+ 1.02 hco3 2.00 SO4= 8.50 Cl 7.00 CO3" 0.00 Loamy Sand Sand g kg-1 866.00 Silt 51.96 Clay 82.04 Table 2. : Plants used in study Common name Latine name Sampling part Sampling date Zizyphus Ziziphus mauritiano Lam. CV. Zaitoni leaves Oct. Ziziphus spina — christi (L.) Willd. leaves Oct. Colacynth Citrullus colocynthis (L.) Schrod. Fruits Nov. Caper Capparis spinosa L. Seeds Oct. Casuarina Casuarina equisetifolia L. Stem bark Jan. Bead tree Melia azedarach L. Fruits Oct. Pomegranate Punica granatum L. Peels Jan. Cotton Gossypium herbaceum L. roots Jan. Bermudagrass Cynodon dactylon (L.) Pers. rhizomes Feb. Bladygrass Imperata cylindrica (L.) Beauv. rhizomes Feb. Sowthistle Sonchus oleraceus L. Total shoot Mar. Wheat Triticum aestivum L. bran Jul. Date palm Phoenix dactylifera L. CV. Zehdi Leaves Fiber Dec. Feb. Oleander Nerium oleander L. leaves Apr. Eucalyptus Eucalyptus camaldulensis Dehnh. leaves Apr Myrtus Myrtus communis L. leaves Apr. Nitrification inhibition : Sample of sieved soil was washed with enough 0.01 N KCl to leach out the inorganic forms of nitrogen present in soil. Leached soil was air dried, then 5 g of dried soil was placed in plastic containers (capacity 20ml). Soils in plastic containers were treated with solutions contain urea(at rate of 1000 ^g Ng - 1 soil) and test solutions (at rates of 0.05, 0.10 and 0.20 ml gm-1soil) . To compare the effect of plant extracts on nitrification on soil with synthetic chemical inhibitor (i. e. dicyandiamide, DCD), set of containers was treated with solution contain 250 ^g of DCD (50 ^g DCD gm- 1 soil) and urea at rate of 1000 ^g N g - 1 soil. Soil of control treatments was treated with solution contains only urea at the same rate as that of other treatments. The moisture content of all treatment was maintained at field capacity during the study period. Treatments were triplicated and incubated at 30oC. Set of samples was withdrawn at 10 days and other at 40 days after amendment of extracts and urea . Soils were extracted with 2 M KCl , then the extracted amount of NH4+ , NO2" and NO3" were determined following procedure of Bremner and Edwards(1965).Percentage inhibition of nitrification was calculated according to Bremner and McCarty (1988) : % inhibition = C - T C aoo .(1) T = NO2- + NO3- in treated soil C = NO2" + NO3" in control soil E.C. and pH determination To reveal the effect of plant extracts on soil electrical conductivity(E.C.) and acidity (pH), fifty grams of soils amendment with plant extracts( that showed most effect on nitrification) and urea at rate of 1000 ^ N g-1 were placed in plastic containers, then incubated at 30o c for 40 days. Soil moisture was adjusted to field capacity during incubation periods. Set of samples was withdrawn after 2,4,8,10,25,and 40 days after incubation and soil E.C. and PH were determined. Statistical analysis,: The experiment was designed as factorial experiment with three variables (plant extract x extract concentration x incubation period) with three replicates. The results were analyzed using analysis of variance carried out by SPSS11 (Agyrous,2005). Differences among means were compared using revised LSD test. 3 RESULTS Nitrification inhibition : Data in table (3) show that application of all plant extracts, except those of casuarina, date palm and eucalyptus, to soil reduced nitrification of urea - N during incubation periods of 10 and 40 days. However, the persistence of the inhibitory effect of these extracts on nitrification decreasing with increasing incubation time from 10 to 40 days. Data indicated that degree of nitrification inhibition in soil differs with source and concentration of the extracts used . Retardation of nitrification caused by extracts of caper, sowthistle, bladygrass and pomegranate were higher than that of DCD treatment. The highest retardation was achieved by using extracts of the plants at concentration of0.1 ml g - 1 after 10 days of incubation. The inhibition percentages were 51,40 ,40 and 42% for caper, pomegranate, bladygrass and sowthistle, respectively as compared to 33% for DCD treatment . Statistical analysis of treatments is shown in table (4). Inhibition effects of other plant extracts were either lower (Zizyphus, bermudagrass and oleander) or did not significantly differ (sowthistle, colacynth, bladygrass and bead tree) from that of DCD treatment. Table 3: (%) inhibition of nitrification in soil treated with different concentrations of plant aqueous extracts after 10 and 40 days of incubation. Conc. \(ml gm - 1 soil) Plant After 10 days of incubation After 40 days of incubation G.G5 G.1G G.2G mean G.G5 G.1G G.2G Mean Zizyphus (CV. Zaitoni ) G i5 3G i5 G G i8 6 Zizyphus ( Willd ) G 39 38 25.6 G iG i5 5 Colacynth 26 34 34 31.3 2i 16 5 i4 Caper 46 5i 46 47.6 5 2i i6 i4.GG Casuarina G G iG 3.3 5 G 5 3.3 Bead tree 36 3i 32 33 26 i6 5 i5.6 Pomegranate 34 4G i4 29.3 26 32 32 3G.G Cotton G 36 38 24.6 G i6 5 7 Bermudagrass 39 24 3i 31.3 6 i6 2i i7.6 Bladygrass 39 4G 4G 39.6 G iG i6 8.6 Sowthistle 4G 42 36 39.3 G 5 G i.6 Wheat G 37 3G 22.3 G G G G Date palm (leaves ) G 35 29 2i.3 G G G G Date palm ( fiber ) G G G G G G G G Oleander G 2G 28 i6.G 5 iG 5 6.6 Eucalyptus G 6 G 2 G G 5 i.6 Myrtus 36 35 33 34.6 5 G 5 3.3 DCD 33 33 iG iG iG iG Mean i8.2 28.7 27.8 24.9 6.6 9.G 9.G5 8.21 L.S.D. G.Gi plant extracts(p) =2.8i, Conc. of extract(c) =i.i4, incubation time (t) =* pxc = 4.87, pxt = 3.98, cxt = i.62, pxtxc = 6.89 C.V = 9.25 Inorganic N accumulation : Table (4) shows the amount of inorganic N (NO2", NO3- and NH4+) accumulated in soils treated with DCD or aqueous extracts of caper, sowthistle, bladygrass and pomegranate after 10 and 40 days of incubation as compare to control treatment. Data in the table indicated that treated soils with these plant extracts significantly increased amount of NH4+- N accumulated in soils comparing with that of DCD. Caper, sowthistle, bladygrass and pomegranate maintained 220.97, 207.57, 193.84 and 212.14 mg NH4+- N kg 1 soil as compared with 182.14 mg NH/-N kg - 1 soil at DCD treatment after 10 days of incubation. The amount of NH4+-N accumulated in control soil at that time was 149.73 mg NH+ - N kg - 1 soil. However, the amount of NO3 - - N produced in soils treated with these plant extracts was lower than these of DCD or control treatments. Plant extracts or DCD effects on NO3 -- N produced was much lower at 40 days than 10 days of incubation . No NO2 -- N was detected at any of the treatments involved in the study. E.C. and pH : The effect of caper , sowthistle , bladygrass and pomegranate extracts on soil E.C. and pH as compared with control are presented in (Fig. 1 and Fig.2). Fig. (1) shows that plant extracts increased E. C. of treated soils from 2dSm-1 at control treatment to about 4dSm-1 at early period of incubation. However, effect of all plant extracts on E.C. decreased as time of incubation increased. Fig. (2) shows that soil pH of all treatments were close to that of control treatment during the incubation period (40 days) and was in the range of 7.9 to 8.3. Table 4: NH4+, NO2- and NO3- (mg Kg 1 soil) released from soil treated with plant aqueous extracts after 10 and 40 days of incubation . After 10 days of incubation After 40 days of incubation treatments NH4+-N NO2" - N NO3" - N NH4+-N NO2" - N NO3" -N Control 149.73 0 46.64 21.45 0 17.72 Caper 220.97 0 22.95 24.66 0 13.99 Sowthistle 207.57 0 27.05 22.39 0 16.79 Bladygrass 193.84 0 27.99 22.39 0 15.86 Pomegranate 212.14 0 27.98 23.63 0 12.12 DCD 182.14 0 31.25 21.45 0 15.86 RLSD0.01 NH4+ -N = 8.16 NO3- N = 2.3 C.V 15.40 12.33 S 3 US 3 U 2 M RLSD0.01= 0.026 10 15 20 25 Incubation (days) 30 35 Caper ♦ Sowthist ■ Bladygrass ▲ Bomegrana • Control x 40 —i 45 Figure 1: Effect of plant aqueous extracts on soil E.C. at different incubation periods. 5 4 1 0 0 5 Figure 2: Effect of plant aqueous extracts on soil pH. at different incubation periods. (L.S.D 0.01 = 0.023) 4 DISCUSSION AND CONCLUSION Nitrification inhibition and inorganic N accumulation: Several chemical such as DCD , N-serve(DowElanco, USA) , and other have been tried to reduce urea hydrolysis or nitrification in soil in order to increase N-fertilizer efficiency . However, use of such chemicals may have adverse influence on soil micro flora and soil and water pollution(Trenkel,1997) . As early as 1952, Steiven reported presence of naturally occurring substances mostly in higher plants when introduced into soil delay nitrification. Since then interest in using of organic compounds produced and released by plants to control nitrification in soil has increased. However, inconsistent results of effect organic compounds on nitrification have been reported . In this study, selected plants or parts of plants were tested for their effect on nitrification of urea-N in soil. Results of the study showed application of most of studied plants indicated possibility of retarding nitrification of urea-N and the persistence of the inhibitory effect decreased with the time, however, degree of nitrification inhibition differs with source and concentration of the extracts used . Data of Hardy and Sevasithamparam (1989) showed negative effects of added eucalyptus bark on soil microorganism decreased with time. Organic compounds in soil could be volatilized, leached, or converted to non-toxic products as time elapse (Alexander , 1985) . Comparing with chemical nitrification inhibitor (i. e. DCD ) retardation of nitrification caused by extracts of plants under study were higher/lower than, or did not differ from that of DCD. Nitrification inhibitory properties of plant materials such as Karenj (Pongemia glebra) neem (Azadirachta indica) and tea (Camellia sinensis) have been reported (Kiran and Patra ,2003). White (1991) and Paavalainen (1998) reported that introducing water or ethanol extracts of plants contain phenolics, monoterpenes, and other organic compounds into soil exert allelopathic effect on nitrification in soil . Ito and Ichikawa (1999) suggested that D. adscendens roots release substances that inhibit not only the growth of other plants and Rhizobium nodulation, but also the nitrifiers activities in soils .On other hand, Kholdebarin and Oertli (1992) and Bremner and McCarty (1988,1993) revealed that any decrease in the amount of NO3- N produced during nitrification in the presence of cotyledon powder or climax vegetation could be due fixation, volatilization and immobilization of nitrification substrate by organic materials such as phenolics or other compounds released into soil , rather than to their effect on nitrifying bacteria . Whatever, might be the mechanism of their action aqueous extracts of caper , sowthistle , bladygrass and pomegranate plant used in this study showed higher inhibitory effect on urea - N nitrification in soil than that of chemical inhibiter (i.e. DCD). Data in table (5) supported this conclusion by showing that the amount of NH/-N accumulated in soil treated with these plant extracts was significantly higher and the amount of NO3-- N accumulated was significantly lower than those of DCD or control treatments at early period of incubation . E.C. and pH: Since soil E.C. and pH are among factors controlling nitrification in soil (Alexander, 1985) , the effect of studied plant extracts on these parameters as compared with control were studied (Fig. 1 and Fig. 2) . Results in Fig. (1) Showed that, treating soils with plant extracts increased soil E.C. during early periods of incubation, however, this effect decreased as time of incubation increased. Data in table(3) showed that persistence of the inhibitory effect of plant extracts used in this study decreased with increasing incubation time from 10 to 40 days. Hence, inhibitory effect observed in this study could partly due to increased salinity of treated soils caused by plant extracts during early periods of incubation. Kumar and Wagenet (1985) and Jarallah (1998) reported negative correlation between salinity and nitrification in soil. On other hand, other studies showed that increasing soil salinity from 3 to 12 dSm-1 ( Jabari,1989; Al-Rashdi et al.,1991) and increased salt concentration up to 0.01 M (Agrawal et al., 1971) or 0.22% (Laura, 1979) increased nitrification in soil. 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Biogeochem. 12: 43 - 68, DOI: 10.1007/BF00002625. Yadav, R. L. and R. Mohan. 1982. Physiological analysis of methanol yield variation in Mentha arvensis L. under different rates of nitrogen application. Indian perfume. 26: 94 - 98 . COBISS Code 1.02 DOI: 10.14720/aas.2014.103.1.02 Agrovoc descriptors: grassland soils, acidity, chemicophysical properties, liming, soil management, soil improvement, soil fertility, growth rate, grasses, yields, botanical composition, nutritive value, quality Agris category code: p35 Soil acidification and liming in grassland production and grassland soil fertility in Slovenia Jure ČOP1 Received January 24, 2014; accepted March 10, 2014. Delo je prispelo 24. januarja 2014, sprejeto 10. marca 2014. ABSTRACT This paper reviews the evidences on grassland soil acidity and liming in relation to soil processes and herbage production. There is also an outline of the present state of soil acidity and acidity-related traits - contents of organic matter (OM), phosphorus (P) and potassium (K) in Slovene grassland. In grassland, soil acidification is an ongoing process under humid climate conditions. It is mainly driven by leaching of nutrients, net loss of cations due to retention in livestock products, use of physiologically acid fertilizers, acid rain and N2 fixation. This process is reduced by strong pH buffering capacity of the soil and by physiologically basic fertilizers. Acid grassland soils in Slovenia are widely distributed in spite of the fact that 44% of the total land has developed from a carbonate parent material. Of the 1713 grassland soil samples analysed during 2005-2007 45% were regarded as acid ones (pH < 5.5; in KCl), 57% as soils with very low P status (< 6 mg P205/100 g soil) and 22% as soils with very low K status (< 10 mg K20/100 soil). Increased content of soil organic matter was identified for alpine pastures (> 10% OM in 44% of samples), mainly as a result of low decomposition rate. Liming of acid grassland soils did not always reflect in a higher herbage yield. The cause for this inefficiency is plant composition of grassland. Thus, many grassland plants with relatively high production potential have adapted to acid soil conditions. To illustrate the inconsistent liming effect three researches are reviewed. In the first two researches liming along with fertilizer application did not increase the yield comparing to the fertilized control while in the third research the increase amounted 26%. Liming improves considerably botanical composition of the acid grassland (e.g. sward where Common Bent - Agrostis tenuis Sibth. - prevails) and thus indirectly affects palatability and nutritive value of herbage. Grassland liming has a weak direct effect on herbage quality - it usually increases content of Ca and sometimes decreases Mg in herbage. The latter effect is rare. In Slovenia, ameliorative liming is advised for grassland soils with pH < 5.0 and maintenance liming for grassland soils with pH < 6.0 (pH in KCl or CaCb). Key words: grassland, soil acidity, liming, herbage yield, Slovenia IZVLEČEK ZAKISANJE TAL IN APNJENJE V TRAVNIŠTVU TER RODOVITNOST TRAVNIŠKIH TAL V SLOVENIJI Pregledni članek obravnava kislost travniških tal in apnjenje v povezavi s procesi v tleh in pridelavo travniške krme. Dodan je zgoščen prikaz kislosti ter s tem povezane vsebnosti organske snovi, fosforja in kalija v travniških tleh v Sloveniji. Zakisanje travniških tal je v vlažnem podnebju stalen proces, ki je odvisen predvsem od izpiranja hranil, negativne bilance hranil zaradi odvzema, uporabe fiziološko kislih gnojil, kislega dežja in biotske fiksacije N2. Zakisanje tal po drugi strani pomembno zmanjšujejo puferski mehanizmi v tleh in nekatera gnojila. Razširjenost kislih travniških tal v Sloveniji je velika, kljub temu, da ima 44 % zemljišč karbonatno podlago. Od 1713 vzorcev travniških tal je imelo 45 % pH vrednost pod 5,5 (v KCl), 57 % zelo malo fosforja (< 6 mg P2O5/IOO g tal) in 22 % zelo malo kalija (< 10 mg K20/100 g tal). Vsebnost organske snovi je povečana na planinskih pašnikih (> 10 % OS v 44 % vzorcev) predvsem zaradi slabe razgradnje. Apnjenje kislih travniških tal vedno ne poveča pridelka krme. Razlog za to je v travniških rastlinah, ki dobro prenašajo kisla tla, a imajo obenem razmeroma velik rastni potencial. V zvezi s tem so predstavljene tri raziskave, v dveh apnjenje skupaj z gnojenjem ni povečalo pridelka v primerjavi z gnojenimi kontrolami, v enem pa je pridelek povečalo za 26 %. Apnjenje pomembno izboljša botanično sestavo acidofilne travne ruše (npr. ruša s prevladujočo lasasto šopuljo - Agrostis tenuis Sibth.) in s tem posredno vpliva na okusnost in hranilno vrednost krme. Neposredni vpliv apnjenja na kakovost krme je razmeroma majhen - običajno poveča vsebnost Ca v krmi, lahko pa tudi zmanjša vsebnost Mg. Slednji vpliv je redek. Za Slovenijo stroka priporoča meliorativno apnjenje travniških tal s pH < 5,0 in vzdrževalno apnjenje tal s pH < 6,0 (pH v KCl ali CaCl2). Ključne besede: travništvo, kislost tal, apnjenje, pridelek zelinja, Slovenija 1 Asist. prof., Dr., University of Ljubljana, Biotechnical Faculty, Jamnikarjeva 101, SI-1000 Ljubljana, jure.cop@bf.uni-lj.si 1 INTRODUCTION Soil acidity expressed as a pH value can importantly influence plant growth in grassland. Much of agricultural plants actively grow in the pH range between 4.0 and 8.5 but not at the same rate throughout the interval (Whitehead, 2000). Optimal pH value for grassland soil has much narrower interval and differs among grassland species. In spite of these differences, there is a uniform optimal pH value for grassland which differs among countries. Different methods for pH Table 1: Optimal and target pH value for grassland soils i determination represent the key reason for this. Therefore it should be taken into account when dealing with a pH soil value. Table 1 shows some recommended soil pH values for grassland in particular countries. The extraction media used for soil pH determination are also denoted. Grassland soils with non-optimal pH value are usually acid and this is generally true for the situation in Slovenia. Slovenia and in some other countries. pH (in KCl or CaCl2) pH (in water) Source Slovenia 5.0-5.5 (6.0) - Leskosek, 1987 Austria 5.0-6.0 - BMLFUW, 2006 Swiss - 5.5-6.7 GRUDAF, 2009 Germany 4.7-6.1 - Wendland in sod., 2011 United Kingdom - 6.0 DEFRA, 2010 Ireland - 6.2 (6.5) Tunney in sod., 2010 New Zealand - 5.5-6.3 Sparling in sod., 2008 Note: Soil pH values measured in solution of potassium chloride or calcium chloride are very similar, while those values measured in water are higher than the formers. There is no linear correlation between the results of the first two methods and the third one. 2 GRASSLAND SOIL ACIDIFICATION Acid soils occur mainly in areas with humid climate and are the most widespread in forest and grassland habitats. After von Uexkulla and Muterta's (1995) estimation, the world's area with acid soils counts 3950 million ha. Of this, 67% is covered by forest, 18%by grassland vegetation and 4.5% by arable crops. In addition to climate development of acid soil is also affected by the parent materials. Soils with silicate parent materials are usually more acid than those with carbonate ones. Acidity of the latter soils is of secondary origin and results mainly from leaching of base cations through soil profile. Soil acidification results from mass flow and interrelated biochemical processes in grassland ecosystems. The most important flows consist in one hand of loss of mineral nutrients due to leaching and yield removal and in the other hand of input of matters from fertilizers, rainwater and lithological basis. Chemical processes involved in soil acidifications are mainly occurring during the nitrogen cycling and less importantly during carbon and sulphur cycling. In general soil acidification is more pronounced on grassland than on arable land. In Europe the main reasons for this accelerated acidification is connected with geographic position, soil properties and management of grasslands. Grassland here prevails in uplands and mountain areas, i.e. the altitude belt between 700 and 1900 m a.s.l. Meadows and pastures in these areas are usually sloping and have porous and shallow soils. It causes these soils to be prone to soil erosion and leaching of plant nutrients (e.g. NO3-, Ca2+, Mg2+) through soil profile, thus leading to soil acidification. These shortcomings can also occur in grassland of low-laying areas in Europe. Soil acidification in the extensive grassland production is partly caused by insufficient fertilizer application. Increased removal of mineral cations with grassland fodder, which is not matched by fertilizer application, leads to the excess of H+ ions in the soil and consequently lowering the pH value (de Klein et al, 1997). Fertilizer application influences on soil pH value when using physiological acid or alkaline fertilizers. The former type (e.g. ammonium sulphate and urea) acidifies the soil while the latter one (e.g. Thomas phosphate) has the reverse effect. Soil acidification may also result from acid rain (pH < 5.6) containing SO42-, NH4+ in NO3-. Among these ions, the ammonium ion is the critical acidification input (Bini and Bresolin, 1998). Austrian experimental results on liming and fertilizer application (Schechtner, 1993) show the importance of these three groups of matter flows for grassland soil pH value. In a 2-cut grassland experiment soil pH (CaCl2) fell from 5.8 to 4.7 in 44 year period under zero fertilizer treatment. In another 4-cut experiment, which was fertilized with recommended amounts, the physiological neutral PK fertilizer and physiological acid fertilizer (N in the form of urea) declined soil pH from original 5.6 to 4.5 and 4.2 respectively in 17 year period. In addition to mass flow, soil pH affecting processes occur during the cycling of carbon, nitrogen and sulphur (Bolan et al, 1991). In the case of the carbon cycle, the source of H+ ions is carbonic acid, formed by the reaction of CO2 with water, and carboxylic acids. However, these two sources of soil acidification are less important if the soil is aerated to allow diffusion of CO2 through air-filled pores (Marschner, 1986). Of the other two cycles, nitrogen cycle is much more important for soil acidification because its cycling within an ecosystem is roughly ten times faster than the sulphur cycling. Besides, NO3- for soil acidification compared to SO42- is more important due to its higher leaching loss in some soils. Basic cations which leach together with NO3- are replaced by H+ ions on colloids and the soil solution. Hydrogen ions are generated in a ratio 1 H+ to 1 N in the metabolism of urea to NH4+ (ammonification) and then to NO3- (nitrification). Metabolism of urea is important factor for higher tendency to acidification of grassland soil compared to the arable one (Whitehead, 2000). It generally occurs to a greater extent under grassland than under arable crops. Important factor for potential acidification of the soil is also biological nitrogen fixation where legumes and rhizobia are involved. In this process assimilation of NH3 into amino acids (aspartate and glutamate) generates H+ by their dissociation. In a case study, Bolan et al (1991) calculated the acidification rate for two farms in New Zealand and one in Australia which was caused mainly by biological nitrogen fixation. First two farms grazed their livestock herds on ryegrass-white clover pastures, and the third one did the same on Verano stylo monoculture (Stylosanthes hamata L.). Proportion of biologically N2 fixed in the systems ranged from 91 to 95%. Their results show the net input of H+ ion into the surface soil in the order of 8 kmol/ha and per year for the first two farms and 1 kmol/ha and per year for the third one. Taking into account a short term pH buffering capacity of 30 kmol/ha for two soil types for Australia it may take 12 years to cause a drop in pH of one unit from 6 to 5 for the New Zealander farms and 30 years for the Australian farms. The importance of biological N2 fixation is shown by the experimental results of Mengel and Steffens (1982). In their pot experiments, the soil pH value (in KCl) under red clover (Trifolium pratense L.), which was completely supplied with N by biological fixation, dropped from 7.2 to 4.5 in 14 month period. In the control, where perennial ryegrass (Lolium perenne L.) grew with the addition of ammonium nitrate (NH4NO3), the soil pH value remained unchanged. Hydrogen cations required for the decreasing of soil pH value under red clover derived from the plants to the extent of 60%. In relation to the latter experiment, it should be noted that the proportion of legumes in the sward and N2 fixation rate are different in grassland practices. In the case when this proportion and/or N2 fixation are low, the impact on soil pH can be negligible. Also, pH buffering capacity in the soil under field conditions is usually much higher than that in the case of pot experiments. Therefore, the effect of legumes on the soil pH reported by Mengel and Steffens (1982) is hardly probable to occur in the real situation. An example of very high buffering activity can be found in the article of Murphy et al. (2005). The results of 32 year field experiment about the impact of slurry application on the cation balance of the grassland soil in Northern Ireland show that the use of extremely high amount of slurry (200 m3/ha and per year; 4,76 % dry matter, 0,27 % N) did not decrease the soil pH value. Instead, it even slightly increased compared to unfertilized control. In this case, buffering activity of both soil and applied slurry surpassed acidifying activity of nitrogen in excess of crop need in the system. The ammonia volatilization and denitrification also affect the pH value of the soil. In the first process H+ ions in the soil increase while in the second one they decrease. The importance of NH3 volatilization and denitrification for soil pH value is generally difficult to define due to large diversity of measured values obtained experimentally. Much information on these two soil pH factors can be found in the monograph of Whitehead (1995). 3 THE PH VALUE AND RELATED PROPERTIES OF GRASSLAND SOILS IN SLOVENIA Published data of the Agricultural institute of Slovenia were used for the assessment of grassland soil fertility in Slovenia on the basis of key indicators (Susin, 2008a, 2008b, 2008c). In a comprehensive survey of soil fertility in Slovenia 1713 grassland soil samples were analysed in the period from 2005 to 2007. Of which 1215 samples were taken from meadows, 323 samples from lowland and hilly pastures and 139 samples from mountain pastures. All of these samples were taken on the depth of 0 to 6 cm. A large number of samples taken and a good dispersion of sampling sites allowed generalized conclusions that refer to the entire country. As expected, acid grassland soils prevail in Slovenia (Figure 1). Taking into account that the optimal pH (in KCl) for the grassland soil is between 5 and 6 and that good growth of sward occurs also in neutral soils (pH 6.6 to 7.2), it can be concluded that over quarter of mountain pastures (pH < 4.6) and less than one fifth of meadows and of lowland and hilly pastures have an inadequate pH value. All grassland soils placed in the lower part (pH 4.6 to 5.0) of the acid soil class have also an inadequate pH value, but their proportion is not clear from the published data. Increased soil acidity is emphasized in mountain pastures as a result of the geographic position of these pastures, shallowness and permeability of the soil and the low use of fertilizers. The content of organic matter in grassland soil of Slovenia is mostly within the normal limits (4 to 10%; Figure 1). Mountain pastures are an exception to this, because the organic matter content of almost half of them is more than 10%. The increased organic matter content is associated with drought conditions and cold weather as well as the soil acidity and excreta of grazing livestock. Accumulation of the root material together with other dead plant material in the soil reduces the productivity of sward. The importance of the soil pH for the mineralization of organic matter is showed by Silvertown et al. (2006). They found 3% of carbon in the soil layer from 0 to 23 cm in the case of unfertilized sward and sward fertilized with sodium nitrate (NaNO3), where the soil pH was between 5.0 and 5.6. Sward fertilized with ammonium sulphate ((NH4)2SO4) with the soil pH between 4.1 and 3.6 contained from 4.8 to 6.6% of carbon, respectively. Soil acidity in Slovene conditions is a synonym for the poor supply of the soil with plant nutrients. This is especially true for grassland soils (Figure 2). Analysed soil samples were very poorly supplied with available phosphorus, i.e. as many as 58% of samples contained less than 6 mg P2O5 per 100 g of soil (AL method). Acidity of the soil contributes significantly to this poor supply of the soil with phosphorus. It is well known that the availability of phosphorus in the acid soil is reduced due to high amount of aluminium cations (Al3+) adsorbed to clay participles (Whitehead, 2000). Figure 1: Distribution of soil samples from grassland into 5 categories according to the acidity (pH value) and content of organic matter. The pH classes: very acid, acid, moderately acid, neutral and basic soil. The samples were taken during 2005-2007, n = 1713 (1251, meadows; 323, pastures; 139, alpine pastures; Susin, 2008a, 2008b, 2008c). Figure 2: Distribution of soil samples from grassland into 5 categories according to the status of phosphorus (P2O5) and potassium (K2O). The classes: A - low, B - medium, C - optimal, D - excessive, E - extreme. The samples were taken during 2005-2007, n = 1713 (1251, meadows; 323, pastures; 139, alpine pastures; Susin, 2008a, 2008b, 2008c). In Slovenia, grassland soils are also relatively poorly supplied with available potassium (Figure 2). Of the analysed soil samples, 21% is arranged in the class of low content of potassium and 43% in the class of medium content. Despite these discouraging findings, the lack of potassium in the soil of Slovene grassland is much less severe than the lack of phosphorus. This is also confirmed by the fact that the uptake of potassium by yield of herbage is higher than one would expect taking into account fertilization and analytically defined potassium content in the soil. 4 INFLUENCE OF LIMING ON GRASSLAND PRODUCTION Soil liming is the amelioration measure used to improve soil pH value and its structure as well as plant and animal calcium supply. Despite this general benefit grassland liming has variable impact if being judged on the basis of herbage yield (Edmeades et al, 1984). The reasons for this uncertainty can be found in the complexity of the interactions between the ground limestone (CaCO3) or lime (Ca (OH)2) and the soil in which the sward plants have important role. Liming increases pH value of soil which affects its physical, chemical and biological characteristics. Soil pH per se does not have an important impact on grassland plants. Wheeler et al. (1992) established that various pasture species are not sensitive to pH (water) 4.5 with the exception of Harding grass (Phalaris aquatica L.) and lucerne (Medicago sativa L.). These results had been derived from many solution culture experiments with two pH treatments at zero aluminium concentration (pH 4.5 vs. 5.5; e.g. Edmeades et al. 1991). More important problem for meadow plants growing on acid soils is toxicity of aluminium cations (Al3+) on one hand, and the lack of phosphorous (H2PO4-), calcium (Ca2+) and magnesium (Mg2+) on the other. Growth disturbance of grassland plants may also occur in conjunction with other nutrients but is less common. Toxicity of Al3+ in grassland soil begins to emerge at pH < 5.5 (measured in water; Wheeler and O'Connor, 1998). Whitehead (2000) states that the threshold of soil pH value for this toxicity is 4.5 (a measuring method is not indicated). Toxic influence of Al3+ on grassland plants is reflected in the same manner as in other cultures, i.e. in poorer growth of roots and thus the whole plants. The increased content of Al3+ in the soil minimizes the availability of phosphorus to plants, which is often the main negative effect of acid soil on the growth of grassland plants. It seems that this is also the main problem of acid grassland soil in Slovenia. Liming of acid grassland soil eliminates Al3+ toxicity and improves the supply of plants with calcium and phosphorus. But this cannot replace grassland fertilization with phosphorus. Liming accelerates the mineralization of organic matter in soil and consequently improves the plant supply with nutrients, especially nitrogen. Wheeler and O'Connor (1998) report that the total net amount of nitrogen mineralized in the first two years after ground limestone application of 5 and 10 t/ha on the mowing trials was 32 and 68 kg N/ha, respectively. 4.1 Herbage yield The positive impact of liming on the herbage yield can be expected up to pH (water) 6, as reported by Edmeades et al. (1985). However, such positive impact has not been always confirmed even at much lower pH values (e.g. Leskosek, 1987). The results of three experiments are stated bellow in order to illustrate the variable impact of liming on the yield of permanent grasslands. Leskosek (1987) performed two experiments that involved different fertilization treatments and found that liming along with PK or NPK fertilizers applications had week effect on the herbage dry matter yield compared to non-limed controls (Figure 3). The reason for poor performance of liming is attributed to relatively high pH value compared to the recommendations for grassland soils. This value was before the start of the research, in both experiments, 4.9 (in KCl). At the same time the concentration of exchangeable Al3+ ions in both experiments was small. It was 0.96 and 0.25 mmolc/100 g soil in Dragatus and in Brezje near Ljubljana, respectively. Figure 3: Influence of fertilizer application and liming on the herbage dry matter yield on two 2-cut meadows. The figure shows the annual yields averaged over 5-year period with standard errors of means (Leskosek, 1987). A, trial at Dragatus, silt loam, pHKci 4.9 B, trial at Brezje, silty clay loam, pHKci 4.9 Unfertilized = zero fertilizers, no liming Unfertilized = zero fertilizers, no liming NPK = 40+40 N, 80 P205, 110 K20 (all in kg/ha/year,variant b) NPK = 40+40 N, 80 P205, 110 K20 (all in kg/ha/year,variant b) NPK+CaO, = b + 1000 kg CaO/ha (mixed lime) NPK+CaO, = b + 1500 kg CaO/ha (groun limestone) NPK+Ca02 = b + 2000 kg CaO/ha (mixed lime) NPK+Ca02 = b + 2000 kg CaO/ha (mixed lime) NPK+Ca03 = b + 3000 kg CaO/ha (mixed lime) NK+CaO+Thf = NK as at b + 1500 kg CaO/ha and Thomas phosphate (80 kg P2Os/ha/year) NK+CaO+Thf = NK as at b + 2000 kg CaO/ha and Thomas phosphate (80 kg P205/ha/year) NPK+CaO;, = b + 2000 kg CaO/ha (quick lime) PK = as at b NPK+Ca04 = b + 2000 kg CaO/ha (ground limestone) PK+Ca02 = as at b + 2000 kg CaO/ha (mixed lime) PK = as at b PK+Ca02 = as at b + 2000 kg CaO/ha (mixed lime) Schechtner (1993) also reports about the poor performance of liming. He conducted two experiments on a high-mountain pasture -Nardetum association. In one he compared the effect of different amounts of mixed lime within the PK fertilization and in the other the effect of different amounts of mixed lime within the NPK fertilization (Figure 4). The influence of liming was expressed only when compared the PK fertilization to the implication of the maximum amount of mixed lime (990 kg CaO/ha every second year) during the period from the fifth to the ninth year of the trial. As for all other comparisons, the increase of herbage yield due to liming was very low regardless the period of comparison. There were two reasons for poor impact of liming: the first one was the grassland community itself, which was difficult to improve and the second reason was the methodological approach since they used Thomas phosphate for phosphorus fertilization that contents calcium in the form of salt and oxide. For this reason both controls (PK and NPK) as well as other treatments received 135 kg CaO/ha per year from Thomas phosphate, meaning that it masked almost all liming influence. This disturbance in trial caused by Thomas phosphate was obvious also in the development of pH values in soil. The implemented amount of 135 kg CaO/ha finally increased pH (KCl) value on around 5 which already provided relatively favorable conditions for growth of grassland species. A O PK OPKCaOl A PKCa02+ PKCa03 A O O + è O â + -1-1-1 1968-71 1972-75 1981-90 ONPK O NPKCaOl A NPKCa02 +NPKCa03 4,5 4 aj >3,5 S Q cu 3 OD ro -Q I 2,5 2 1,5 è o A o o * -1-1-1 1968-71 1972-75 1981-90 B Figure 4: Influence of fertilizer application and liming on the herbage dry matter yield on a poor pasture belonging to the Nardetum association (locality: Zachenschoberl, 1300 m a.s.l.). The figure shows the mean annual yield for three periods (duration of the experiment: 1964-1984; Schechtner, 1993). PK = 300 kg Thomas phosphate (45 % CaO) + 200 kg /ha/year potassium chloride (40 % K20); PK application is the same in all treatments CaOi, Ca02, Ca03 = 500, 1000, 1500 kg/ha (mixed lime, application each second year) Rates of CaO/ha/year: 135 kg (PK), 300 kg (CaO, ). 465 kg (Ca02), 630 kg (Ca03) N = 2 x 40 kg/ha (KAN, application in spring and after the first cutting) Unlike the two above described trials, Grundler and Voigtländer (1979) report on good impact of liming using physiologically acid NPK fertilizer (Figure 5). Using this fertilizer liming increased average hay yield in the whole period (1954-1974) for 1.8 t/ha per year i.e. 26 %. At the same time the final soil acidity decreased indicating high liming activity of slag. The research shows that implementation of lime to physiologically acid fertilizer had strong effect on botanical composition of sward. Physiologically alkaline NPK fertilizer had similar effect. The original sward with prevailing red fescue (Festuca rubra L.), thread rush (Juncus filiformis L.), quaking grass sedge (Carex brizoides L.) and Yorkshire fog (Holcus lanatus L.) changed due to the impact of above stated factors into a sward with prevailing meadow foxtail (Alopecurus pratensis L.), meadow and red fescue (F. pratensis Huds.) and Yorkshire fog. Figure 5: Influence of fertilizer application and liming on the herbage dry matter yield on a permanent pasture at Niedersteinnachu (soil type: gley; pHKCl 4,2; Grundler in Voigtlander,1979). The figure shows the annual yield averaged over 1954-1974. Till 1967, 2-cut system was applied after that it was changed to 3-cut system. pH shown in the figure refers to 1974. Unfertilized = zero fertilizers, no liming NPKbasic = basic NPK (rate per ha: 30 kg N/cutting + 80 kg P205/year + 160 kg K20/year), variant b NPKbasic+CaO = b + 9 applications of CaO (1955-1972, annual rate 11 CaO/lia), variant c NPKacid = acid NPK, rate as at b NPKacid+CaO = acid NPK + CaO as at c 4.2 Herbage yield quality In acid soil (pH ~ 4; in KCl) liming together with fertilizer application improves the sward botanical composition and consequently nutritional value of herbage. Both ameliorating measures are needed to obtain optimal growth conditions for grassland plants that do not strive well on acid and poor soil. Example of such improvement is stated in the previous paragraph (Figure 5). Based on a 109 years long field trial in Rothamsted, that is still going on, Thurston (1969) reports about major differences in sward botanical composition connected to the soil pH value. Fertilizer application of physiologically acid ammonium sulphate ((NH^SO^ caused soil acidity (pH ~ 3.8; in water). In the sward with this treatment, prevailing species was common bent (Agrostis tenuis Sibth.) followed by less abundant red fescue and two other acidophilic species common sorrel (Rumex acetosa L.) and creeping cinquefoil (Potentilla reptans L.) which were rare. In lime-treated sward with soil pH value of about 5.3 higher quality species throve, especially the most abundant meadow fox tail. There was also a lot of common dandelion (Taraxacum officinale F. H. Wigg). Even though liming together with fertilizer application improved sward species composition in many experiments it did not have major influence on the proportion of legumes in swards (e.g. Grundler and Voigtlander, 1979; Leskosek, 1984; Edmeades in et al, 1990; Schechtner, 1993). Liming also affects directly the quality of herbage from grasslands but to a lesser extent. It can increase phosphorus uptake and content in plants due to increased mineralization of organic matter in soil and better availability of mineral bound phosphorus in soil (Wheeler and O'Connor, 1998). Root growth is improved due to decrease of Al3+ ions caused by liming. This consequently improves phosphorus supply to the plant. Liming usually increases calcium content in herbage. This is reported by several sources (e.g. Whitehead, 2000; Wheeler, 1998). In two field trials on grassland with original pH value 5.1 and 5.5 (in water) application of limestone at rate of 8 t/ha increased herbage calcium content from 5.0 to 6.1 g/kg of dry matter (Stevens and Laughlin, 1996). But this is not very important, because the control value itself is already high. Liming can have also the negative impact on grassland forage quality. Wheeler (1998) noted the negative impact of liming (5 and 10 t of ground limestone/ha) on content of exchangeable magnesium in soil and on magnesium content in herbage, but this lower content was still appropriate. He also cites the finding of an increase in grazing tetany due to late autumn liming. 5 CONCLUSIONS Soil acidity in meadows and pastures is often too high for good growth of grassland vegetation. The reason for this is not pH per se, but increased content of Al3+ in the soil which has negative impact on plants. The content of Al3+ is also linked to the restricted availability of phosphorus to plants. Other disturbances in the growth of grassland plants on acid soils are less important. Considering the soil pH value, it is necessary to know the method of its measuring, because it influences on the results considerably. Methods of measuring pH values in the soil represent the key reason for the differences among the optimal values cited in literature. Grassland soils in Slovenia are often too acidified and very poorly supplied with phosphorus. The situation is the worst in mountain pastures due to management of the grassland as due to adverse pedo-climatic conditions. The latter increase the loss of plant nutrients from the rhizosphere and upper soil layers. Liming has a number of beneficial effects on soil fertility and also contributes to the better supply of plants with calcium. Nevertheless, liming of acid grassland soils (pH ~ 5; in KCl) does not always increase the yield of herbage, which has been confirmed by many researches. The reason for this is in particular grassland plants which tolerate the acid soil conditions and have quite a high production capacity as well. In such situation, the herbage yield can be increased simply by adequate fertilizer application to 7 to 9 t dry matter/ha which is quite good. Here, the quality of herbage is also improved in terms of increased proportion of better grasses in the sward. On grassland with very acid soil (pH < 4.5; in KCl) liming is required to improve botanical composition of sward which does not meet yield and quality standards in the managed grassland. At the same time liming of very acid soil improves the supply of plants with some nutrients, especially with phosphorus and nitrogen. Direct impact of liming of grassland soils on herbage quality is small. Normally, this measure increases the content of calcium in herbage, but it is generally less problematic in the diet of livestock. Due to dilution effect the content of other mineral nutrients in herbage is changed slightly by liming although their uptake is increased. Liming can even worsen the supply of animals with magnesium, although this risk is low. In Slovenia, liming of grasslands is recommended on acid soil with pH below 5.0, but also on soils wit pH below 6.0 (measured in KCl or CaCl2). In the first case, liming increases the yield and quality of herbage and in the second case it prevents the acidification of soil. Liming also improves the soil structure which may reduce soil compaction on grasslands due to animal trampling and use of heavy machinery. For liming, ground limestone has the advantage before lime and ground dolomite. 6 REFERENCES Bini C., Bresolin F. 1998. Soil acidification by acid rain in forest ecosystems: A case study in northern Italy. Science of the total environment, 222: 1-15, DOI: 10.1016/S0048-9697(98)00239-3. BMLFUW. 2006. Richtlinien für die sachgerechte düngung. Anleitung zur interpretation von bodenuntersuchungsergebnissen in der Landwirtschaft. Wien, Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft: 79 p. Bolan N. S., Hedley M. J., White R. E. 1991. Processes of soil acidification during nitrogen cycling with emphasis on legume based pastures. Plant and Soil, 134: 53-63 Christie P. 1987. Some long-term effects of slurry on grassland. Journal of Agricultural Science, Cambridge, 108: 529-541, DOI: 10.1017/S0021859600079910. DEFRA. 2010. Fertiliser manual (RB209). Norwich, TSO (The Stationery Office): 249 p. Edmeades D. C., Pringle R. M., Mansell G. P., Shannon P. W. 1984. Effects of lime on pasture production on soils in the North Island of New Zealand: 1. Introduction and description of data base. New Zealand Journal of Agricultural Research, 27: 349-356, DOI: 10.1080/00288233.1984.10430635. Edmeades D. C., Wheeler D. M., Waller J. E. 1985. Comparison of methods for determining lime requirements of New Zealand soils. New Zealand Journal of Agricultural Research, 28: 93-100, DOI: 10.1080/00288233.1985.10427001. Edmeades D. C., Wheeler D. M., Rys G., Smith N. 1990. Effect of pasture composition on lime and phosphorus responses on a dryland soil. Proceedings of the New Zealand Grassland Association, 52: 171-175 Edmeades D. C., Blamey F. P. C., Asher C. J., Edwards D. G. 1991. Effects of pH and aluminium on the growth of temperate pasture species. I. Temperate grasses and legumes supplied with inorganic nitrogen. Australian Journal of Agricultural Research, 42: 559-569, DOI: 10.1071/AR9910559. de Klein C. A. M, Monaghan R. M., Sinclair A. G. 1997. Soil acidification: A provisional model for New Zealand pastoral systems. New Zealand Journal of Agricultural Research, 40: 541-557, DOI: 10.1080/00288233.1997.9513277. GRUDAF. 2009. Grundlagen für die düngung im acker- und futterbau. AgrarForschung, 16: 100 p. Grundler T., Voigtlander G. 1979. Die Wirkung langjahriger Kalkung bei physiologisch alkalischen und saurer NPK-Dungung auf Futterqualitat und Heuertrag einer Feuchtwiese. Bayerisches Landwirtschaftliches Jahrbuch, 56: 337-350 Leskošek M. 1984. Apnjenje kislih tal v Sloveniji. 6. letno poročilo za RSS, Ljubljana, Biotehniška fakulteta, 67 p. Leskošek M. 1987. Delovanje kalcizacije na njivah in travnikih v Sloveniji. Zemljište i biljka, 36: 25-32 Marschner H. 1986. Mineral nutrition of higher plants. London, Academic Press: 674 p. Mengel K., Steffens D. 1982. Beziehung zwischen kationen/anionen-aufnahme von rotklee und protonenabscheidung der wurzeln. Zeitschrift für Pflanzenernährung und Bodenkunde, 145: 229-236, DOI: 10.1002/jpln.19821450303. Murphy M. N. C., Stevens R. J., Christie P. 2005. Long-term application of animal slurries to grassland alters soil cation balance. Soil Use and Management, 21: 240-244, DOI: 10.1111/j.1475-2743.2005.tb00130.x. Schechtner G. 1993. Wirksamkeit der kalkdüngung auf grünland. Bodenkultur, 44: 135-152 Silvertown J., Poulton P., Johnston E., Edwards G., Heard M., Biss P. M. 2006. The Park Grass Experiment 1856-2006: its contribution to ecology. Journal of Ecology, 94: 801814, DOI: 10.1111/j.1365-2745.2006.01145.x. Sparling G. P., Lilburne L., Vojvodic-Vukovic M. 2008. Provisional targets for soil quality indicators in New Zealand. Palmerston North, New Zealand, Manaaki Whenua Press: 64 p. Stevens R. J., Laughin R. J. 1996. Effects of lime and nitrogen fertilizer on two sward types over a 10-year period. Journal of Agricultural Science, 127: 451-461, DOI: 10.1017/S0021859600078679. Sušin J. 2008a. Rodovitnost tal. Kmečki glas, 65, 33:10 Sušin J. 2008b. Rodovitnost tal na pašnikih. Kmečki glas, 65, 37: 10 Sušin J. 2008c. Rodovitnost tal na planinskih pašnikih. Kmečki glas, 65, 45: 8 Thurston J. M. 1969. The effect of liming and fertilisers on the botanical composition of permanent grassland. Experimentelle Pflanzensoziologie, 9: 58-62, DOI: 10.1007/978-94-011-7601-9_7. Tunney H., Sikora F. J., Kissel D., Wolf A., Sonon L., Goulding K. 2010. A comparison of lime requirements by five methods ongrassland mineral soils in Ireland. Soil Use and Management, 26: 126-132, DOI: 10.1111/j.1475-2743.2010.00263.x. Von Uexküll H. R., Mutert E. 1995. Global extent, development and economic impact of acid soils. Plant and Soil, 171: 1-15, DOI: 10.1007/BF00009558. Wendland M., Diepolder M., Capriel P. 2011. Leitfaden für die düngung von acker- und grünland. Freising-Weihenstephan, Bayerische Landesanstalt für Landwirtschaft (LfL): 98 p. Wheeler D. M. 1998. Investigation into the mechanisms causing lime responses in a grass/clover pasture on a clay loam soil. New Zealand Journal of Agricultural Research, 41: 497-515, DOI: 10.1080/00288233.1998.9513333. Wheeler D. M., O'Connor M. B. 1998. Why do pastures respond to lime? Proceedings of the New Zealand Grassland Association 60: 57-61 Wheeler D. M., Edmeades D. C., Christie R. A., Gardner R. C. 1992. Effect of aluminium on the growth of 34 plant species: A summary of results obtained in low ionic strength solution culture. Plant and Soil, 146: 61-66, DOI: 10.1007/BF00011996. Whitehead D. C. 1995. Grassland nitrogen. Wallingford, CAB International: 397 p. Whitehead D. C. 2000. Nutrient elements in grassland: soil-plant-animal relationships. Wallingford, CAB International: 369 p., DOI: 10.1079/9780851994376.0000. COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.03 Agrovoc descriptors: leaf area, canopy, dry matter content, zea mays, glycine max, triticum aestivum, weeds, biomass, cover plants, composts, fertilizer application Agris category code: f50, f60, f04 Response of leaf area and dry matter of crop, weeds and cover crops to competition and fertilizer resources Fahimeh DADASHI1, Faezeh ZAEFARIAN1*, Rahmat ABBASI1, Mohammad Ali BAHMANYAR2, Mohammad REZVANI3 Received August 30, 2013; accepted December 20, 2013. Delo je prispelo 30. avgusta 2013, sprejeto 20. decembra 2013. ABSTRACT IZVLEČEK Plasticity of plants to allocate leaf area and dry matter to upper layer of canopy play important role in canopy architecture and competition. In order to study the vertical distribution of leaf area and dry matter of corn (Zea mays L.), cover crops and weeds canopy in different fertilizer condition and competition, a randomized complete block design experiment with 8 treatments and 3 replicates was conducted at Sari Agricultural Sciences and Natural Resources University in 2012. Treatments were included corn with soybean (Glycine max (L.) Merr.) as cover crop without fertilizer application, corn with soybean as cover crop with chemical fertilizer application, corn with soybean as cover crop with compost fertilizer application, corn with wheat (Triticum aesitivum L.) as cover crop without fertilizer application, corn with wheat as cover crop with chemical fertilizer application, corn with wheat as cover crop with compost fertilizer application and corn monoculture both in weedy and weed free conditions. The results showed that weed infestation reduced total leaf area and dry matter of corn. Corn distributed more leaf area and dry mater of canopy to the upper layer in weedy conditions. Between cover crops, soybeans allocated corn leaf area and dry mater to the higher layers of canopy than wheat. Also, soybean reduced leaf area and dry mater production of weeds more than wheat. Soybean as cover crop with the use of compost treatment was more efficient in reducing of weed biomass and corn yield production. Key words: corn, compost, dry matter allocation, soybean, weed biomass, wheat ODZIV LISTNE POVRŠINE IN SUHE SNOVI POLJŠČIN, VMESNIH POSEVKOV IN PLEVELOV NA KOMPETICIJO IN IZRABO GNOJIL Sposobnost rastlin za premeščanje listne površine in suhe snovi v zgornje plasti krošnje ima pomebno vlogo v njihovi zgradbi in tekmovalnosti. Za preučevanje vertikalne razporeditve listne površine in suhe snovi v krošnji koruze (Zea mays L.), njenega vmesnega posevka in plevelov v različnih razmerah gnojenja in tekmovalnosti je bil v letu 2012 izveden naključni bločni poskus z osmimi obravnavanji in tremi ponovitvami na Sari Agricultural Sciences and Natural Resources University. Obravnavanja so obsegala koruzo in njen vmesni posevek sojo (Glycine max (L.) Merr.) brez uporabe mineralnih gnojil, koruzo s sojo kot vmesnim posevkom gnojeno s kompostom, koruzo s pšenico (Triticum aesitivum L.) kot vmesnim posevkom brez gnojenja, koruzo s pšenico kot vmesnim posevkom, gnojeno z mineralnimi gnojili, koruzo s pšenico kot vmesnim posevkom gnojeno s kompostom in monokulturo koruze v razmerah z in brez plevelov. Rezultati so pokazali, da so pleveli zmanjšali listno površino in vsebnost suhe snovi pri koruzi. Koruza je premestila več listne površine in suhe snovi v zgornje plasti krošnje v razmerah zapleveljenosti. V razmerah z vmesnimi posevki je koruza premestila več listne površine in suhe snovi v zgornje plasti z vmesnim posevkom sojo kot pa s pšenico. Podobno je soja bolj zmanjšala listno površino in suho snov plevelov kot pšenica. Soja je kot vmesni posevek ob uporabi komposta bolj učinkovito zmanjšala biomaso plevelov kot tudi pridelek koruze. Ključne besede: koruza, kompost, alokacija suhe snovi, soja, biomasa plevelov, pšenica, vmesni posevek 1 Department of Agronomy, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran, * Email: fa_zaefarian@yahoo.com as correspondence 2 Department of Soil Science, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran Department of Weed Science, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran 1 INTRODUCTION Weeds are one of the major threats to crop production in cropping systems. The risk of weeds not only reducing crop yields but also decreasing the commercial quality and the feeding palatability of main crops and enhance the soil seed bank of weeds, which may cause continuous weed infestation of field crops (Uchino et al., 2012). The primary goal of weed management approaches is reducing the negative effects of weeds on crop. Herbicides have developed to be a reliable and highly effective method for weed control. However, demand for safe food products and food that have been produced with a minimum application of chemical inputs increased. Therefore, farmers interested in weed management have to rely on other control approaches (Hollander et al, 2007). An alternative weed control method is the use of cover crops (Uchino et al, 2009), which can suppress the growth of weeds by competition for light, soil moisture and nutrients, and also by producing allelopathic compounds (Compigla et al, 2010). Cover crops have been successfully integrated into conservational agriculture systems in many parts of the world. Jedrszczyk and Poniedzialek (2007) reported cover crops increased the content of corn dry matter in comparison to monoculture of corn in weedy condition. Uchino et al., (2009) resulted in increased coverage of corn, soybean and cover crop, declined weed dry matter. Weeds were suppressed effectively and stably without yield reductions of main crops by inter-seeded cover crops with sufficient fertilization in organic farming systems (Uchino et al, 2012). In competition, height and leaf area index are two important, so that species with greater leaf area and height are more successful (Vazin et al., 2010; Rezvani et al, 2013). Plant ability to allocate green shoot to upper layer is one of the main traits in competition (Agha-Alikhani et al., 2009). Because, the canopy structure impact on the absorption of radiation, evaporation and transpiration, canopy and dry matter accumulation and yield (Rezvani et al, 2010). Agha-Alikhani et al. (2009) indicated that in weed free corn pure stand, 30.36 % of the maximum leaf area was distributed in 90-120 cm layer of canopy, but when corn was grown with weed, the maximum leaf area were established in the upper. The objective of the research was investigating leaf area and biomass profile in corn, cover crops and weeds under different treatments of cover crops and fertilizer resources. Also, yield of corn and performances of applied weed managements were evaluated. 2 MATERIALS AND METHODS The experiment was carried out at Sari Agricultural Sciences and Natural Resources University, Sari. The soil was a silt-clay soil with 7.34 pH, 2.53 % organic matter, 0.23 % total N, 38.74 ppm P and 400 ppm K. Field preparation was consisted of a deep tillage in previous fall and a vertical disk in spring. The experiment was established in a randomized complete block design with four replicates. Corn was considered as main crop and soybean and wheat were the cover crops. Treatments were included corn with soybean as cover crop without fertilizer application, corn with soybean as cover crop with chemical fertilizer application, corn with soybean as cover crop with compost fertilizer application, corn with wheat as cover crop without fertilizer application, corn with wheat as cover crop with chemical fertilizer application, corn with wheat as cover crop with compost fertilizer application, corn monoculture both in weedy and corn monoculture in weed free conditions. Natural weed population of all plots except corn monoculture in weed free treatment maintained in all growth stages. Weed free corn monoculture treatment was weeded in all growth stage. Varieties of corn, wheat and soybean were NS-640, Milan and Sari, respectively. Corn planted in 75 cm row spacing with 20 cm between plants in the same row. Each plot was included 5 rows corn. Crops were planted on 26 May 2012. Cover crop inter-seeded simultaneously in the main crop. Chemical fertilizer treatment was used according to the soil analysis. 400 kg ha-1 N-fertilizer as Urea, 200 kg ha-1 K-fertilizer as Potassium sulfate and 150 kg ha-1 P-fertilizer as Triple superphosphate were applied. A total of 20 ton ha-1 mushroom compost was used as an organic fertilizer resource. The chemicals properties of compost were as 6.9 pH, 1.8 % N, 1.8 % P and 1.6 % K. At planting, 200 kg ha-1 N-fertilizer and total P and K-fertilizer and compost was incorporated into the soil. Other 200 kg ha-1 N-fertilizer top dressed in early flowering stage of corn. At the corn canopy closure stage, a vertical card board frame marked in 30-cm increments was used in the field as a guide to cut standing plants including corn, cover crops and weeds. In each vertical layer of canopy, leaves and stem samples were separated. The leaf area both crops and weeds were measured with a leaf area meter LICOR-3000A (LI-COR, Lincoln, NE, USA). Stem and leaf samples oven dried. Weed biomass production of treatments evaluated at the corn harvest time. Also, Corn yield was measured by mechanically harvesting both middle rows and adjusting to 13% moisture. 2.1 Statistical analysis Corn yield and weed biomass data subjected to analysis of variance (ANOVA) using the SAS (ver. 9.2). Means were compared with LSD test at P=0.05. The vertical distribution of leaf area and dry matter were plotted by Grapher (ver. 9) software. 3 RESULTS AND DISCUSSION 3.1 Vertical changes of corn and cover crops leaf area The maximum leaf area of corn cultivated with soybean as cover crop both in compost and chemical fertilizer treatments were placed at 90120 cm layer (Figs. 1a). In all treatments that wheat used as cover crop, corn allocated the leaf area in lower layers of canopy that those of treatments that corn growth with soybean as cover crop (Figs. 1a). Figure 1b indicates vertical distribution of corn monoculture both in weedy and weed free conditions. Results showed that in weedy condition the most leaf area (24.01 %) placed in layer of 150-180 cm corn canopy. But, in weed free condition the maximum leaf area of corn (22.33 %) established in the layer of 90-120 cm (Fig. 1b). Between cover crops, soybeans compared to wheat expanded corn leaf area to the upper layers of the canopy. Large proportion of the soybean leaf area was established at both layers of 60-90 cm and 90-120 cm (Fig. 2), while the major part of the wheat leaf area was allocated to the layer of 0-30 cm of the canopy in all corn with wheat as cover crop treatments. Soybean leaf area was expanded to the upper layers of the canopy than wheat, which can cause superiority of soybean plants in competition with weeds (Fig. 2). Corn allocated more leaf area to the upper layer in presence of weeds. In response to competition, plants transfer their leaf area to upper layers of canopy; through preventing light penetration to the bottom layers, to increase their competitive abilities (Safahani-Langerodi et al., 2008). Saadatian et al. (2011) also reported increasing the ration of the upper layer of wheat canopy in interference conditions with wild mustard. 180-210 150-180 120-150 90-120 60-90 30-60 0-30 180-210 150-180 120-150 90-120 60-90 30-60 0-30 180-210 150-180 120-150 90-120 60-90 30-60 0-30 1111111 T ■ wheat | ■ soybean J—. Compost 3 Chemical fertilizer b 3 No-Fertilizer rr 240-270 210-240 x 180-210 k jB 150-180 t is 120-150 ^ 90-120 i_. & 60-90 llll i Weed control S 30-60 (3 0-30 . Weedy 100 80 60 40 20 0 20 40 Leaf area (%) 1 I 1 I ' I ' I ' I , , , , 60 80 100 100 80 60 40 20 0 20 40 60 80 100 Leaf area (%) Figure 1: Vertical distribution of corn leaf area under presence of cover crops (a) and corn monocropping (b). Vertical bars represent Se of the means. wheat soybean ^ 90-120 ^y 60-90 g" 30-60 § 0-3» 20 60-90 30-60 0-30 Compost Chemical fertilizer PT i I i I i T~ No-Fertilizer I 1 I 1 I 1 I 1 100 80 60 40 20 0 20 40 60 Leaf area (%) 100 Figure 2: Vertical distribution of cover crops leaf area. Vertical bars represent Se of the means. 3.2 Vertical changes of weed population leaf area The dominant weed species were velvetleaf (Abutilon theophrasti Medic.), Johnson grass (Sorghum halepense (L.) Pers.), wild melon (Cucumis melo var. agrestis) and giant foxtail (Setaria glauca) in the experimental field. Velvetleaf leaf area was expanded to the upper layers of the canopy in wheat used as cover crop compared with soybean used as cover crop treatment. But, in soybean was as cover crop with a 120 150 90 30 120-150 120 150 compost treatment, velvetleaf expanded all its leaf layer (Fig. 3f). Generally, in presence of cover area to 30-60 cm layer (Fig. 3a). crops conditions weeds allocated leaf area to the lower layers. But, in no fertilizer treatment due to Velvetleaf in weedy monoculture of corn expanded competition for nutrients, weeds allocated the its leaf area to 90-120 cm layer and the maximum major part of leaf area at 90-120 cm layer (Fig. 3a). proportion of the leaf area allocated to 60-90 cm 90-120 ' " o ( 0-30 ■ 1 ■ ( • " 0-30 ■ • " 0-30 I I I I I I I I I I I wheat I soybean b ""1 Compost 3H 90-120 60-90 30-60 0-30 120-150 90-120 Johnsongrass t£ -p Chemical fertilizer j? 60-90 3 g; 30-60 120-150 90-120 60-90 30-60 0-30 I I wheat I_I soybean ^ |l Compost I I I I I I I I I H Chemical fertilizer — 100 80 60 40 20 0 20 40 60 Leaf area (%) I 1 I 1 I 1 I 1 I 1 11 I 1 I 1 I 1 I 1 100 80 60 40 20 0 20 40 60 80 1 Leaf area (%) I I I I I I I I I I I wheat r^] soybean Compost Chemical fertilizer ttttttttt- 100 80 60 40 20 0 20 40 60 80 100 Leaf area (%) 30-60 0-30 60-90 30-60 0-30 90-120 60-90 30-60 0-30 I I wheat □ soybean Other weed |h Compost 60-90 30-60 0-30 Chemical fertilizer ? 2 J 60-90 30-60 0-30 I 1 I 1 I 1 I 1 I 1 100 80 60 40 20 0 20 40 60 Leaf area (%) 1 I 1 I 1 I 1 I 1 I 100 I I I M I I I I I I wheat I soybean f Compost No-Fertilizer I I I I I I I I I Weed infestation 0 Other weed Wildmelon f 1 Johnsongrass 1 4 r 0 Foxtail | Velvetleaf 1 i 1 i 1 i 1 i 1 i i 1 i 1 i 1 i 1 i 1 100 80 60 40 20 0 20 40 60 Leaf area (%) 100 80 60 40 20 0 20 40 60 80 100 Leaf area (%) Figure 3: Vertical distribution of leaf area of velvetleaf (a), johnson grass (b), wild melon(c), giant foxtail (d) and other (e) under presence of cover crops and vertical distribution of weeds leaf area in monocropping of corn under weed infestation. Vertical bars represent Se of the means. c a 0-30 No-Fertilizer No-Fertilizer 100 d 30-60 100 Johnson grass in soybean with cover crop was more successful in competition than wheat with cover crop treatments, because of the ability to expand the most leaf area to the upper layers of canopy height. The maximum leaf area Johnson grass in soybean cover crop with compost, chemical fertilizer and no fertilizer treatments were placed at 60-90 cm, 60-90 cm and 90-120 cm layers of canopy, respectively (Fig. 3b). Johnson grass leaf area in no fertilizer allocated to higher layer of canopy than other fertilizer treatments. The maximum leaf area of Johnson grass in monoculture of corn was observed at 60-90 cm layer (Fig. 3f). Leaf area of Wild melon in all treatments expanded only at 0-30 cm canopy layer. Giant foxtail completely suppressed and controlled with treatments of compost and soybean used as cover crop (Fig. 3d). Soybean as cover crop was more successful than wheat in giant foxtail control. Other weeds of fields in treatments of soybean cover crop were observed only in chemical fertilizer treatments at 0-30 cm layer (Fig. 3e) and two other fertilizer treatments were free of other weeds. In wheat used as cover crop treatments other weeds were presented in all three fertilizer treatments and in chemical fertilizer treatment compared to other treatments, expanded their leaf area to the upper layers of the canopy. In corn monoculture weedy condition treatments, other weeds allocated the maximum leaf area Layer to 030 cm (Fig. 3f). Uchino et al. (2012) with study of the possibility of suppressing weeds in corn by cover crops reported that the maximum total leaf area of weeds was observed in no cover crops treatments. 3.3Vertical changes of corn and cover crops dry matter Corn in soybean cover crop treatments compared to wheat cover crop allocated dry matter to the upper layer of canopy. The layer of the maximum corn dry matter in soybean cover crop treatments with compost and chemical fertilizer were observed at 90-120 cm. But, in no fertilizer treatments the layer was formed at 60-90cm layer of canopy. In wheat cover crop treatments the maximum layer of corn dry matter accumulated at 30-60 cm, 90-120 cm and 60-90 cm layers in plots with compost, chemical fertilizer and no fertilizer, respectively (Fig. 4a). Ahmadvand et al. (2006) who worked on wheat and wild oat (Avena fatua L.) canopy structure, reported allocation of total dry matter and leaf area of wild oat to the upper layers increased by enhancement of density. In the monoculture of corn with weed infestation due to competition between corn and weed, observed a reduction in dry matter of corn than in weed free (Data did not shown). The maximum amount of corn dry matter in weed free treatment was established in layer of 120-150 cm (Fig. 4b). Corn in competition with weeds, translocated the most percentage of dry matter to the upper layers of canopy. The changes in distribution of dry matter pattern may be due to more light achievement. Study of rice (Oryza sativa L.) canopy structure showed that rice allocated more leaf area and dry matter to the upper layers in competition with barnyard grass (Echinochloa cruss-galli) because of competition over nutrient and light sources (Aminpanah et al., 2009). 210-240 180-210 150-180 120-150 90-120 60-90 30-60 0-30 210-240 180-210 150-180 120-150 90-120 60-90 30-60 0-30 210-240 180-210 150-180 120-150 90-120 60-90 30-60 0-30 T T I I I T + wheat | + soybean Compost Chemical fertilizer b No-Fertilizer T T I I I T A 240-270 o 210-240 1} m 180-210 j 1 I 1 I 1 I 1 I 1 I 100 80 60 40 20 0 20 40 60 80 100 Dry matter (%) I I I I I I I I I I I wheat soybean Compost Chemical fertilizer I I I I I I I I I Giant foxtail 60-90 30-60 0-30 60-90 30-60 0-30 I I I I I I I I I I I wheat soybean Compost Other weed 3 0-60 0-30 90-120 60-90 3 0-60 Chemical fertilizer ' i= •> - I I wheat I soybean Compost 100 80 60 40 20 0 20 40 60 80 100 Dry matter (%) Weed infestation 30-60 0-30 90-120 Other weed Chemical fertilizer .2 60-90 ^ 30-60 Z = • -:. No-Fertilizer 3 120-150 90-120 Foxtail 60-90 30-60 •> j 1 I 1 I 1 I 1 I I 1 I 1 I 1 I 1 I 1 100 80 60 40 20 0 20 40 60 80 100 100 80 60 40 20 0 20 40 60 Dry matter (%) Dry matter (%) 1 I 1 I 1 I 1 I 1 I 100 ttttttttt Johnsongrass I I I I I I I I I 100 80 60 40 20 0 20 40 60 80 100 Dry matter (%) c a No-Fertilizer d e 0-30 60-90 Figure 6: Vertical distribution of dry matter of velvetleaf (a), johnson grass (b), wild melon (c), giant foxtail (d) and other (e) under presence of cover crops and vertical distribution of weeds dry matter in moonocropping of corn under weed infestation. Vertical bars represent Se of the means. Wild melon because of vegetative growth form allocated dry matter to the 0-30 cm layer (Fig. 6c). Giant foxtail growth completely suppressed by the soybean cover crop both in compost and chemical fertilizer application treatment (Fig. 6d). Other weed in the soybean cover crop were observed only in chemical fertilizer application treatments and in wheat cover crop with compost was observed only at 0-30 cm layer, but in other treatments were placed at the upper layers (Fig. 6e and 6f). Previous studies showed that use of hairy vetch (Vicia villosa) (Czaper et al., 2002), Italian ryegrass (Lolium multiflorum) (Faget et al., 2012), red clover (Trifulium pratense) and rye (Secale montanum) (Altentorbert et al., 1996) as cover crops reduced biomass, density and diversity of weeds. 3.5 Weed biomass and Corn yield Use of cover crops decreased weed biomass. In treatments of soybean with compost and also wheat with compost produced the minimum weed biomass. Generally, soybean as cover crop was more successful than wheat to inhibit weed growth (Table 1). There is a wide agreement in the researches conclusion that living cover crops will suppress weeds successfully. Barnes and Putnam (1983) also reported a living mulch of springplanted rye reduced early season biomass of common lambsquarters, large crabgrass [Digitaria sanguinalis (L.) Scop.], and common ragweed (Ambrosia artemisi-ifolia L.) compared to controls. Effect of cover crops in reducing weed biomass previously reported by Ngoguajio et al. (2003) Samarajeewa et al. (2006). The suppressive effect of cover crop could be due to inhibition of weed seed germination through effect on the radiation and chemicals environment of seeds. Also continuous suppressive effect of cover crop could reduce seed production by weeds (Brennan and Smith, 2005). Results of analysis of variance indicated treatments had significant effect on corn economic yield (Data not shown). Corn monoculture in weed free condition produced the maximal yield (Table 1). In the cover crop treatments including soybean with compost and soybean with chemical fertilizer had the highest economic yield (Table 1). All wheat used as cover crop treatment was not as successful as soybean in grain yield production (Table 1). There are reports that cover crops can suppress cash crops growth through the competition for resources. But, simulative effect of legume cover crops on cash crops through enhancement of nitrogen availability was reported by Sarrantonio and Gallandt (2003) and Calegari et al. (2005) and promotion of genes that delay senescence and enhance disease resistance (Kumar et al., 2004). Table 1: Mean comparison of corn yield and weed biomass. Treatments Economic yield (kg/ha) Weed biomass (g/m2) Corn monoculture Weed free Weedy 12124.00a 2733.30d 33.92a No-fertilizer 3884.70cd 21.4c Corn+soybean Chemical fertilizer 7769.70b 19.52c Compost 8351.30b 5.45d No-fertilizer 3795.00cd 27.53b Corn+wheat Chemical fertilizer 4903.00bcd 25.55b Compost 4089.70c 12.58cd In each column, numbers with the same letter are not significantly different at 5 % level. 4 CONCLUSIONS According to our research corn allocated more leaf and dry matter to upper layers in response to competition to cover crops and weeds to light absorption. Compost application and use of soybean as a cover crop was a successful management in weed growth suppression. Results showed use of legume as cover crop especially with organic fertilizers can be an alternative approach for herbicides and are more effective than others. However, further studies are required on cover crops species, seeding rate and growth pattern and their nutrition management such as amount and type of fertilizer. 5 REFERENCES Agha-Alikhani, M., Zaefarian, F., Zand, E., RahimianMashhadi, H., Rezvani, M., 2009. Corn and soybean intercropping canopy structure as affected by competition from Redroot pigweed (Amaranthus retrofelxus L.) and Jimson weed (Datura stramonium L.). Iranian J Weed Sci. 5(2): 39-53. Ahmadvand, G., NasiriMahallati, M., Koocheki, A. 2006.Effect of light competition and nitrogen fertilizer on canopy structure of wheat and wild oat.(In Persian with English Abstract).Journal of Agricultural Science and Environ Resource. 12(6): 100-112. Altentorbert, H., Reeves, D., Mulvancy, R. 1996. Winter legume cover crop benefits of corn: Rotation us fixed Nitrogen effects. Agron J. 88: 527-535, DOI: 10.2134/agronj 1996.00021962008800040005x. Aminpanah, H., Sorooshzadeh, A., Zand, E., Momeni, A. 2009. 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COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.04 Agrovoc descriptors: vitis vinifera, grapevines, varieties, grapes, chemicophysical properties, proximate composition, antioxidants, organoleptic analysis, winemaking, biodiversity, new products, product development Agris category code: q04, f60 Physico-chemical and sensory characteristics of jellies made from seven grapevine (Vitis vinifera L.) varieties Luana FERNANDES, Nuno RODRIGUES, José Alberto PEREIRA, Elsa RAMALHOSA1 Received Janury 21, 2014; accepted February 19, 2014. Delo je prispelo 21. januarja 2014, sprejeto 19. februarja 2014. ABSTRACT IZVLEČEK Jellies of seven grapevine varieties were physico-chemical and sensorial characterized for the first time. Jellies differed significantly in moisture and ash contents, colour, pH, acidity and antioxidant activities. 'Tinta Carvalha' was the darkest and redness jelly, showing the highest antioxidant activity. Regarding sensory characteristics, no significant differences in the appearance, taste, sweetness, acidity and global assessment were observed among jellies. Nevertheless, these attributes were positively evaluated. In conclusion, the production of different jellies will allow the valorisation of grapevine varieties with less potential for wine production, helping to preserve biodiversity, and be an economic alternative to grape producers who may elaborate an enjoyable product with interesting bioactivity. Key words: grapevine, jellies, physico-chemical characterization, antioxidant activity, sensory analysis FIZIKALNO-KEMICNE IN SENZORICNE LASTNOSTI ŽELEJEV NAREJENIH IZ SEDMIH SORT GROZDJA (Vitis vinifera L.) Fizikalno-kemične in senzorične lastnosti sedmih sort grozdja so bile prvič analizirane. Želeji so se značilno razlikovali v vsebnosti vode in pepela, v barvi, pH, kislosti in antioksidativni aktivnosti. Žele pripravljen iz sorte 'Tinta Carvalha' je bil najtemnejši in najbolj rdeč. V senzoričnih lastnostih med želeji ni bilo značilnih razlik v izgledu, okusu, sladkosti, kislosti in celotni oceni, vendar so bile te lastnosti pozitivno ovrednotene. Sklepamo, da bo izdelava različnih želejev omogočala ovrednotenje tistih sort vinske trte, ki imajo manjši potencial za pridelavo vina, kar bo prispevalo k ohranjanju raznolikosti žlahtne vinske trte in bo ekonomska alternativa vinogradnikom za izdelavo koristnega izdelka z zanimivo bioaktivnostjo. Ključne besede: grozdje, želeji, fizikalno-kemično vrednotenje, antioksidacijska aktivnost, senzorična analiza 1 INTRODUCTION Portugal has great tradition in wine production. The Northeast region is not exception and it is known for the different grapevine (Vitis vinifera L.) varieties that grow there. The quality and specificity of these varieties are the result of their diversity and adaptation to different agro-climatic conditions. Through the knowledge on these varieties and the processes that may contribute to their preservation, the development of differentiated products may be a great opportunity to increase market competitiveness of this sector, besides preserving biodiversity. Furthermore, consumers are increasingly demanding for natural and healthy products, being products rich in 1 Mountain Research Centre (CIMO) - School of Agriculture, Polytechnic Institute of Bragança, Campus de Sta Apolônia, Apartado 1172, 5301-855 Bragança, Portugal; E-mail: luaopus@hotmail.com; nunorodrigues@ipb.pt; jpereira@ipb.pt; elsa@ipb.pt This paper is part of MSc thesis "Physico-chemical characterization and biological activity of grape seed oils and grape jellies" of Luana Fernandes (Advisors: Elsa Ramalhosa and José Alberto Pereira). antioxidants a good example. Grape meets these requirements, since it has a high antioxidant potential, being part of this due to its skin (Bekhit et al., 2011; Katalinic et al., 2010; Poudel et al., 2008). Several studies report that grape skin is rich in phenolic compounds, whose profile varies with variety, maturation stage and origin of the fruit (Bekhit et al., 2011). In this way, different grape varieties may exhibit different chemical compositions that may consequently influence their antioxidant potential, both in fresh and grape sub products (Abe et al., 2007). Jelly production is a good example of a product easy to produce and consume, with long storage periods that continue to have the value of fruit. Moreover, jelly production allows the employment of underused fruits, such as secondary quality (e.g. small) and over-ripe grapes that are often not desired by consumers and, hence, are generally wasted. According to the Portuguese law (Law-Decree No. 230/2003), jelly is defined as a product sufficiently gelled that result from the mixture of sugar and juice and/or aqueous extract of one or more types of fruit. Unlike other jellies of other fruits, of our knowledge few studies have been conducted to date on grape jellies. The works performed until now have addressed the effect of using different gelling agents (Gaspar et al., 1998), the role of the enzymatic activity, namely peroxidase and polyphenol oxidase (Freitas et al., 2008), and the antioxidant activity of two jellies produced from grapes of V. labrusca and V. vinifera (Falcao el al., 2007). In order to obtain more valuable data on this subject, in this study grape jellies of seven varieties of V. vinifera, namely, 'Periquita', 'Touriga National', 'Cornifesto', 'Tinta Barroca', 'Marufo', 'Trincadeira Preta' and 'Tinta Carvalha', were produced and characterized in terms of physico-chemical properties, antioxidant activity and sensory characteristics. 2 MATERIALS AND METHODS 2.1 Grape samples Seven red grapevine varieties, namely, 'Periquita', 'Touriga National', 'Cornifesto', 'Tinta Barroca', 'Marufo', 'Trincadeira Preta' and 'Tinta Carvalha', were harvested at their technological ripening time in Valpa^os, Northeast of Portugal. After harvest, the grapes were transported under refrigeration and on their arrival at the laboratory the fruits were washed with ultra-pure water (Milli-Q system, Merck Millipore, Massachusetts, USA). A grapes portion (ca. 900 g) was used to formulate jellies, while other portion (ca. 100 g) was used to separate the skins. The skins proportion for each variety was determined after separating them from the pulp and by fruit and skin weighting. Grapes and skins were packed properly at -18 °C until further use. 2.2 Jellies production For jellies production the ingredients used were fresh grapes and sucrose. At the beginning 500 g of crushed grapes of each variety were macerated at room temperature (ca. 20 °C) for approximately 5 minutes and the mixture was heated to boiling for 10 minutes. Subsequently, the mixture was filtered through a strainer and the sugar added at a ratio of 1:2 (1 g of sugar per 2 ml of liquid). Afterwards, the solution was again taken to boiling until a Total Soluble Solids (TSS) value between 65-70 °Brix (Lago et al., 2006; Lago-Vanzela et al., 2011), measured on an Abbe refractometer (Optic Ivymen System, Madrid, Spain). Before cooling the mixture were poured into glass jars with 250 g capacity and closed with metal caps. Then the jars were placed in a hot water bath (100 °C) for 15 minutes (Granada et al., 2005) and left to cool at room temperature (ca. 20 °C). 2.3 Physico-chemical analysis Before jellies processing, the TSS values of the juices of the seven grapevine varieties were measured. The following parameters were evaluated in the jellies: colour, pH, moisture, ash and acidity. Colour was measured with a CR-400 colorimeter (Konica Minolta, Tokyo, Japan) in the CIELab colour space, through the coordinates: L*, a* and b*, using the Spectra Magic Nx software (version CM-S100W 2.03.0006, Konica Minolta, Tokyo, Japan). The instrument was always calibrated with a standard white tile before analysis. Illuminant C and 2° standard observer were used. pH was measured directly (Jenway potentiometer, model 370, Jenway, Essex, United Kingdom). Moisture and ash contents were determined by weight loss at 105 °C until constant weight and 550 °C for at least 4 hours (AOAC, 1999), respectively. Acidity was determined by titrimetric analysis, consisting of a titration with 0.10 mol l-1 NaOH, being the values reported in % of tartaric acid. Due to colour of the jelly, it was not possible to detect clearly the end point of the titration when using phenolphthalein as indicator. So, the pH of the solution was monitored continuously in order to obtain the titration curve. The pH at the equivalence point was established as 8.1, as indicated in the Portuguese rule NP-1421 (1977). The titratable acidity (TA) was calculated by Equation 1, according to NP-1421 (1977): „ , cxvx MM /1 \ TA (% tartaricacid) =-x100 (1) 2x m Where c is NaOH concentration (mol l-1), v is NaOH volume spent at the titration (l), MM the molar mass of tartaric acid (150.087 g mol-1) and m the sample mass (g). The TSS contents (°Brix) of jellies were measured with an Abbe refractometer (Optic Ivymen System, Madrid, Spain). All reagents were p.a. (pro analysis) and were purchased to Sigma-Aldrich Fine Chemicals (St. Louis, MO, USA). 2.4 Antioxidant Activity 2.4.1 Grape jelly and skin extracts Extracts were prepared by mixing 5 g of sample (grape jelly or skins) with 20 ml of methanol. In case of grape skins, these were previously deep-frozen and grounded. The solutions were placed under stirring for one hour. Subsequently the solutions were filtered through Whatman No. 2 filters (Whatman, Kent, United Kingdom) to round bottom flasks previously weighed. In order to evaporate the solvent, the flasks were placed on a rotary evaporator RE300DB (Stuart, Stone, United Kingdom) and afterwards in the oven UNB500 (Memmert, Schwabach, Germany) at 40-45 °C. The extracts were redissolved in methanol to an extract concentration of 50.0 mg ml-1. 2.4.2 Total Reducing Capacity Total reducing capacity (TRC) of the extracts was determined by the Folin-Ciocalteu's assay (Singleton and Rossi, 1965). To 100 ^l of the extract solutions, 7.90 ml of deionized water and 500 ^l of Folin-Ciocalteu reagent were added. The blank was prepared in a similar way, replacing the extract solution by methanol. After 3 to 8 minutes, 1.50 ml of sodium carbonate saturated solution was added. After two hours the absorbance values were read at 765 nm (Genesys 10UV, Thermo Scientific, Madrid, Spain). Gallic acid was used as standard, being the results expressed in g of gallic acid equivalents (GAE) per kilogram of extract. 2.4.3 DPPH (2,2-diphenyl-1 -picrylhydrazyl) Radical Scavenging Activity DPPH radical scavenging activity was determined by the procedure described by Delgado et al. (2010) with some modifications. DPPH assay evaluates the ability of the grape extracts to scavenge this free radical. To 0.30 ml of extract solutions (5.00 mg extract ml-1) were added 2.70 ml of DPPH methanol solution (6.09x10"4 mol l-1). After 1 hour at room temperature (ca. 20 °C) in the dark, the absorbance was read at 517 nm (Genesys 10UV, Thermo Scientific, Madrid, Spain). DPPH radical scavenging activity was calculated as follows: DPPH radical scavenging activity (%) = ——DPPH-Sample x 100 (2) —dpph Where —DPPH is the absorbance of the DPPH solution and —sample the absorbance of the solution when the sample extract was added. The blank was made with methanol. 2.4.4 Reducing Power The reducing powers of the extracts were determined by the procedure described by Delgado et al. (2010). Extract solutions at different concentrations were prepared from the stock solution of 50.0 mg extract ml-1. To 1.00 ml of each solution were added 2.50 ml of 0.20 mol l-1 phosphate buffer (pH 6.6) and 2.50 ml of 10 g l-1 K3[Fe(CN)6]. After stirring, the mixture was incubated at 50 °C for 20 minutes. Afterwards, 2.50 ml of 100 g l-1 trichloroacetic acid was added to the test tubes. 2.50 ml of the mixture were transferred to another test tube, to which 2.50 ml of distilled water and 0.50 ml of 1 g l-1 FeCl3 were added. The absorbance values were read at 700 nm (Genesys 10UV, Thermo Scientific, Madrid, Spain). The extract concentration providing 0.5 of absorbance (EC50) was calculated from the graph of absorbance versus extract concentration. 2.5 Sensory analysis In order to evaluate the acceptability of the grape jellies a consumer panel was used, following the methodology of Lago et al. (2006). The sensory analysis took part at the University on two consecutive days due to the high number of samples, being four jellies analysed each day. Since there were seven grape jellies, one of these ('Tinta Barroca' grape jelly) was repeated in both days but identified with a different number. Around twenty-gram samples of jelly at room temperature were presented in white plastic plates labelled with three-digit random codes. A glass of water was offered to the consumers to rinse their mouths. To prevent biases related to the serving order, this was determined by random permutation. After a brief explanation of how to perform the sensory analysis, the consumers were asked to evaluate the samples according to a 9-point hedonic scale: 1 - Dislike extremely, 2 - Dislike very much, 3 - Dislike moderately, 4 - Dislike slightly, 5 - Neither like nor dislike, 6 - Like slightly, 7 - Like moderately, 8 - Like very much, 9 - Like extremely. The attributes evaluated were the appearance, colour, taste, acidity, sweetness and global assessment. 2.6 Statistical analysis The statistical analysis was performed using the SPSS software (SPSS, Chicago, Illinois, USA), version 20.0. When analysing the physico-chemical properties and antioxidant activity data, the normality and homogeneity of variance were always checked by the Shapiro-Wilk and Levene Tests, respectively. When both conditions failed the nonparametric Kruskal-Wallis test was applied, followed by multiple comparison of order means. On contrary, when normality and homogeneity of variances were observed, an ANOVA followed by Tukey post-hoc test was used. Regarding the sensory analysis data, the nonparametric Kruskal-Wallis test was applied because ordinal variables were used. To check whether there were differences between the first and second days for the jelly that was repeated ('Tinta Barroca' grape jelly), it was used the Wilcoxon-Mann-Whitney test. 3 RESULTS AND DISCUSSION 3.1 Physico-chemical characterization of grape jellies The juices of the seven grapevine varieties studied in the present work had different total soluble solid contents, varying between 19.1 °Brix and 33.5 °Brix for 'Touriga National' and 'Trincadeira Preta', respectively. These values indicated differences in grapes sweetness. Concerning grape jellies, their physico-chemical characterization is shown in Table 1. The moisture contents ranged from 38.6% ('Periquita') to 45.0% ('Touriga National') and ash levels between 0.4% ('Cornifesto') and 0.7% ('Marufo'), suggesting a higher mineral content in this jelly. Regarding colour and in particular lightness (L*), differences on jellies colour were found. 'Periquita' jelly was the one with the highest L* value (33.44), indicating that it was the clearest jelly, while 'Tinta Carvalha' was the darkest (31.84) jelly. Concerning a* (-green-red+) and b* (-blue-yellow+) parameters, the highest values were obtained for 'Tinta Carvalha' and 'Marufo' jellies, respectively, whereas 'Tinta Barroca' and 'Tinta Carvalha' jellies presented the lowest values. Accordingly, the differences found in grape jellies colour depended on grape variety. Regarding pH and acidity, significant differences between jellies were also observed. pH varied between 3.60 ('Marufo') and 3.74 ('Touriga National') and acidity between 0.7% ('Tinta Barroca') and 1.0% ('Touriga National'). These results indicated that jellies prepared from some grapevine varieties were significantly different in colour because they had different CIELab parameters, as well as in flavour, due to differences on pH and acidity values, allowing the production of a wider range of and wishes. products that may meet different consumer's tastes Table 1: Physico-chemical parameters of the jellies prepared in the present work from seven grapevine varieties Variety Moisture (%) Ash (%) L* Colour a* b* PH Acidity (% tartaric acid) Cornifesto 42.00±0.07a 0.40±0.06a 32.42±0.08b,d 0.05±0.01b,c 0.88±0.02a,b 3.64±0.01b 0.85±0.03a,b,c Marufo 41.04±0.06a,b 0.69±0.08a 32.40±0.19a,b,d 0.27±0.03a 1.00±0.07a 3.60±0.06a-b 0.73±0.00a Periquita 38.59±0.14b 0.56±0.02a 33.44±0.18c 0.09±0.03b 0.90±0.04a 3.68±0.01a 0.82±0.01c Tinta Barroca 43.49±0.06d 0.51±0.0C 32.22±0.01d -0.09±-0.04c 0.88±0.01a 3.71±0.02a-b 0.72±0.01a Tinta Carvalha 43.90±0.43d 0.58±0.14a 31.84±0.05a 0.41±0.04a 0.77±0.04a,b 3.62±0.01b 0.75±0.14a,b,c Touriga Nacional 44.97±0.29c 0.56±0.10a 32.31±0.02b,d 0.09±0.01bc 0.81±0.05b 3.74±0.01a 1.01±0.00b Trincadeira Preta 42.93±0.44d 0.51±0.02a 32.43±0.04b 0.04±0.01b,c 0.86±0.02a,b 3.66±0.01b 0.74±0.01a *Different letters in the same column indicate significant differences (p < 0.05) 3.2 Antioxidant activity 3.2.1 Total Reducing Capacity (TRC) TRC was measured according the Folin-Ciocalteau's assay. This method is currently used and the results are usually expressed in total phenols content; however, once different chemicals react (reducing saccharides, proteins, etc...) with this reagent (Singleton et al., 1999), the value of total phenols is overestimated. So, the use of total reducing capacity is more accepted. The TRC of the extracts prepared from the jellies produced in the present work and from the berry skins are given in Figures 1A and 1B, respectively. The TRC of the jellies extracts were much lower than those of the berry skin extracts. These results were expected, since jellies were prepared from grape pulp and skins, as well as sucrose, being the skins the richest constituent in total phenols. 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 70 60 « U ü n = 3 ■o < _ M) 3 £ 50 ; ^ 30 3 s 10 Cornifesto Tinta Carvalha Touriga Trincadeira Nacional Preta Figure 1: Total Reducing Capacity (mg GAE g- of extract) of jellies (A) and skins (B) of seven grapevine varieties. 40 20 0 When comparing grapevine varieties, significantly differences on TRCs of the jellies and skin extracts were found. The TRC of the jellies varied between 0.54 and 1.27 g of GAE kg-1 of extract of 'Tinta Barroca' and 'Tinta Carvalha', respectively. Nevertheless for berry skin extracts, higher TRC values were found and varied between 24.36 g of GAE kg-1 of extract ('Periquita') and 57.05 g of GAE kg-1 of extract ('Touriga National'), respectively, showing that the grapevine varieties with skins with the highest TRCs were not those that originated the jellies with the highest antioxidant potentials. After expressing the TRC in g of GAE kg-1 of jelly (Table 2), the values varied between 0.356 and 0.874 g of GAE kg-1 of jelly for 'Tinta Barroca' and 'Tinta Carvalha' varieties, respectively. The total phenol contents of the grape jellies produced in the present study were much lower than those reported by Falcao et al. (2007) for a model system of a jelly prepared from grapes of 'Isabel' variety, namely 63.4 g of GAE kg-1 of jelly and 95.1 g of GAE kg-1 of jelly when acetone and ethanol at 70% (v/v) were used as extraction solvents. However, even though the extraction solvents used were different to that employed in the present study, the production method of the jelly was much more complex, including the use of gelling agents, citric acid and anthocyanin extracts, which explain the higher antioxidant activity of the jelly produced by Falcao et al. (2007) than ours. Taking into account the fruit quantity used in jelly production, the TRC values expressed on g of GAE kg-1 of fruit weight were determined (TRCfruit). Then, through the skins proportion determined previously for each grapevine variety, the TRCs expected from the berry skins were determined and named by TRCskin (expected), expressed on g of GAE kg-1 of skin. After comparing these concentrations with the TRCs determined for the skins before processing (in natura) (TRCskin (reai)), recovery yields between 14.6% ('Tinta Barroca') and 62.3% ('Periquita') were found, indicating that during jelly production the diffusion rate of phenolic compounds for sucrose solutions or the loss of such compounds due to heating, depended on grapevine variety. In general terms and considering the TRC obtained for all varieties (Table 2 and Figure 1A), 'Tinta Carvalha' seemed to be the most suitable grape variety for jelly production with the highest content of bioactive compounds (0.874 g kg-1 of GAE by jelly weight). Table 2: Total Reducing Capacity (TRC) (mg GAE g-1) of the jellies and berry skins of seven grapevine varieties studied in the present work. Variety TRCjelly (mg GAE gjelly"1) TRCfruit (mg GAE gfruit-1) m(fiuit) (g) m(skin) (g) TRCskin (real) (mg GAE gskin"1) TRCskin (expected) (mg GAE gskin- 1) Recovery Yield TRC skins (%) Cornifesto 0.567 0.85 1.92 0.37 4.41 16.3 27.1 Marufo 0.516 0.77 3.24 0.41 6.12 12.0 50.8 Periquita 0.588 0.88 3.05 0.34 7.92 12.7 62.3 Tinta Barroca 0.356 0.53 2.79 0.56 2.66 18.2 14.6 Tinta Carvalha 0.874 1.31 2.77 0.44 8.26 14.8 55.7 Touriga Nacional 0.679 1.02 2.27 0.29 7.97 19.6 40.6 Trincadeira Preta 0.417 0.63 2.24 0.25 5.60 15.7 35.7 This jelly was the one that also showed the darkest colour (lowest L*) and the highest proportion of red pigments (highest a*), suggesting the presence of a high amount of anthocyanins. Nevertheless, these results also suggest that in the future, it will be of great interest to optimize the process of jelly production in order to extract a high number of phenolic compounds of the skins and increase their recovery yields. 3.2.2 DPPH (2,2-diphenyl-1 -picrylhydrazyl) Radical Scavenging Activity The antioxidant activity determined by the DPPH method for the extract concentration of 5 mg ml-1 (Table 3) showed that the seven grape jellies had different DPPH radical scavenging activities, varying from 9.8% ('Periquita') to 60.0% ('Tinta Carvalha'). The extracts with the highest blocking effect on DPPH radicals were again those of 'Tinta Carvalha' jelly, in line with the TRC results. Regarding berry skins, similar values were obtained within grapevine varieties, ranging between 84.9% ('Tinta Barroca') and 89.9% ('Periquita'). Once again it was found that the skins showed higher antioxidant potential than jellies, since the processing may affect the bioactive compounds present in vegetable products (Marquina et al., 2008). Table 3: DPPH radical scavenging effect (%) for the concentration of 5 mg extract ml-1 of jellies and berry skins of seven grapevine varieties. Variety Jelly Skins Cornifesto 31.8±1.0d,e 88.9±0.4b,c Marufo 22.5±0.5a 88.3±0.8a Periquita 9.8±0.4a 89.9±0.3d,e Tinta Barroca 59.0±1.2e 84.9±0.7e Tinta Carvalha 60.0±0.2c 89.7±0.2b,c Touriga Nacional 42.3±0.8b 87.7±0.4b Trincadeira Preta 28.1±0.4c,d 88.9±0.6c,d *Different letters in the same column indicate significant differences (p < 0.05). 3.2.3 Reducing Power present work increased with the extract -n j- r^-i n- j i- ...... concentration (Figure 2). The reducing power of the jellies and skins extracts ° of the seven grapevine varieties studied in the 1.20 1.00 0.80 s o o 0.60 w -1= < 0.40 0.20 0.00 0 1.20 1.00 Is 0.80 s o 0.60 -o < 0.40 0.20 0.00 2.0 5 10 15 20 Extract concentration (mg-ml-1) 2.2 2.4 2.6 2.8 Extract concentration (mg-ml-1) Cornifesto Marufo Periquita Tinta Barroca Tinta Carvalha —^—Touriga Nacional —^Trincadeira Preta 3.0 Figure 2: Reducing power (Abs 700 (nm)) versus extract concentration of jellies (A) and berry skins (B) of seven grapevine varieties. However, it should be referred that similar reducing powers were obtained with solutions of skin extracts ten times more diluted than those of grape jellies. These results explained the EC50 values obtained (Table 4), being the lowest values determined for the skins (2.19 mg ml-1 to 2.60 mg ml-1). Jellies presented higher EC50 values, varying between 9.17 mg ml-1 and 41.28 mg ml-1 for 'Tinta Carvalha' and 'Periquita' grape varieties, respectively. These results were expected since the EC50 value is inversely proportional to the antioxidant potential, demonstrating that the skins were richer in antioxidants than jellies. Moreover, the jelly produced from 'Tinta Carvalha' variety showed again the lowest EC50 value, suggesting a high antioxidant potential. Our results are in line with Abe et al. (2007) who stated that grapes with darker colour had a higher content of antioxidants. Indeed, as indicated earlier, 'Tinta Carvalha' was the variety that showed the darkest grape berries (lowest L* value) (Table 1) and redness colouration (highest a* value), suggesting the highest anthocyanins concentration, which may led to a jelly with the highest total phenol content (1.27 g kg-1 of GAE), the highest DPPH radical scavenging activity (60.0%) and the lowest EC50 value for the Reducing Power assay (9.17 mg ml-1). Table 4: EC50 values (mg extract ml-1) determined on the reducing power assay of jellies and berry skins of seven grapevine varieties. Variety Jelly Skins Cornifesto 19.70±0.38 2.24±0.00 Marufo 26.93±3.76 2.60±0.08 Periquita 41.28±0.70 2.28±0.00 Tinta Barroca 12.22±0.03 2.19±0.00 Tinta Carvalha 9.17±0.17 2.35±0.00 Touriga Nacional 17.78±0.46 2.54±1.11 Trincadeira Preta 31.97±1.32 2.25±0.00 3.3 Sensory analysis The test for acceptability was carried out by 54 consumers, 34 females and 20 males. The age of consumers ranged from 12 to 55 years. Firstly, we started to compare the results obtained for the jelly analysed in both days. It was observed that most of the parameters evaluated for the 'Tinta Barroca' jelly did not present significantly different scores at a = 0.05 on both days and no significant differences were detected between genders. In more detail, no significant differences on the appearance (p = 0.088), taste (p = 0.054), sweetness (p = 0.309), acidity (p = 0.323) and global assessment (p = 0.077) were observed. However, in terms of colour significant differences were determined (p = 0.003). One possible explanation was that 'Tinta Barroca' jelly was tested simultaneously with other jellies that had different colours, being 'Tinta Barroca' jelly colour judgment influenced by the colour of the other jellies. In fact, if jellies with colour that the consumer liked more were presented on the second day, the panellist would rate lower the colour of the repeated jelly. When comparing the seven grape jellies, no significant differences on the attributes appearance (p = 0.442), taste (p = 0.607), sweetness (p = 0.870), acidity (p = 0.911) and global assessment (p = 0.652) were observed. On contrary, significant differences on colour (p = 0.001) were again observed. Observing Figures 3 and 4, it can be seen that all evaluated attributes presented medians above the 5 point scale (indifferent), being most of the cases close to 7 (like moderately). In terms of global evaluation, all jellies presented a sensory profile almost totally situated in the region of acceptance (>5.00). Regarding colour, 'Tinta Carvalha' and 'Marufo' jellies were the worst rated. On contrary, 'Tinta Barroca' was the preferable jelly mainly on the 2nd day, followed by 'Touriga National' on the same day, and 'Cornifesto' and 'Trincadeira Preta' on the 1st day. Generally, these results indicated that the seven grape jellies will have good acceptance by consumers, revealing good perspectives to broaden the application of grapes in food industry. Figure 3: Box-plots obtained for the appearance (A), taste (B), acidity (C), sweetness (D) and global assessment (E) of jellies produced from seven grapevine varieties. (Not significant at a = 0.05) b I. h ft 4 1 IDT 12« 33 I I Trc* Cnrviilia Ti*j Burrocn Ccmifeslo Trfan^Jein Pre« Figure 4: Box-plots obtained for the colour evaluation of the grape jellies on the first (A) and second (B) days of sensory analysis. 4 CONCLUSIONS The present work showed that jelly production using different grapevine varieties seems to be a good option for small grape farmers and industrials and it will allow the valorisation of grapevine varieties with less potential for wine production and the preservation of grape biodiversity. After performing the physico-chemical characterization of the jellies significant differences were found in colour, pH, ash content and acidity, indicating that the production of grape jellies with different characteristics is possible in the future, meeting the wishes of a greater number of consumer types. 'Tinta Carvalha' jelly was the one that showed the highest amount of bioactive compounds, being also the darkest and redness jelly. Even though processing may cause the loss of some antioxidant activity, our results showed that jellies still have antioxidant potential and may emerge as an interesting product for the market, as they continue to maintain bioactive properties of the fresh fruit. Regarding sensory analysis, no significant differences were found among the seven jellies studied for most of the parameters, except colour. Regarding the overall assessment, consumers classified them as enjoyable. 5 ACKNOWLEDGMENTS Authors are grateful to POCTEP - Programa de Coopera^ao Transfronteiri?a Espanha - Portugal for financial support (Project "RED/AGROTEC - Experimentation network and transfer for development of agricultural and agro industrial sectors between Spain and Portugal). 6 REFERENCES Abe, L.T., Vieira da Mota, R., Lajolo, F.M.,Genovese, M.I. 2007. , Phenolic compounds and antioxidant capacity of Vitis labrusca L. and Vitis vinifera L. grape cultivars. 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Analysis of total phenols and other oxidation substrates and antioxidants by means of Folin-Ciocalteu reagent. Methods in Enzymology. 299: 152-178. http://www.sciencedirect.com/science/article/pii/S0 076687999990171 (30. jan. 2014) COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.05 Agrovoc descriptors: ganoderma lucidum, grifola, lentinus edodes, sporophores, fungal morphology, edible fungi, oilseed cakes, byproducts, growing media Agris category code: f60, p35 Cultivation of three medicinal mushroom species on olive oil press cakes containing substrates Andrej GREGORI1*, Franc POHLEVEN2 Received January 08, 2014; accepted January 17, 2014. Delo je prispelo 08. januarja 2014, sprejeto 17. januarja 2014. ABSTRACT IZVLEČEK Olive oil press cakes (OOPC) represent a waste that has a negative impact on environment. OOPC have little or no use and because of that solutions for their alternative use are sought after. In our experiments we investigated substrate mixtures composed of different proportions of OOPC, wheat bran, crushed corn seeds and beech sawdust for cultivation of Ganoderma lucidum, Lentinula edodes and Grifola frondosa fruiting bodies. The increasing amount of OOPC in fruiting bodies cultivation substrates resulted in decreasing production of fruiting bodies. Results show, that although OOPC in small portion can be successfully used as a medicinal mushroom fruiting bodies cultivating substrate, their use is rational only, if no other substrate composing materials can be found or when OOPC usage solves the problem of its deposition. Key words: Ganoderma lucidum, Grifola frondosa, Lentinula edodes, mushroom cultivation, olive oil press cakes GOJENJE TREH VRST MEDICINSKIH GOB NA SUBSTRATIH VSEBUJOČIH OLJČNE TROPINE Oljčne tropine (OT) predstavljajo odpadek s škodljivim vplivom na okolje in omejenimi možnostmi uporabe. OT imajo malo ali nobene uporabne vrednosti, zaradi česar se išče načine za njihovo alternativno uporabo. V naših poizkusih smo preizkušali substrate iz različnih deležev OT, pšeničnih otrobov, zdrobljenega koruznega zrnja in bukove žagovine za gojenje trosnjakov gliv Ganoderma lucidum, Lentinula edodes in Grifola frondosa. S povečevanjem deleža OT v substratu smo opazili trend zmanjševanja biološke učinkovitosti obroda. Rezultati kažejo, da čeprav lahko OT v manjših deležih uspešno uporabimo za substrat za gojenje trosnjakov, je to smotrno le v primerih, ko ni na voljo drugih primernejših sestavin substrata ali takrat, ko je dodatek OT namenjem preprečavanju negativnih vplivov teh odpadkov na okolje. Ključne besede: Ganoderma lucidum, Grifola frondosa, Lentinula edodes, gojenje gob, oljčne tropine 1 INTRODUCTION Olive oil press cakes (OOPC) represent a waste with a great negative impact on environment in Mediterranean countries, where many olive oil producing plants are located. OOPC have little or no use and solutions for their alternative use are sought after. It is well known that mushrooms can be cultivated on broad assortment of organic matter, including sawdust, straw, weeds, husks, compost and others. There were also reports of successful OOPC usage as a mushroom cultivating media (Soler-Rivas et al., 2006; Ruiz-Rodriguez et al., 2010; Zervakis et al., 2013). dr., Zavod za naravoslovje (Institute for natural sciences), Ulica bratov Učakar 108, 1000 Ljubljana, Slovenia; MycoMedica d.o.o., Podkoren 72, 4280 Kranjska Gora, Slovenia, coresponding author: E-mail: andrej.gregori@zanaravo.com 2 prof. dr., Biotechnical Faculty, University of Ljubljana, Department of Wood Science and Technology, Rožna dolina, Cesta VIII/34, 1000 Ljubljana, Slovenia All experiments were performed at the mycology laboratory of MycoMedica d.o.o., Podkoren 72, 4280 Kranjska Gora, Slovenia Ganoderma lucidum (Curtis) P. Karst., Grifola frondosa (Dicks.) Gray and Lentinula edodes (Berk.) Pegler are popular medicinal mushrooms with immune system strengthening, anticholesterolemic, antitumor, hepatoprotective, antidiabetic and other medicinal properties (Wasser, 2010; Powel, 2010). Successful cultivation of these species on OOPC containing substrates would have multiplicative positive effects, firstly on environment being polluted by OOPC and secondly on humans ingesting the cultivated fruiting bodies and medicinal substances they contain. In our experiments we tested substrate mixtures composed of different portions of OOPC, wheat bran and beech sawdust for cultivation of Ganoderma lucidum, Lentinula edodes and Grifola frondosa. We aimed to analyze how medicinal mushroom cultivation substrates containing variable OOPC concentration influence the production of G. lucidum, L. edodes and G. frondosa fruiting bodies. 2 MATERIALS AND METHODS Lentinula edodes strain No. 4080, Ganoderma lucidum strain Gal5 from culture collection of Zavod za naravoslovje (Institute for natural sciences), Ljubljana, and Grifola frondosa strain Gf3 from fungal collection of Wood Science and Technology department, Biotechnical Faculty, University of Ljubljana, Slovenia were used. Cultures were maintained on potato dextrose agar (Difco) at 24 °C. Substrates were composed of variable proportions of OOPC (Torklja, Koper, Slovenia), beech sawdust (BS) (Gorazd Rant s.p., Železniki, Slovenia), wheat bran (WB) (Mlin Katic, Velika vas pri Krškem, Slovenia) and gypsum (Rigips Austria GmbH, Saint-Gobain, Austria) (Table 1). Substrate components were mixed and water content adjusted to 65 %. Substrate was filled into polypropylene bags with breathing filters (3.5 kg for L. edodes and G. lucidum and 3.0 kg for G. frondosa) and sterilized for five hours at 121 °C. At least four replicates were prepared for each substrate mixture. Table 1. Substrate mixtures used for Lentinula edodes, Grifola frondosa and Ganoderma lucidum cultivation Olive oil press cakes (OOPC) (%) Wheat bran (WB) (%) Beech sawdust (BS) (%) Gypsum (%) 80 18 0 2 60 18 20 2 40 18 40 2 20 18 60 2 0 18 80 2 After the sterilization and cooling process substrates were inoculated with 100 g of Ganoderma lucidum, Lentinula edodes or Grifola frondosa mycelium, cultivated on rye grains, mixed by hand and incubated at 24 ± 1 °C in a dark growth chamber. When the surface of the overgrown substrate became dark brown (L. edodes) or when primordia started to form (G. frondosa and G. lucidum), bags were moved into cultivation room with 17 ± 2 °C, 10 hours of light daily and 80 % relative humidity. Fruiting bodies were harvested after they fully matured and their fresh weight determined. Biological efficiency (BE), being fresh fruiting bodies weight divided by weight of fresh substrate, multiplied by 100, was calculated (Royse and Sanchez-Vasquez, 2003). Because G. lucidum fruiting bodies are usually used and sold in dry form, BE for this species was calculated using dry weight of fruiting bodies after drying at 60 °C for 48 hours (to constant weight). All experiments were conducted in a mycological Podkoren (Slovenia). laboratory of MycoMedica d.o.o. company, 3 RESULTS Lentinula edodes mycelium tends to grow slower and in some cases ceases to grow, if the substrates contained 80 % OOPC (Figure 1). Also there was a negative impact of OOPC on the growth of L. edodes mycelia and also its maturation. Substrates containing higher proportions of OOPC had a tendency to mature (change of color) later than substrates with lower OOPC share (Figure 1). Figure 1. Substrates inoculated with Lentinula edodes mycelia containing (from left to right column) 80 %, 60 %, 40 %, 20 % or 0 % olive oil press cakes (OOPC). Highest BE (38 %) of L. edodes fruiting bodies was calculated on substrates composed of 0 % OOPC, 80 % BS, 2 % gypsum and 18 % WB. Biological efficiency of fruiting bodies decreases in correlation to increasing proportions of OOPC in the growing substrates. When substrate contained 80 % OOPC, fruiting bodies ceased forming completely (Figure 1). Figure 2. Deformed Ganoderma lucidum fruiting bodies emerging from substrate containing 80 % olive oil press cakes. Figure 3. Non-deformed Ganoderma lucidum fruiting bodies emerging from substrate containing without olive oil press cakes. Biological efficiency of Grifola frondosa fruiting bodies was reduced with increasing share of OOPC in the cultivating substrate. With G. frondosa higher fruiting bodies yields (62 %) were obtained on substrates not containing OOPC (Figure 4). Ganoderma lucidum fruiting bodies yields also decreased with increasing portions of OOPC in the growth substrate (Figure 4). At higher OOPC content (60 % and 80 %) in the substrate fruiting bodies tended to have slight deformations in the shape (Figure 2), and were more sensitive to mold and bacterial infections. Development of G. lucidum fruiting bodies on 0 % OOPC containing substrates was not hindered (Figure 3). Figure 4. Biological efficiency (BE (%)) of Lentinula edodes, Ganoderma lucidum and Grifola frondosa fruiting bodies cultivated on olive oil press cakes containing substrates. (BE (%) of Ganoderma lucidum was calculated for dry fruiting bodies.) 4 DISCUSSION Higher proportions of OOPC contained in cultivation substrates hindered the formation of Lentinula edodes, Ganoderma lucidum and Grifola frondosa fruiting bodies (Figure 4) and as well caused their deformation (Figure 2). With substrates not containing OOPC no yield reduction and fruiting bodies deformation was noticed (Figure 3). With L. edodes hindered mycelial growth was noticed immediatelly after inoculation (when mycelia ceased to grow completely), and during the substrate incubation period (when mycelia was maturing slower) compared with other substrates (Figure 1). Hindered mycelia growth during incubation period as well as decrease of fruiting bodies yield on OOPC containing substrates could be the consequence of polyphenols contained in OOPC (Lakhtar et al., 2010; Zervakis et al. 2013). Beside polyphenolic compounds, a low porosity of OOPC and consequently lower substrate aeration and low water retaining capacity could be the reason for slower mycelial growth and lowered yields of fruiting bodies. It was found out that aeration greatly influences mycelial overgrowth and L. edodes fruiting bodies yields (Kalberer, 1995; Donoghue and Deninson, 1995). On the other hand fungal species and strains ability to utilize OOPC, or exposition to higher content of polyphenolic compounds in the substrate could have a significant influence on fruiting body yields. Strain characteristics tend to strongly influence mycelial growth as well as quantity and quality of produced fruiting bodies (Diehle and Royse, 1986; Royse and Bahler, 1986). Reduction of fruiting bodies yields on higher proportions of OOPC containing substrates is in accordance to the findings of other authors, who tested OOPC as a substrate component for cultivation of Pleurotus ostreatus (Ruiz-Rodriguez et al., 2010), Pleurotus pulmonarius (Soler-Rivas et al., 2006) as well as other Pleurotus and Agrocybe cylindracea species (Zervakis et al., 2013). Nevertheless, the results show that OOPC in small proportions can be successfully used as a supplement to the medicinal mushrooms cultivating substrate. This application is reasonable only, if no other substrate composing materials are available, or when OOPC usage solves the problem of its deposition. Zervakis and coworkers (2013) found that composting of olive mill waste greatly increases the BE of produced fruiting bodies. This method could be used also with OOPC, potentially reducing its negative effect on mycelium growth and mushroom yields. 5 ACKNOWLEDGEMENTS This research work was financed by the Slovenian Research Agency (applicative research project No. L2-7598), Perutnina Ptuj d.d. and the Municipality of Ptuj. We would like to thank all of them for their support. 6 REFERENCES Diehle, D. A., Royse, D. J., 1986: Shiitake cultivation on sawdust: evaluation of selected genotypes for biological efficiency and mushroom size. Mycologia 78: 929-933, DOI: 10.2307/3807433. Donoghue, J. D., Denison, W. C., 1995: Shiitake cultivation: Gas phase during incubation influences productivity. Mycologia 87: 239-244, DOI: 10.2307/3760909. Kalberer, P. P., 1995: An investigation of the incubation phase of a shiitake (Lentinus edodes) culture. Mushroom Science 14: 375-383. Lakhtar, H., Ismaili-Alaoui, M., Philippoussis, A., Perraud-Gaime, I., Roussos, S., 2010: Screening of strains of Lentinula edodes grown on model olive mill wastewater in solid and liquid state culture for polyphenol biodegradation. International Biodeterioration and Biodegradation 64: 167-172, DOI: 10.1016/j.ibiod.2009.10.006. Powell M., 2010: Medicinal mushrooms: A clinical guide. 1st ed. Mycology press, East Sussex. pp. 128. Royse, D. J., Bahler, C. C., 1986: Effects of genotype, spawn run time and substrate formulation on biological efficiency of shiitake. Applied Environmental Microbiology 52: 1425-1427. Royse, D. J., Sanchez-Vasquez, J., 2003: Influence of precipitated calcium carbonate (CaCO3) on shiitake (Lentinula edodes) yield and mushroom size. Bioresource technology 90: 225-228, DOI: 10.1016/S0960-8524(03)00119-6. Ruiz-Rodriguez, A., Soler-Rivas, C., Polonia, I., Wichers, H. J., 2010: Effect of olive mill waste (OMW) supplementation to Oyster mushrooms substrates on the cultivation parameters and fruiting bodies quality. International Biodeterioration and Biodegradation 64: 638-645, DOI: 10.1016/j.ibiod.2010.07.003. Soler-Rivas, C., Garcia-Rosado, A., Polonia, I., Junca-Blanch, G., Marin, R. F., Wichers, J. H., 2006: Microbiological effects of olive mill waste addition to substrates for Pleurotus pulmonarius cultivation. International Biodeterioration and Biodegradation 57: 37-44, DOI: 10.1016/j.ibiod.2005.10.007. Wasser, S. P., 2010: Shiitake. In: Encyclopedia of dietary supplements. (Eds., Coates, P.M., Betz, J.M., Blackman, M.R., Cragg, G.M., Levine, M., Moss, J., White J.D.), Informa Healthcare, New York, pp. 719-726, DOI: 10.1201/b14669-83. Zervakis, G. I., Koutrotsios, G., Katsaris, P., 2013: Composted versus Raw Olive Mill Waste as Substrates for the Production of Medicinal Mushrooms: An Assessment of Selected Cultivation and Quality Parameters. BioMed Research International, Volume 2013 (2013), Article ID 546830, 13 pages. COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.06 Agrovoc descriptors: vitis vinifera, grapevines, genetic variation, land varieties, plant anatomy, germplasm, genetic markers, selection Agris category code: f30 The characterisation of Vitis vinifera 'Refošk' with AFLP and SSR molecular markers and ampelographic traits Matjaž HLADNIK1, Jernej JAKŠE2, Dunja BANDELJ3, Irma VUK4 Received September 27, 2013; accepted February 10, 2014. Delo je prispelo 27. septembra 2013, sprejeto 10. februarja 2014. ABSTRACT IZVLEČEK The genetic diversity and ampelographic variability of autochthonous red wine cultivar 'Refosk' (Vitis vinifera L.) grown in Slovenia were evaluated with AFLP molecular markers and OIV descriptors, respectively. SSR molecular markers were employed to confirm cultivar identity of analysed samples. Eight AFLP primer combinations, one was monomorphic, produced 16 polymorphic markers in 41 out of 113 samples, what classified samples into monomorphic and polymorphic group. Dendrogram constructed with simple matching coefficient and unweighted pair-group method analysis presented genetic diversity within polymorphic group. Refosk biotypes from monomorphic and polymorphic groups were evaluated with 22 OIV descriptors related to bunch, berry and must, but on the basis of ampelographic characterization samples were not differentiated among two major groups obtained with AFLP analysis. Results of genetic analysis indicated that 'Refosk' originated from closely related plants that are phenotypically very similar. With regard to low observed genetic diversity more attention should be dedicated to the selection in order to conserve remaining genetic diversity. Key words: AFLP, genetic diversity, SSR, cultivar identity, morphological traits, germplasm, grapevine, Refosk, Refosco KARAKTERIZACIJA ŽLAHTNE VINSKE TRTE (Vitis vinifera L.) SORTE 'REFOŠK' Z AFLP IN SSR MOLEKULSKIMI MARKERJI IN AMPELOGRAFSKIMI LASTNOSTMI Z AFLP molekulskimi markerji in z OIV deskriptorji je bila ovrednotena genetska variabilnost in ampelografska raznolikost avtohtone sorte 'Refošk' (Vitis vinifera L.) v Sloveniji. Sortna pristnost analiziranih vzorcev je bila potrjena z mikrosatelitskimi markerji. Pri 41 vzorcih od skupno 113 smo z uporabo osmih parov začetnih selektivnih oligonukleotidov, od katerih je bila ena kombinacija monomorfna, odkrili 16 polimorfnih markerjev. Na podlagi rezultatov AFLP analize smo vzorce razvrstili v dve skupini in sicer v monomorfno in polimorfno skupino. Dendrogram, narejen na podlagi koeficientov enostavnega ujemanja in z metodo netehtanih parnih skupin z aritmetično sredino prikazuje genetsko variabilnost znotraj polimorfne skupine. Trse iz različnih genetskih skupin smo ovrednotili z 22 OIV deskriptorji, ki se nanašajo na grozd, jagode in mošt, vendar se na podlagi ampelografske karakterizacije niso razvrstili v skladu z razvrstitvijo pri AFLP analizi. Rezultati nakazujejo na izvor sorte 'Refošk' iz sorodnih, fenotipsko zelo podobnih starševskih rastlin. Glede na nizko število dobljenih polimorfnih AFLP markerjev bi morali intenzivneje delati na selekciji sorte 'Refošk' z namenom ohranitve obstoječe genetske variabilnosti. Ključne besede: AFLP, genetska variabilnost, SSR, sortna pristnost, morfološke lastnosti, dednina, vinska trta, Refošk, Refosco University of Primorska, Science and Research Centre, Garibaldijeva 1, SI - 6000 Koper, Slovenia, matjaz.hladnik@zrs.upr.si; University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI - 6000 Koper, Slovenia, matjaz.hladnik@upr.si Ph.D., University of Ljubljana, Centre for Plant Biotechnology, Jamnikarjeva 101, SI - 1000 Ljubljana, Slovenia, jernej.jakse@bf.uni-lj.si Ph.D., University of Primorska, Science and Research Centre, Garibaldijeva 1, SI - 6000 Koper, Slovenia, dunja.bandelj@zrs.upr.si; University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI - 6000 Koper, Slovenia, dunja.bandelj@upr. si Ph.D., University of Primorska, Science and Research Centre, Garibaldijeva 1, SI - 6000 Koper, Slovenia, irma.vuk@zrs.upr.si; University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI - 6000 Koper, Slovenia, irma.vuk@upr. si 2 1 INTRODUCTION The red wine cultivar 'Refosk' (Vitis vinifera L.), in Italy known as Refosco del Carso, Refosco d'Istria or Terrano d'Istria, and in Croatia as Refosk istarski or Teran is a member of the Refosco family. In Slovenia it is cultivated mainly in the Kras and the Slovenska Istra winegrowing districts where it presents 73 % and 45 % of the vineyards area, respectively (MOP, 2011), totalling 1.200 hectares. In the Karst region the produced wine is Karst Teran with high lactic acid and mineral iron contents in comparison with Refosk wine produced from the same cultivar in Slovenian Istria, due to pedoclimatic factors. Content of anthocyanins in Refosk grapes is similar to that in Cabernet Sauvignon (Vrhovesk et al., 2002). 'Refosk' represents one of the earliest cultivated cultivars in this region and due to several biotypes, the ampelographers are still not in agreement on the basic traits of the cultivar. However, it is already known that Italian types of Refosco (e.g. Refosco dal peduncolo rosso, Refoscone, Refosco nostrano, Refosco di Rauscedo) are morphologically and genetically different from 'Refosk' grown in Slovenia (Cipriani et al., 1994; Plahuta and Korosec-Koruza, 2009). In 1989 a collection vineyard in Komen (the Karst district) was established with the aim to choose appropriate clones and to preserve the old local Refosk biotypes. Since only one clone of 'Refosk' is officially certified, there is great need to promote further selection process. Ampelography is essential in order to obtain information about viticultural performance of cultivars and clones included in selection. This method is based on phenotypic traits that are heavily influenced by different environmental conditions as well as nutritional state and health (Mannini, 2000; Sefc et al., 2001), thus DNA analysis approaches are frequently used in the characterisation of grapevine germplasm (Barth et al., 2009; Maria Ortiz et al., 2004). Kozjak et al. (2003) tested some selected accessions from the collection vineyard in Komen with 6 microsatellite loci, also known as simple sequence repeats (SSR), and found that two Refosk samples are probably different from cultivar Refosk, showed different patterns, while other accessions revealed identical SSR allelic profiles. The insufficient clone discrimination ability of SSR molecular markers was also stated in other papers (Imazio et al., 2002; Laucou et al., 2011), although microsatellite markers have been widely used for grapevine cultivar identification, defining synonyms and homonyms, and for pedigree reconstruction (Cipriani et al., 2010; Laucou et al., 2011; Rusjan et al., 2012). Molecular markers that have been used on grapevine in several studies to detect intravarietal variability are the inter simple sequence repeats (ISSR) (Regner et al., 2000), amplified fragment length polymorphism (AFLP) (Cervera et al., 1998; Fanizza et al., 2003; Imazio et al., 2002; Konradi et al., 2007; Meneghetti et al., 2012), selective amplification of microsatellite polymorphic loci (SAMPL) (Cretazzo et al., 2010; Meneghetti et al., 2012), microsatellite amplified fragment length polymorphism (M-AFLP) (Cretazzo et al., 2010; Meneghetti et al., 2012) and specific sequence amplified polymorphism (S-SAP) (Carrier et al., 2012; Stajner et al., 2009). Identifying and preserving rare genetic diverse plant material is highly recommended in order to maintain the existing genetic variability within a cultivar to allow a good response to the natural selection pressure (new pests, environmental and management changes, etc.) and to enhance the quality and complexity of wines (Mannini, 2000). The objectives of this work were to assess the genetic variability of the Refosk cultivar planted in the collection vineyard in Komen and in production vineyards in the Kras and Slovenska Istra winegrowing districts with AFLP markers. Microsatellite markers were employed to confirm the cultivar identity of analysed samples. Ampelographic characters of Refosk biotypes chosen on the basis of AFLP results were describe with OIV described. 2 MATERIAL AND METHODS 2.1 Plant material Refosk samples were taken from: a collection vineyard established in Komen (N45 48.917 E13 44.692) (biotypes No. 1-35, 37-54, 56, 58-67, 69, 70, 73, 74 and 76, all together 69 samples); thirteen production vineyards randomly chosen in the Kras and Slovenska Istra winegrowing districts (41 samples) and three vines from Merce, Sepulje and Marezige, each more than 150 years old, were also included in analysis (Table 1). A total of 113 samples were included in the analysis. 2.2 DNA isolation Genomic DNA for SSR and AFLP analysis was extracted from young leaves of shoot tips using the modified cetyltrimethylammonium bromide (CTAB) method described by Kump and Javornik (1996). The DNA was quantified by fluorometric determination using the Quant-iTTM dsDNA Broad-Range (BR) Assay Kit by the QubitFluorometer (Invitrogen, Darmstadt, Germany). Table 1. List of Refosk samples used for SSR and AFLP analysis from production vineyards, together with old Refosk vines Origin Code Year of planting Coordinates Winegrowing district Križ (a) is, 3s, 7s, Bs, 10s 2002 N45 44.566 E13 51.905 Kras Križ (b) 12s, 13s, 17s, IBs, 19s, 20s 2005 N45 44.566 E13 51.905 Kras Tomaj 21s, 25s, 26s, 28s, 29s, 30s 1970 N45 45.220 E13 51.077 Kras Godnje 37s, 3Bs, 39s, 40s 1990 N45 45.399 E13 50.434 Kras Dutovlje (a) 45s, 46s, 47s 2002 N45 45.203 E13 49.B05 Kras Dutovlje (b) 54s, 5Bs 195B N45 45.204 E13 49.B05 Kras Krajna vas 63s 1999 N45 45.B70 E13 4B.119 Kras Šepulje 72s app. 17B0 N45 45.0B0 E13 52.191 Kras Merče 73s app. 1700 N45 42.071 E13 54.047 Kras Prade 3k, 5 k, 10k 199B N45 32.903 E13 46.909 Slovenska Istra Pobegi (a) 11k, 12k, 13k, 15k 19B0 N45 32.266 E13 47.156 Slovenska Istra Marezige 1Bk app. 1BB0 N45 30.3B3 E13 4B.143 Slovenska Istra Truške 19k, 20k, 21k, 22k 2000 N45 29.674 E13 4B.960 Slovenska Istra Boršt 33k 19B0 N45 2B.647 E13 46.903 Slovenska Istra Izola 36k 2001 N45 31.745 E13 40.2BB Slovenska Istra Pobegi (b) 41k 2003 N45 32.0B1 E13 47.396 Slovenska Istra 2.3 Microsatellite analysis To prove cultivar identity, six previously described microsatellite loci were analysed: VVMD5, VVMD7 (Bowers et al., 1996); VVMD27, VVMD32 (Bowers et al., 1999); ssrVrZAG62 and ssrVrZAG79 (Sefc et al., 1999). Amplifications were made with the economic method described by Schuelke (2000) where the loci specific primer was elongated for M13 sequence and four M13 primers fluorescently labelled with dye phosphoramidites (6-FAM, VIC, PET or NED) were used in PCR as well. In a total volume of 15 ^l the PCR reaction mixture contained 20 ng of genomic DNA, 1 x Taq Buffer with (NH^SO^ 0.2 mM of each dNTP, 2 mM MgCl2, 0.2 ^M of each primer (Integrated DNA Technologies, Leuven, Belgium), 0.25 ^M of M13 fluorescent primer (Applied Biosystems, Cheshire, UK) and 0.375 U of Taq DNA polymerase. All chemicals were supplied by Fermentas/Thermo Fisher Scientific, MA, USA. PCR reactions were carried out in a 2720 thermal cycler (Applied Biosystems, Darmstadt, Germany) with a two-step PCR protocol started with initial touchdown cycle: 94 °C for 5 min, followed by five cycles of 30 s at 94 °C, 30 s at 60 °C, which was lowered by 1 °C each cycle, 90 s at 72 °C, followed by 30 cycles with annealing temperature at 55 °C and ending with an 8-min extension step at 72 °C. PCR products were multiplexed as shown in Table 2 and separated by capillary electrophoresis on an Applied Biosystems 3130 Genetic Analyser, using GeneScan™ -500 LIZ® (Applied Biosystemsh, Cheshire, UK) as size standard. 2.4 AFLP analysis AFLP analysis was performed on 113 samples according to Vos et al. (1995) with the modifications described below. Each 500 ng sample of genomic DNA was digested with Tru 1I (Msel iso-schizomer) and PstI (3 U each) restriction endonucleases for 120 min at 37 °C (PstI incubation temperature) and 120 min at 65 °C (Tru1I incubation temperature) in a 40 ^l volume in the presence of 1x Buffer R. After restriction 10 ^l of ligation mix, including 50 pmol of MseI adapters, 5 pmol PstI adapters, 2 ^l 10 mM ATP, 10x T4 DNA ligase buffer and 1 U T4 ligase was added to restriction reaction. Adapters were prepared by adding equimolar amounts of both strands (Integrated DNA Technologies, Leuven, Belgium). Ligation was performed at 22 °C for 60 min, followed by the final step at 65 °C for 10 min to inactivate enzymes. The pre-amplification of DNA templates (50 ng) was performed in 50 ^l volume with non-selective PstI and MseI primers in a final concentration 0.2 ^M, 2 mM MgCl2, 0.2 mM of each dNTP, 1x Taq Buffer with (NH4)2SO4 and 1.25 U Taq DNA polymerase. Selective amplifications were performed in a volume of 10 ^l containing the following components: 2 ^l 10-times diluted pre-amplification products, 1x Taq Buffer with (NH4)2SO4, 2 mM MgCl2, 0.2 mM of each dNTP, 0.2 ^M with fluorescent dye (6-FAM, VIC, PET) labelled PstI primer (Applied Biosystems, Cheshire, UK), 0.2 ^M unlabelled MseI primer and 0.25 U Taq DNA polymerase. Selective amplifications were performed using a total of seven primer combinations with two or three selective nucleotides (Table 3). Primer pairs were chosen based on previous testing of 56 combinations on 8 samples (PstI primers with selective nucleotides: ATA, AAC, AGA and ACA; MseI primers with selective nucleotides: AG, CG, CA, AC, CC, CTT, CAT, CAA, CAG, CAC, CTG, CTA, CTC, ACC) with the aim of obtaining an optimized number of scorable bands for every primer combination (data not shown). PCR protocols were as described by Vos et al. (1995), except preamplification was performed with the initial step of 2 min at 72 °C. PCR products were multiplexed (as shown in Table 3), and separated by capillary electrophoresis with GeneScanTM -500 LIZ® (Applied Biosystemsh, Cheshire, UK) as internal size standard on an Applied Biosystems 3130 Genetic Analyser. All accessions were analysed twice (DNA restriction, pre-amplification and selective amplification) to test the reproducibility of the AFLP profiles. 2.5 Ampelographic Analysis Twelve Refosk biotypes, chosen on the basis of AFLP results, grown in the collection vineyard were described with 22 OIV descriptors related to bunch, berry and must (2nd edition of the OIV descriptor list for grape varieties and Vitis species) (O.I.V., 2009). Descriptions were performed on 10 shoots of3 to5 vines per biotype. Vines are grafted on rootstock SO4 (Vitis berlandieri x Vitis riparia), trained as double guyot and cultivated following the instructions of integrated pest management. The vineyard was permanently green covered. Each biotype has 3 to 35 vines planted in the block. 2.6 Data analysis SSR and AFLP electropherograms were analysed and sized with Gene Mapper software version 4.1 (Applied Biosystems, Chesire, UK). AFLP electropherograms were scored for the presence or absence of bands and expressed in binary data, while microsatellite alleles were presented in the amplification lengths. For AFLP, only reproducible, clear bands falling within the range of 50 - 500 bp were considered for analysis. The total number of fragments and percentage of polymorphic fragments were assessed for every primer combination and in the total set. The genetic similarity among clones was calculated using simple matching (SM) genetic distance. A dendrogram was constructed using the unweighted pair group method average (UPGMA) clustering of the NTSYSpc software package, version 2.02i (Rohlf, 1998). Average gene diversity over loci was calculated based on Nei (1987) formula using the Arlequin program (Excoffier and Lischer, 2010). The observed mean values of ampelographic characters were transformed to numerical scales according to the OIV descriptors (O.I.V., 2009). The dendrogram was drawn using UPGMA performed with NTSYSpc 2.02i software (Rohlf, method and distance (DIST) coefficient for interval 1998). measure (quantitative) data. Calculations were 3 RESULTS 3.1 Molecular Analysis The microsatellite analyses confirmed the cultivar identity of all tested Refosk vines. All 113 samples had the same fingerprint at 6 microsatellite loci (Table 2). AFLP analysis, conducted on 113 samples, using eight different primer pairs, produced 208 scorable fragments, 16 of which were polymorphic. One combination generated only monomorphic markers, while 7 combinations were informative. Polymorphic fragments and percentage of polymorphism varied from 1 to 5 loci and from 2.3 to 18.8 % per primer combination, respectively (Table 3). The size of polymorphic amplified products ranged from 100 bp to 397 bp. The AFLP analysis was repeated at least twice and all polymorphic bands were reproducible. In general samples included in analysis could be classified into monomorphic group and polymorphic group since 72 samples showed no polymorphisms compared to other 41 samples that showed polymorphisms in terms of gaining new bands compared to the monomorphic group (Figure 1). Average gene diversity over loci for all samples was 0.0294 with standard deviation 0.0155. Twenty two out of 41 samples had identical fingerprints, while other 19 samples were more diverse, with 78 to 93.8 % genetic similarity compared with the main identical group. Table 2: SSR allele length (alleles in bp) at 6 microsatellite loci performed on all 113 Refosk samples, fluorescently labelled M13 primer labelled with different dyes for different SSR markers and multiplexing combinations after PCR. Combinations analysed in the same electrophoresis run are marked with the same letters (A and B). SSR marker Dye of M13 primer Electrophoresis multiplex Genotype VVMD5 NED A 241:243 VVMD7 6-FAM A 262:264 VVMD27 VIC B 208:208 VVMD32 VIC A 266:289 VrZAG62 6-FAM B 210:212 VrZAG79 PET A 256:268 Table 3: The number of total scorable and polymorphic AFLP markers generated by the selected primer combinations, where "P" and "M" are PstI and Msel primers, respectively. Combinations analysed in the same electrophoresis run are marked with the same letters (A, B and C). Primer combination Total bands Polymorphic markers Polymorphism (%) Electrophoresis multiplex 6-FAM-P-AGA/M-CTT 43 1 2.3 A VIC-P-AAC/M-CTG 29 2 6.9 A 6-FAM-P-AGA/M-CAT 23 3 13.0 B VIC-P-AAC/M-AG 34 5 14.7 B PET-P-ATA/M-CAA 16 3 18.8 B 6-FAM-P-AGA/M-AG 22 1 4.5 C VIC-P-AAC/M-CTC 16 1 6.25 C PET-P-ATA/M-CTT 25 / / A Total 208 16 7.7 Figure 1: UPGMA-derived dendrogram of genetic similarity based on the SM coefficient among the 41 Refosk samples 3.2 Ampelographic characterization Twelve Refosk biotypes grown in the collection vineyard were selected on the basis of AFLP analysis, 4 from the monomorphic group and 8 from the polymorphic group, and were evaluated for 22 OIV descriptors (Table 4). Traits, showing variability among Refosk biotypes, were: bunch density (OIV 204) varied from loose to medium; observed length of peduncle of primary bunch (OIV 206) varied from 46.2 to 72.5 mm; peduncle was lignified up to about the middle or more than the middle (OIV 207); the number of wings of the primary bunch (OIV 209) varied from 1 to 5; berry shapes (OIV 223) were either globose or ellipsoid; mean weight of a single bunch (OIV 502) varied from 371 to 696 g; mean weight of 30 typical berries of 5 bunches (OIV 503) varied from 2.77 to 4.30 g; observed anthocyanin coloration of flesh (OIV 231) varied from none to medium; and must traits: sugar (OIV 505) and total acid content expressed as tartaric acid equivalents (OIV 506), varied from 18.2 to 23.3 % and from 10 to 11.8 g l-respectively. However, Refosk biotypes did not show any similar distribution with regards to AFLP monomorphic and polymorphic group, since Refosk biotypes 31, 39, 40 and 43, presenting the monomorphic group, were distributed among different clusters (Figure 2). Refosk_il Refosk_10 Refosk_26 Refosk_43 Refosk_25 -i_M Refosk lS -I - Refosk_22--- Refosk 39- Refosk_40-1 - Refosk_44-' Refosk_45- Refosk_2J- I 1 1 I 1 1 I 1 1 I 1 1 I 1 1 I 0.45 0.60 0.75 0.90 1.05 1.20 DKT Coefficient Figure 2: Dendrogram based on ampelographic characterization of the 12 Refosk biotypes from the collection vineyard in Komen (Kras winegrowing district, Slovenia), constructed with UPGMA method and distance (DIST) coefficient Table 4: Scoring results of 22 OIV codes of the 12 Refosk biotypes from collection vineyard in Komen (Kras winegrowing district, Slovenia). Observations were performed on 10 shoots on 3 to 5 vines per biotype. OIV code Characteristic Refosk biotypes 31 39 40 43 10 22 23 18 25 26 44 45 202 Bunch length with peduncle 5 5 5 5 5 5 5 5 5 5 5 5 excluded 203 Bunch width 5 5 5 5 5 5 5 5 5 5 5 5 204 Bunch density 5 3 3 5 5 5 5 5 5 5 3 5 206 Length of peduncle of 3 3 3 5 5 3 3 5 5 3 3 3 primary bunch 207 Lignification of peduncle 5 5 5 7 7 5 5 5 5 7 5 5 208 Bunch shape 2 2 2 2 2 2 2 2 2 2 2 2 209 Number of wings of the 3 2 3 4 2 2 4 2 2 3 3 4 primary bunch 220 Berry length 5 5 5 5 5 5 5 5 5 5 5 5 221 Berry width 5 5 5 5 5 5 5 5 5 5 5 5 222 Uniformity of berry size 2 2 2 2 2 2 2 2 2 2 2 2 223 Berry shape 2 3 3 2 3 2 3 2 3 2 3 2 225 Berry skin colour 6 6 6 6 6 6 6 6 6 6 6 6 226 Uniformity of berry skin 6 6 6 6 6 6 6 6 6 6 6 6 colour 231 Intensity of the anthocyanin 3 1 1 1 3 1 5 1 3 3 1 3 coloration of flesh 233 Must yield 5 5 5 5 5 5 5 5 5 5 5 5 238 Length of pedicel 3 3 3 3 3 3 3 3 3 3 3 3 240 Ease of detachment from 3 3 3 3 3 3 3 3 3 3 3 3 pedicel 502 Weight of a single bunch 5 3 5 5 5 5 3 5 5 7 5 3 503 Single berry weight 3 3 3 3 3 5 3 3 3 5 5 3 505 Sugar content of must 7 7 5 7 7 7 9 7 7 7 5 5 506 Total acid content of must 5 5 5 7 5 7 5 7 7 5 7 7 508 Must specific pH 3 3 3 3 3 3 3 3 3 3 3 3 4 DISCUSSION The genetic diversity of cultivar and the presence of several biotypes are of great importance because of their adaptation to different climate conditions as this can contribute to typical characteristics of vine. In the present study, the cultivar identity was confirmed with SSR markers and genetic diversity of Refosk was assessed with AFLP molecular markers. The amplification of six SSR loci revealed the same allele patterns in all 113 accessions and confirmed the genetic identity of the cultivar. Kozjak et al. (2003) distinguished samples labelled with number 7 and 50 from other Refosk biotypes with microsatellite analysis, while all other analysed samples had the same microsatellite fingerprint in our research. The discrepancies that were observed between the Refosk samples 7 and 50 by Kozjak et al. (2003) and our results, were probably due to mistakes at planting or collecting stage. No other previous information is available on genetic diversity within cultivar Refosk grown in Slovenia. The Pstl-Msel primer combinations used reveal 16 reproducible polymorphisms out of 208 scorable markers and thus allowed to differentiate analysed samples in polymorphic and monomorphic group. Overall mean value of gene diversity was lower than published for example for Pinot Noir clones and similar as observed for Pinot gris clones (Blaich et al., 2007; Konradi et al., 2007). The dendrogram presented genetic variability within the polymorphic group (Figure 1). When analysing clonal diversity of grapevine cultivars in other studies, a wide range of obtained AFLP polymorphisms and power of discrimination have been reported. For example, Fanizza et al. (2003) did not manage to differentiate 4 clones of the table grapevine cultivar Italia, although 3880 markers had been produced with 49 primer combinations; Filippetti et al. (2005) discriminated only 3 polymorphic clones out of 26 using 9 primer combinations; Konradi et al. (2007) revealed 72 polymorphic markers of total 375 among 32 Pinot clones exhibiting up to 5 % dissimilarity, on the other hand Anhalt et al. (2011) obtained 135 polymorphic markers out of 305 with 10 primer combinations when studying 86 Riesling clones, but most clones showed none, one or two mutations over all primer combinations Discrimination of samples in monomorphic and polymorphic groups could indicate that Refosk grown in Slovenia originated from different, but genetically and morphologically very similar plant material. A possible explanation for this phenomenon is provided by Filippetti et al. (1999) who demonstrated that seedlings from a single self-pollinated vines were morphologically similar, but at the DNA level could be differentiated. The results show that genetically different plant material is equally represented in production vineyards, indicating that vine nurseries propagate genetically mixed material. Due to low detected variability (only 10 different AFLP fingerprints) it is necessary to continue with the analysis to determine as much genetic variability as possible for efficient and proper conservation. Results of ampelographic description showed that Refosk biotypes differ in several traits. However, correlation between ampelographic characters and either monomorphic or polymorphic group according to AFLP results were not observed. Since traits including berry weight, number of wings of the primary bunch, lignification of the peduncle, and the must traits of sugar and total acid content could vary from year to year, due to different crop level and other biotic and abiotic factors, multiple years of ampelographic observations should be considering for comparison. 5 CONCLUSION Genetic diversity is needed for efficient adaptation of cultivars to environmental changes and to be more resilient to environmental shocks. 'Refosk' is cultivated across a relatively large region but AFLP genetic analysis showed that very little genetic diversity exists within cultivar, which subsequently presents higher production risks. In recent years Refosk was recognized as very susceptible to Grapevine yellows and few vineyards were already grubbed-up. When selecting morphological appropriate grapevine, genetic analysis should complement ampelography what allows to prevent diminishing of genetic variability. Using AFLP markers we were able to detect greater variability compared to microsatellite molecular markers, where no polymorphisms were discovered and thus provided valuable information for further selection and conservation processes. ó ACKNOWLEDGMENTS The authors thank the Slovenian Research Agency for financial support to MH, contract No. 1000-08310189. 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In: Vinogradi in vina za tretje tisočletje? Nova Gorica, Grafika Soča: 359-367 COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.07 Agrovoc descriptors: vitis vinifera, grapevines, land varieties, plant diseases, viroses, grafting, disease transmission, stress Agris category code: h20, f02 Autografted vines of cultivar 'Refošk' (Vitis vinifera L.) reveal symptoms of the rugose wood disease Matjaž HLADNIK1, Dunja BANDELJ2, Irma VUK3 Received Janury 23, 2014; accepted March 10, 2014. Delo je prispelo 23. januarja 2014, sprejeto 10. marec 2014. ABSTRACT Rugose wood disease complex is one of the most important graft-transmissible grapevine diseases and it is considered to be a viral disease. With the aim to obtain more information about appearance of rugose wood disease observed on cultivar 'Refosk', 'Refosk' vines from collection vineyard in Komen were used for green grafting on SO4 rootstock and autografts for control were made as well. Rugose wood symptoms were observed on grafts of two 'Refosk' biotypes, which confirmed graft transmissibility. Appearance of rugose wood symptoms on autografts excluded the impact of incompatibility in rugose wood disease, but at the same time it could be proposed that stress caused by grafting has an important role. Key words: rugose wood complex disease, green grafting, graft indexing IZVLEČEK POJAV ZNAMENJ RAZBRAZDANJA LESA NA CEPLJENKAH S SPOJENIMI LASTNIMI DELI TRSOV SORTE Vitis vinifera'Refošk' Kompleks bolezni razbrazdanja lesa je ena od najpomembnejših bolezni vinske trte, ki se prenaša s cepilnim materialom in za katero velja, da naj bi jo povzročali virusi. Da bi pridobili več podatkov o razvoju znamenj bolezni razbrazdanja lesa smo cepiče sorte 'Refošk' s kolekcijskega vinograda iz Komna s tehniko cepljenja zeleno na zeleno cepili na podlago SO4. Za kontrolo smo mladike prerezali in jih ponovno spojili. S pojavom znamenj razbrazdanja lesa na cepljenkah pri dveh biotipih sorte 'Refošk' smo potrdili ugotovitev, da se bolezen prenaša s cepljenjem, medtem ko lahko zaradi pojava znamenj na cepljenkah s spojenimi lastnimi deli mladik sklepamo, da na razvoj bolezni ne vpliva inkompatibilnost cepiča in podlage, temveč bi lahko imel pomembno vlogo stres, ki ga izzove cepljenje. Ključne besede: kompleks bolezni razbrazdanja lesa, zeleno cepljenje, indeksiranje 1 INTRODUCTION Rugose wood disease complex is one of the most important graft-transmissible grapevine diseases, however despite numerous studies (Credi, 1997b; Meng et al., 1999; Nakaune et al., 2008) its etiology is still largely unknown. The disease is spread worldwide (Martelli, 1993) and has been found on many grapevine cultivars V. vinifera and 1 University of Primorska, Science and Research Centre, Garibaldijeva 1, SI - 6000 Koper, Slovenia, matjaz.hladnik@zrs.upr.si; University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI - 6000 Koper, Slovenia, matjaz.hladnik@upr.si 2 Ph.D., University of Primorska, Science and Research Centre, Garibaldijeva 1, SI - 6000 Koper, Slovenia, dunja.bandelj@zrs.upr.si; University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI - 6000 Koper, Slovenia, dunja.bandelj@upr. si 3 Ph.D., University of Primorska, Science and Research Centre, Garibaldijeva 1, SI - 6000 Koper, Slovenia, irma.vuk@zrs.upr.si; University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, SI - 6000 Koper, Slovenia, irma.vuk@upr. si on other species of the genus Vitis (Bonfiglioli et al., 1998; Credi, 1997a; Nakaune et al., 2008). Rugose wood complex is a disease complex usually characterized by modifications of the woody cylinder that is typically marked by pits and/or grooves (Martelli, 1993). The ridges of the cortex consist of hyperthrophied rays extending from the bark into the functional xylem (Martelli, 1993). Anatomical abnormalities originate from the altered behavior of the vascular cambium (Martelli, 1993). The symptoms can appear either on scion, rootstock or on both (Martelli, 1993). The rugose wood complex of diseases are essentially diseases of grafted vines, since appearance of symptoms for non-grafted vines is unusual (Bonfiglioli et al., 1998). Rugose wood disease is considered to be a viral disease, although this assumption is based only on its graft transmissibility and in part on its vector transmissibility (Martelli, 1993). Rupestris stem pitting, the most widespread disease of the rugose wood complex, is consistently associated with Grapevine Rupestris stem pitting associated virus (GRSPaV) (Meng et al., 1999; Nakaune et al., 2008). On the other hand GRSPaV was also detected in asymptomatic vines (Meng et al., 2005; Nakaune et al., 2008). Recently GRSPaV was observed to be closely associated with vein necrosis symptoms (Bouyahia et al., 2005). The exact etiological role of GRSPaV in different diseases remains unknown. Grapevine virus A (GVA) and Grapevine virus B (GVB) are thought to be involved in Kober stem grooving and Corky bark, respectively (Bonavia et al., 1996; Garau et al., 1994) and they are transmitted by mealybug (Phenacoccus aceris) (Le Maguet et al., 2012). However, due to the complexity of the disease, a general causal agent has not been identified yet. Symptoms similar to those of rugose wood were observed and recorded in Slovenia as well. 'Refosk' vines from the collection vineyard in Komen, Slovenia, that have shown diverse rugose wood symptoms, like swelling above the grafted site, deep grooves, pitting, thicker scion vines; were already tested by ELISA, ISEM, Western blot and RT-PCR for the presence of the rugose wood disease related viruses (Petrovic et al., 2003; Tomazic et al., 2005a; Tomazic et al., 2005b; Tomazic et al., 2008) but none of the tested viruses could be correlated with rugose wood disease on the cultivar 'Refosk'. According to EPPO certification scheme for the production of healthy plants for planting, graft indexing is still a compulsory step, since rugose wood disease can be identified solely on woody differential hosts; in case of Grapevine virus A and Grapevine virus B molecular testing is recommended (EPPO, 2008). However, it was already shown that biological indexing tests may not be completely reliable, because results can be affected by various elements, such as a possible synergistic effect of various causal pathogenic agents and possible latency of wood disorders (Credi, 1997a). Due to extreme complexity of rugose wood disease complex much more research is needed to enable the use of modern technologies to clarify the etiology of this disease. We believe the work we are presenting in the present paper will contribute to enhanced understanding of the etiology of rugose wood disease complex. The first objective of this study was to find out if rugose wood symptoms are expressed in green grafts and to determine when they appear after green grafting. Indexing tests are most frequently performed with the dormant chip budding method, which may take two to several years before rugose wood symptoms become visible (Credi, 1997b; Martelli, 1993). The green grafting method has several advantages in comparison with woody grafts: for several of the graft-transmitted diseases, symptoms develop in a matter of weeks instead of months; less space is required for green-grafted indicators and it can be done throughout the growing season (Walter et al., 1990). Green graft indexing is used in Slovenia in grapevine sanitary selection as well. However, Walter et al. (1990) didn't manage to detect stem pitting when using green grafting on the indicators Kober 5BB and V. rupestris after 3 months. Besides that, when they compared results of green grafting and dormant budding, they discovered more positive indicators of corky bark on grafts with the dormant budding technique. The second objective of this work was to test if rugose wood symptoms are expressed on autografted 'Refosk' vines to determine if the appearance of rugose wood symptoms could be due to a physiological response of the plant to grafting stress, rather than or in addition to the transmission of a virus or virus-like agents. 2 MATERIAL AND METHODS 2.1 Plant material Plant material for indexing was obtained from the collection vineyard in Komen (N45 48.917 E13 44.692), established in 1989 when old 'Refosk' vines from the field were propagated by grafting on SO4 (V. berlandieri x V. riparia) and planted in blocks of3 to 35 vines per biotype. Vines are trained as double guyot and cultivated according to the instructions of integrated pest management. Fifteen percent of vines from collection vineyard have shown rugose wood symptoms on rootstocks and/or scions, while 18 % of plants with rugose wood symptoms died in 10 years after planting (Tomazic et al., 2005b). The virus status of 'Refosk' vines used in this study was already reported (Petrovic et al., 2003; Tomazic et al., 2005a; Tomazic et al., 2005b; Tomazic, 2002; Tomazic et al., 2008). Results were summarized in Table 1. However, virus status could be changed in case of transmission. 'Refosk' vines used for indexing are listed in Table 1. Asa putative source of rugose wood, vines labeled as 'Refosk' 20, 38, 48 and 51 were used. From vineyard observation 'Refosk' biotypes 38 and 48 develop symptoms on itself, on the other hand 'Refosk' biotypes 20 and 51 induce apparent rugose wood symptoms on SO4 rootstock while scion parts maintain a healthy appearance (Table 3). Regarding the differences in symptoms expression, there could be two different types of rugose wood. 'Refosk' biotypes 43 and 61 never showed symptoms in the vineyard and were used as controls. In June 2009, shoots of 'Refosk' vines were collected in the morning and immediately transported to the Vine Selection Center in Vrhpolje, where green grafting on SO4 rootstock and autografting were carried out. 2.2 Grafting experiment For the rootstock, shoots of 'Refosk' vines and SO4 were cut on two buds (right below lower bud and in the middle of internode above the next bud), while the scion cuttings had one bud. Leaves on upper rootstock node and on the scion were trimmed to about half of their original size before grafting. The method used for indexing was machine splice grafting. The assembled graft was wrapped with white first aid tape. Rootstocks were treated with naphthalene acetic acid (NAA) (Germon Bewurzelungspuder H per talee legnose, Conc. E. Gerlach GmbH, Germany). Grafts were planted in vermiculite and kept for 34 days in humid chamber on 28 °C and 85 % relative humidity. After that period rooted grafts were transplanted into universal substratum in flowerpots and transferred to the green house to the controlled water table for constant irrigation where they were maintained till September 2012. The grafts were visually examined monthly for the presence of the rugose wood symptoms on the scion and rootstock parts in 2009 and 2010, while the last two years only at the end of active vegetation at the beginning of September. At final examination all grafts were autoclaved and bark was peeled away. Table 1. Virus status of 'Refošk' vines from collection vineyard in Komen, Slovenia, as reported in previous studies. Virus / 'Refošk' vine 20 (IVd/110e) 38 (VIII/44) 43 (VIII/113) 48 (IX/43) 51 (IX/69) 61 (XII/68) ArMVa - - - - - - GFkVa + - - - - - GFLVa - - - - - - GLRaV-1a - - - - + - GLRaV-2a - - - - ? + GLRaV-3a - - - - - - GLRaV-6a + + - - - - GLRaV-7a - - - - ? - GVAa - - - - - - GVBa - - - - - - RSPaV-^ d +a,b,d/ c +a,b,d,c +a,b,d/ c +a,b,d/ c +a,b,d/ c +a,b,d / c a ELISA testing, PCR testing, cISEM testing, Western blot testing, Raw in collection vineyard, e Vine number in raw ? unable to confirm infection since threshold was difficult to determine due to higher background in ELISA testing 3 RESULTS AND DISCUSSION A major part of research on rugose wood disease on 'Refosk' was done in the field of virology, but no causal agent was identified that could be used in sanitation for rugose wood affected vines (Tomazic et al., 2005a; Tomazic et al., 2005b; Tomazic et al., 2008). In the collection vineyard in Komen it is observationally evident that vines, propagated by grafting from the same mother vines are showing similar rugose wood symptoms, which indicates that rugose wood is transmitted with grafting. This is consistent with rugose wood complex in general (Martelli, 1993). Indexing for rugose wood associated diseases is usually carried out using standard indicator vines, i.e. V. rupestris St. George, LN 33 (Coudero 1613 x V. berlandieri) and Kober 5BB (V. berlandieri x V. riparia). In our study, grafting on rootstock SO4 was performed, since it is frequently used rootstock in Kras and Slovenska Istra winegrowing districts, it develops rugose wood symptoms and it was used in the collection vineyard in Komen. 3.1 Survival rate of grafted material The results of autografting and grafting 'Refosk' on SO4 are summarized in Table 2. At final monitoring from 27.3 % to 80 % of 'Refosk' autografts were still growing. The highest mortality rate at last monitoring was observed in 'Refosk' 43, 51 and 61, reaching 60 % to 72.7 %. 'Refosk' 43 and 61 biotypes are symptomless in the vineyard. On the other hand only 30% of 'Refosk' 38 and 20 % of 'Refosk' 48 autografts died, while both biotypes show the most severe rugose wood symptoms in the vineyard. Considering the results of grafting 'Refosk' on SO4 from 25 % to 40 % of grafts were viable at final monitoring, except the 'Refosk' 51 grafts with survival rate of 60 %. The survival rate of grafted material could not be explained by different grafting treats, especially due to low number of survived 'Refosk' 43 and 61 autografts, higher number of survived 'Refosk' 38 and 48 autografts and very variable survival rate of 'Refosk' 20 and 51 autografts and grafts; therefore it could be assigned to random effect. In the case that grafts, putatively affected with rugose wood, show lower survival rate, they could be eliminated in early stages of planting material production in vine nursery. Table 2: Graft success and number of 'Refosk' autografts and grafts on SO4 rootstock at final examination. 'Refosk' vines used for green grafting were from collection vineyard in Komen, Slovenia. Autografted 'Refosk' vines 'Refosk' grafted on SO4 'Refosk' vine Total Successfully 3rd September Total Successfully 3rd September number of rooted 2012 number rooted grafts at 2012 autografts autografts at of the time of (12th June the time of grafts transplanting 2009) transplanting (12th (17th August (17 August June 2009) 2009) 2009) n % n % n % n % 'Refosk' 20 IV/110 11 10 90,9 7 63,6 12 11 91,7 3 25,0 'Refosk' 38 VIII/44 10 9 90,0 7 70,0 10 7 70,0 3 30,0 'Refosk' 43 VIII/113 10 9 90,0 4 40,0 10 8 80,0 4 40,0 'Refosk' 48 IX/43 10 10 100,0 8 80,0 8 7 87,5 3 37,5 'Refosk' 51 IX/69 11 8 72,7 3 27,3 10 9 90,0 6 60,0 'Refosk' 61 XII/68 10 9 90,0 3 30,0 10 8 80,0 3 30,0 Total / Average (%) 62 55 88,9 32 51,8 60 50 83,3 22 36,7 SO4 10 7 70,0 4 40,0 10 8 80,0 3 30,0 Total / Average (%) 72 62 86,1 36 50,0 10 8 80,0 4 40,0 3.2 Expression of rugose wood symptoms on 'Refosk' 38 and 'Refosk' 48 autografts and grafts on SO4 rootstock The first typical symptoms of rugose wood were observed on 'Refosk' 38 and 48 vines at last examination, i.e. 39 months after grafting. Fine grooving was observed on the scion part of 'Refosk' 38 and 48 vines grafted on SO4 rootstock, while no evident symptoms were seen on SO4 rootstock (Table 3 and Figure 1). When 'Refosk' 38 and 48 were autografted, the symptoms of rugose wood were observed on the scion part of 'Refosk' 38 autografts, while on 'Refosk' 48 autografts symptoms were observed on the scion and rootstock (Table 3 and Figure 1). According to the literature this is the first report of observed rugose wood symptoms on autografts. Appearance of rugose wood symptoms on grafts and autografts of 'Refosk' 38 and 'Refosk' 48 confirmed that rugose wood is transmitted by grafting. Since the symptoms were observed on autografts then the effect of incompatibility in the development of rugose wood disease could be eliminated. Possible reasons could therefore be reaction of plant as response to stress and wound healing or synergistic effect of stress and pathogen agents. The low number of 'Refosk' 38 and 'Refosk' 48 grafts and autografts with symptoms could be explained in two ways: a) in the case that pathogen agents causing the development of rugose wood are viruses, then it is possible that they were not already transmitted to green canes. It is known that viruses are unevenly distributed throughout the canopy (Fiore et al., 2009; Rowhani and Uyemoto, 1997); b) the second reason is possible latency of symptoms as reported by (Credi (1997a); Martelli, 1993). It should be also taken into consideration that symptoms could become visible if plants would be left in green house for additional one year or if different growing conditions were applied. Although green-grafting was used, more than three years were needed in order to symptoms of rugose wood became visible what is similar to graft indexing with chip budding method (Credi, 1997b; Martelli, 1993). Table 3: The results of graft indexing and the results of vineyard monitoring for rugose wood symptoms. 'Refošk' vine Symptoms observed in collection vineyard 'Refošk' SO4 (scion) (rootstock) Graft indexing results Appearance of rugose Appearance of rugose wood symptoms on wood symptoms on autografts 'Refosk'/SO4 grafts 'Refošk' 20 IV/110 - + -/- -/- 'Refošk' 38 VIII/44 + - +/- (2/7) +/- (1/3) 'Refošk' 43 VIII/113 - - -/- -/- 'Refošk' 48 IX/43 + - +/+ (2/8) +/- (1/3) 'Refošk' 51 IX/69 - + -/- -/- 'Refošk' 61 XII/68 - - -/- -/- - minus or plus before slash indicates absence or presence of rugose wood symptoms on scion, while sign after slash indicates absence or presence of symptoms on rootstock - numbers in parenthesis indicate the number of autografts or grafts, out of total number of viable vines observed at last monitoring A If St • s 1 j. i Figure 1: 'Refosk' 48 autograft showing fine grooving on rootstock and on scion part (A); 'Refosk' 38 grafted on SO4 rootstock (B). Symptoms of rugose wood are visible on scion part. 3.3 Symptomless 'Refosk' 20 and 'Refosk' 51 autografts and grafts on SO4 rootstock The rugose wood symptoms were not detected on 'Refosk' 20 and 51 grafs and autografts (Table 3). Therefore, we were not able to confirm transmittance of rugose wood on SO4 with 'Refosk' 20 and 'Refosk' 51. We proposed that the source of rugose wood should be 'Refosk' vines since infection of rootstock in collection vineyard could be eliminated because rugose wood is present only in specific biotypes and not randomly across vineyard as would be expected in case of the infected rootstock. The possibility of symptomless SO4 could be that a different SO4 clone was used for grafting than the one used in the collection vineyard. Differential sensitivity of clones was observed for example in 'Syrah' clones for Syrah decline, which is also a disease causing degeneration of the woody cylinder (Renault-Spilmont et al., 2007). As hypothesized by Credi (1997b) development of rugose wood is dependent also on abiotic factors, as in the case of leafroll where the choice of indicator is based on climatic conditions (EPPO, 2008). For optimum symptoms expression in green grafting effects of temperature and light conditions could be optimized (Walter et al., 1990). This could also improve the development of symptoms in 'Refosk' 38 and 'Refosk' 48 grafts and autografts. However, it is possible, that symptoms would become expressed in the green grafts after one additional year. Walter et al. (1990) did not manage to detect stem pitting disease symptoms on indicators Kober 5BB and V. rupestris a few months after green grafting and concluded that perhaps a longer incubation period is required for classic symptoms to develop. 4 CONCLUSIONS With this experiment we were able to confirm graft-transmissibility of rugose wood. However, graft success of grafts with vines showing rugose wood symptoms in the collection vineyard was not affected, which means that they are not excluded in the process of planting material production. The appearance of rugose wood symptoms on autografts supports the statement that effect of incompatibility is not involved in rugose wood. On the other hand stress caused by grafting could have notably impact on the development of symptoms what makes rugose wood even more complex. Proper growing conditions of graft indexing trials should, therefore, be defined in order to maximize the expression of rugose wood symptoms. 5 ACKNOWLEDGEMENTS The authors thank the Slovenian Research Agency for financial support to MH, contract No. 1000-08310189. Many thanks to Andreja Skvarc, head of the Vine Selection Centre Vrhpolje for kindly offering a place in greenhouse and to Matej Vrcon for their technical help and for growing the greenhouse plants. The authors thank dr. 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COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.08 Agrovoc descriptors: organic fertilizers, inorganic fertilizers, growth rate, essential oils, yields, yield increases, fertilizer application, climatic factors, edaphic factors, growth factors Agris category code: f04 Influence of chemical and organic fertilizer on growth, yield and essential oil of dragonhead (Dracocephalum moldavica L.) plant Mohsen JANMOHAMMADI1*, Zahed SUFI-MAHMOUDI1, Amin AHADNEZHAD1, Saeed YOUSEFZADEH2, Naser SABAGHNIA1 Received June 07, 2013; accepted Janury 17, 2014. Delo je prispelo 07. junija 2013, sprejeto 17. januarja 2014. ABSTRACT IZVLEČEK Two field experiments were carried out to study the response of Dracocephalum moldavica L. to NPK fertilizer and different application techniques of MOG organic fertilizer in two regions of Iran (Piranshahr with cold Mediterranean climate and clay loam soil, Maragheh with cool sub-humid temperate climate and sandy loam soil ). MOG is bio-organic fertilizer with plant origin and contains different natural enzymes and amino acids. In current study following treatments have been applied: NPK (a complete NPK 20-2020, 90 kg fertilizer ha-1); MOGj (soil application of MOG organic fertilizer at sowing stage); MOG2 (foliar application of MOG organic fertilizer at early stage of flowering); MOG3 (soil application of MOG organic fertilizer at sowing and at 5 to 6 leaf stage); MOG4 (soil application of MOG organic fertilizer at sowing and at 5 to 6 leaf stage with foliar application at early stage of flowering). Results indicated that all MOG treatments overcome the chemical fertilizers in both locations. However, plants grown in Piranshahr were more responsive to MOG fertilizer treatments than those grown in Mragheh. Overall, it could be concluded that utilization of MOG fertilizer as both soil and foliar application (MOG4) may increase content and yield of essential oil, which could be suggested as a suitable alternative for chemical fertilizers. Key words: dry herbage, essential oil yield, flower, Moldavian balm, vegetative growth VPLIV MINERALNIH IN ORGANSKIH GNOJIL NA RAST, PRIDELEK IN VSEBNOST ETERIČNIH OLJ KAČ JEGLAVKE (Dracocephalum moldavica L.) V dveh poljskih poskusih je bil preučevan odziv kačjeglavke (Dracocephalum moldavica L.) na gnojenje z NPK in različne tehnike uporabe MOG organskih gnojil na dveh območjih Irana (Piranshahr, s hladnim mediteranskim podnebjem in glineno-ilovnatimi tlemi, Maragheh s hladnim, semi humidnim zmernim podnebjem in peščeno-ilovnatimi tlemi). MOG je biološko gnojilo rastlinskega izvora, ki vsebuje številne naravne encime in amino kisline. V tej raziskavi so bili uporabljeni naslednji tretmani: NPK (NPK 20-20-20, 90 kg gnojila ha-1); MOG! (talna aplikacija MOG organskega gnojila ob setvi); MOG2 (foliarna aplikacija MOG organskega gnojilav zgodnji fazi cvetenja); MOG3 (talna aplikacija MOG organskega gnojila ob setvi in v fazi 5 do 6 lista); MOG4 (talna aplikacija MOG organskega gnojila ob setvi in v fazi 5 do 6 lista s foliarno aplikacijo ob začetku cvetenja). Rezultati so pokazali,da so dala vsa obravnavanja z MOG boljše rezultate kot mineralna gnojila na obeh lokacijah. Rastline z območja Piranshahr so bile bolj odzivne na MOG gnojenje kot tiste z območja Maragheh. Zaključimo lahko, da uporaba MOG gnojil, tako talna kot foliarna lahko poveča vsebnost in pridelek eteričnih olj in bi se lahko priporočila kot primerna alternativa gnojenju z mineralnimi gnojili. Ključne besede: suha zel, pridelek eteričnih olj, cvet, kačjeglavka, vegetativna rast Department of Agronomy and Plant Breeding, Agriculture College, University of Maragheh, East Azerbaijan, Iran; * Author of correspondence; Email: mjanmohammadi@maragheh.ac.ir Department of Agriculture, Payame Noor University, Po Box: 19395-3697 Tehran, Iran 2 1 INTRODUCTION Dragonhead or Moldavian balm (Dracocephalum moldavica) is an annual herbaceous aromatic plant belonging to family of Lamiaceae (El-Baky and El-Baroty, 2007). It is native to central Asia and to eastern and central Europe (Griffiths, 1994). Dragonhead is commonly consumed as a food-related product and as a herbal preparation because of its reputed medicinal properties. In some parts of Iran, distilled aqueous extracts from D. moldavica is used as a beverage (Dmitruk & Weryszko-Chmielewska, 2010; Rechinger, 1986). The oil content and its composition showed high variation due to the plant origin (Hussein et. al, 2006). In Iran, it distributed in the north and northwestern parts of the country, especially in the western parts of Azerbaijan province, and in the Albourz Mountains (Dastmalchi et al., 2007; Dmitruk & Weryszko-Chmielewska, 2010). The seeds of Moldavian Balm have astringent, carminative and tonic properties. They are used as a demulcent in the treatment of fevers (Dastmalchi et al., 2007). Furthermore, the plant is astringent, tonic and vulnerary (Rechinger, 1986) and has antitumor properties (Chachoyan & Oganesyan, 1996). Plant nutrition is one of the most important factors affecting quantity and quality of secondary metabolites in plants. In order to meet the ever-increasing demand of medicinal plants need to be identified the best fertilizer application strategies. It is apparent that essential oil content enhance with increasing plant age to reach the maximum values at post flowering stage. The yield of plant fresh herb, the essential oil content and its composition can be influenced by growth stages, ecological and climatic conditions. Several attempts have been made to increase yield potential of medicinal plants (Das et al., 2007; Sharma and Kumar 2011), but they are concerned with use of inorganic fertilizers which may affect biological aspect of soil. Therefore, the use of organics and biofertilizers is gaining more importance for getting higher yield and quality. Bio-fertilizer as an organic agro-input can promotes plant growth by increasing the supply or availability of macro and micro nutrients through the natural processes (Vessey 2003). Furthermore, bio-fertilizers can be expected to reduce the use of chemical fertilizers. One of the recently introduced organic fertilizer is MOG manufactured by using of some fruits juice and crop residues and contains 18 types enzymes (like as Alkaline Protease, Glucamylase, Lipase, Lipoxigenas, Nitrogenase...), natural form of micro and macro nutrients and vegetable based vitamins. However, the information on the role of MOG organic fertilizer on morphophysiological traits and chemical contents in Dragonhead is little. Hence, there is an urgent need to study the influence of biofertilizer on biochemical, quality and yield components in Dragonhead to boost the productivity potential. The present investigation was performed to study the effect of MOG organic fertilizer and chemical fertilizers on growth and productivity in Dracocephalum moldavica in two regions in northwest Iran. 2 MATERIALS AND METHODS The experiments were conducted at two different locations. The first was agricultural research stations of Piranshahr, West Azarbayejan in the north-west of Iran (36° 40' N, 45° 08' E; 1840 m) with cold Mediterranean climate and a long-term mean air temperature of 17.8°C for the April until August period. In Piranshahr summers are almost dry but rest of year could be considered as wet seasons and soil texture of field was clay loam. Second location was Research farm of University of Maragheh, East Azarbayejan in the north-west of Iran (37° 24' N, 46° 16' E; 1477 m). Maragheh has cool sub-humid temperate climate with relative warm summers and the length of dry season is about 75 days. The soil texture of the field was sandy loam. Meteorological data during the crop growth period at both sites are presented in Table 1. Influence of chemical and organic fertilizer ... dragonhead (Dracocephalum moldavica) plant Table 1. Monthly temperature and precipitation during the growing season in 2012. Month Average temperature (°C) - Total precipitation (mm) Minimum Maximum Mean Piranshahr Maragheh Piranshahr Maragheh Piranshahr Maragheh Piranshahr Maragheh April 10.5 5.6 19.1 21.6 14.8 13.6 95.5 40.5 May 14.7 10.9 23.7 25.3 19.2 18.1 34.1 16.4 Jun 16.7 13.9 29.5 32.7 23.1 23.3 7.2 5.0 July 18.7 3.20 32.7 33.6 26.7 26.5 1.3 0.0 Augest 22.9 2.21 33.3 34.1 28.1 27.2 0.0 1.4 For both locations, composite soil samples were collected two weeks before planting, at a depth of 0-30 cm. The soil was air-dried and crushed before its pH, electrical conductivity (EC), and saturation percentage were evaluated. Then total organic carbon (using the Walkley and Black method, which involves sulphuric acid), total nitrogen (using the Kjeldahl method), available phosphorus Table 2: Soil physical and chemical properties in two loc (using the Olsen procedure), available potassium after extraction with ammonium acetate and Total Neutralizing Value were determined following the method as described by Jackson (1973) and Tandon (1995) were measured. Details of the soil properties of the both two locations are shown in Table 2. Soil properties Values Piranshahr Maragheh Soil texture clay loam Sandy loam Total N (%) 0.103 0.058 Available K (mg kg-1) 462 342 Available P (mg kg-1) 38.6 5.67 Organic carbon 2.08 0.41 pH 6.85 7.54 EC (ds m-1) 0.93 1.96 Total Neutralizing Value (TNV)% 49.6 34 The soil characteristics were determined according to Tandon (1995). The experiment was performed in a randomized block design layout with three replications. Six fertilizer treatments were applied, consist on; Control= no application of fertilizers; NPK= a complete NPK 20-20-20, 90 kg fertilizer ha-1; MOG1= soil application at sowing stage; MOG2= foliar application when first flowers was observable; MOG3= soil application at sowing and at 5 to 6 leaf stage; MOG4= soil application at sowing and at 5 to 6 leaf stage with foliar application when first flowers was observable. MOG organic fertilizer was provided from Azarabadegan Company, (West Azarbaijan, Iran). In all MOG treatments, organic fertilizer were utilized after dilution to 5% (v/v). The physicochemical properties of MOG organic fertilizer are shown in Table 3. D. moldavica seeds were obtained from local market of Bonab, Iran. Table 3: Chemical characteristics of MOG organic fertilizer. pH Total organic carbon (%) Total N (%) K2O (%)_P (%) Fe (%)_Cu (%)_Enzymes (%) 6.1 25 4 4 1.06 0.42 0.16 13 Each experimental plot was 3 m long and 2 m wide with the spacing of 10 cm between the plants and 40 cm between the rows. There was a space of one meter between the plots and 2 meters between replications. Dragonhead seeds were directly sown by hand on 17 April 2012 in both locations. There was no incidence of pest or disease on dragonhead during the experiment. Weeding was done manually and the plots were irrigated weekly to 70% of field capacity. All necessary cultural practices and plant protection measures were followed uniformly for all the plots during the entire period of experimentation. Harvest time for all investigated traits except 1000-grain weight and harvest index was at 50% flowering. Fresh and dry weight plants were determined with digital weighing scales. The plants were cut at ground level and samples of plants were dried in the shade and for extracting essential oils were used distillation with water practice and Clevenger device (Yousefzadeh et al., 2013). About 100 g of each dried sample (aerial parts) was separated, triturated and steam-hydro distilled for 2.5 hours. The extraction of oils was carried out according to method of European Pharmacopoeia (1983). The oils were dried over anhydrous sodium sulphate and stored in sealed vials at 2 °C before analysis. Gas chromatography (GC) analysis was performed using a Thermo-UFM Ultra Fast gas chromatograph equipped with a DB-5 fused silica column (10 m x 0.1 mm i.d., film thickness 0.40 ^m). The oven temperature was held at 60 °C for 3 min, and then programmed to increase to 280 °C at a rate of 80 °C min"1. The temperatures of the injector and flame-ionisation detector were held at 285 °C. Helium was used as carrier gas with a linear velocity of 32 cm s-1. The oils were injected manually into the GC instrument without dilution. The percentages of compounds were calculated by using the area normalisation method, without consideration of response factors (Davazdahemami et al., 2008). Gas chromatography-mass spectroscopy (GC-MS) were carried out using a Varian 3400 GC-MS system equipped with a DB-5 fused silica column (30 m x 0.25 mm i.d., film thickness 0.25 ^m). Following injection, the oven temperature was increased from 50 to 240 °C at a rate of 4 °C min-1, the temperature of the transfer line was maintained at 260 °C, and the linear velocity of the helium carrier gas was maintained at 31.5 cm s-1, with a split ratio of 1:60, an ionisation energy of 70 eV, a scan time of 1 s, and a mass range of 40-300 amu. The components of the oils were identified by comparing their mass spectra with those held in a computer library or obtained using authentic compounds. The identities of the components were confirmed by comparing their retention indices, either with those of authentic compounds or with data published in the literature (Adams, 1995). The statistical analysis including analysis of variance and the Least Significant Differences (LSD) among the means (at the 5% probability levels) were performed Snedecor and Cochran (1990). 3 RESULT AND DISCUSSION Morphological traits Plant height significantly influenced by fertilizer treatments and location (Table 4). Plant height comparison between the fertilizer treatments showed that the maximum value is related to plants received organic MOG4 (90.92 cm), it was followed by organic MOG2 (82.43 cm) and minimum of that was recorded for control plants (75.71cm). Moreover, the comparison of plant height between two locations revealed that D. moldavica plants cultivated in Piranshahr were 25% taller than those grown in Maragheh. The findings of the current study are consistent with those of Mafakheri et al. (2012) who found that concurrent application of organic fertilizer (vermicompost) could significantly improve the height of dragonhead. Numbers of the secondary branches were not affected by fertilizer treatments or by locations. Fertilizer application significantly affected the number of flower per plant, so that the highest number of flower was recorded in plants which experienced the MOG2 and MOG4. Furthermore, the number of flowers produced per plant significantly was different between locations, since the number of flowers in plants grown in Piranshahr was 89% higher than those which grown in Maragheh. The effects of fertilizer treatments on the chlorophyll content are shown in Table 4. The study showed that, regardless of location and type of fertilizer, the chlorophyll content for the control plants was about 28% lower than plants that received fertilizer. Also results revealed that nutrient source could considerably affect chlorophyll content, since the highest amount observed for MOG4. These findings confirmed the earlier suggestion that N and Mg can be released by organic fertilizer and then incorporated to porphyrin rings of chlorophyll molecules (Amujoyegbe et al., 2007). Thus, it seems that the higher level of N and Mg could result in developed site of photosynthesis and enhanced plant growth. Fertilizer treatments had significant effects on the 1000-grain weight and harvest index at 5% probability level. In both locations, the lowest harvest index was recorded in control plants and those grown with chemical fertilizers. The highest 1000-grain weight was observed in plants that received organic MOG fertilizer as both soil and foliar application (Table 4). Obtained results agreed with those of Rahimzadeh et al. (2011) and Mafakheri et al. (2012), they reported that, organic and bio fertilizers are rich and slow release fertilizers which usage leads to stimulate and increase of both vegetative and reproductive growth. Khalid et al. (2006) reported that applying liquid compost improved vegetative growth and reproductive characters of sweet basil (Ocimum basilicum L.) plants. Dry herbage yield Result revealed that dry herbage yield of dragonhead plants grown in Piranshahr was significantly higher (41%) than Maragheh. In addition, significant differences observed in dry herbage yield among fertilizer treatments (Table 4). In both locations, the MOG4 treatment gave the highest dry herbage yield (7947 and 6127 kg ha-1 in Piranshahr and Maragheh, respectively). In addition, control plants produced the lowest dry herbage yields, with 3942 kg ha-1 in Piranshahr and 3206 kg ha-1 in Maragheh. Differences between locations can be attributed to soil and climatic conditions. It seems that environmental circumstances in Piranshahr were quite suitable for dragonhead plants. These results are in agreement with those obtained by Abdelaziz et al. (2007) on Rosmarinus officinalis and Rahimzadeh et al. (2011) on Dracocephalum moldavica. In this respect, it is possible that the favourable effect of organic fertilizer on dry herbage yield will be due to their ability to enhance the physiological, biochemical, and biological properties of the soil. Essential oil content The results showed that essential oil content affected by the location and fertilization treatments, and the interaction between both factors (Table 4). Mean comparison between fertilization treatments revealed that the highest essential oil content (0.77%) there is in plants grown in Piranshahr and received MOG organic fertilizer through both soil and leaves (MOG4). This trend was also observed in Maragheh with a slower rate (0.49%). Essential oil content of the plant grown in Piranshahr averagely was 36% higher than those grown in Maragheh. Increases in the percentage oil content following the application of bio and organic fertilizer were observed in medicinal pumpkin (Habibi et al., 2011), Rosmarinus officinalis L. (Abdelaziz et al., 2007), dragonhead (Mafakheri et al., 2012; Yousefzadeh et al., 2013). For optimal plant growth, nutrients must be available in adequate and reasonable quantities (Chen, 2006). Intensive agriculture that emphasize heavy chemical application is led to adverse environmental, ecological; and health consequences (Habibi et al., 2011). One of the promising options to reduce the use of chemical fertilizers could be utilization of bio and organic fertilizers. Soils of arid and semi-arid regions often have low organic matter and need organic amendments to recover their characteristics and consequently their productivity and natural fertility. Addition of organic matter, from different resources may through improving physical and chemical properties of soil can affects the growth and development of plant roots and shoots and accumulation of essential oils (Elashry et al., 2008). Our results showed that the main effects of fertilizer treatments and location on yields of essential oils were significant. For plants grown in both locations, the maximum yields of essential oil were recorded in MOG4 and MOG2 treatments. The evaluation of the yields of essential oils between locations showed that yields of plants grown in Piranshahr (19.62 kg ha-1) were 21% higher than those grown in Maragheh (16.27 kg haIn general, provide the required elements for growth increases the yield of essential oil in medicinal and aromatic plants by increasing photosynthesis, chlorophyll content, and Rubisco activity, biomass yield, plant growth, and leaf surface area (Ram et al., 2003; Sekeroglu and Ozguven, 2006; Sifola and Barbieri, 2006). Table 4: Effects of Fertilizer treatments on some traits of dragonhead plants in two locations. Fertilizer Number . f , , , , ,, Dry Essential Essential 1000- Plant of number chlorophyll . Harvest Location _.........., „ „ RWC herbage oil oil yield grain . , Treatments height secondary of flower content . index yield content weight (FT) branches Control 80.67c 12.83a 69.40lg 38.491 74.60abc 3942ef 0.464cde 11.02fg 1.830c 19.02c N.P.K 88.54bc 16.33a 124.67cde 43.42cde 68.74bc 5998bcd 0.436edfef 14.63ef 1.862cbc 19.78c TV U U MOG1 93.07ab 14.29a 175.92bc 46.66bc 71.26bc 6679aabbc 0.409ebf 13.36efg 1.820cc 21.30^ Piranshahr mog2 96.53* 15.26a 200.39ab 46.61"c 73.83abc 7312ab 0.664bb 24.76cbdc 1.873cc 20.7lebd mog3 91.53b 13.14a 156.5bcd 48.53b 81.55a 5946bcd 0.645b 20.64cd 1.867c 20.30bc mog4 101.62a 17.07a 260.7g3a 53.77e 75.06abc 7947aef 0.7713 33.46a 1.9833 22.89cb Control 66.50d 13.33a 37.26g 39.04ef 71.02bc 3206ef 0.422d 9.79g 1.787d 19.25c N.P.K 70.83d 14.40a 62.0lg 40.59cd 67.21c 3757e 0.401fg 11.74fg 1.853cbc 19.46c Maragheh MOG1 69.00d 16.30a 91.64efg 43.70def 69.06bc 4087e 0.445def 12.04fg 1.830c 20.93abc mog2 67.17d 14.67 108.43del 42.01b 70.02bc 4932cde 0.366gh 20.13d 1.820bc 20.70abc mog3 69.16d 13.33a 86.27efg 48.73ab 76.44ab 4602de 0.357ch 17.48de 1.824bc 20.86abc mog4 80.33c 15.07a 138.56bcd 54.62a 75.42abc 6127bc 0.494c 26.48b 1.907ab 23.12abc LSD 9.42 4.48 63.86 4.43 8.62 1776 0.041 4.33 0.093 2.78 L ** ns * ns ns * ** * ns ns FT ** ns ** ** * ** ** ** * * Lx FT ns ns ns ns ns ns ** ns ns ns Values are given as means of three replicates. Means within each column followed by the same letter are not statistically different at a = 0.05 by LSD test. Fertilizer treatments: MOG1: soil application at sowing stage, MOG2: foliar application when first flowers were observable, MOG3: soil application at sowing and at 5 to 6 leaf stage, MOG4: soil application at sowing and at 5 to 6 leaf stage with foliar application when first flowers were observable. *Indicate significance at P level of 0.05. **Indicate significance at P level of 0.01. Composition of essential oils The composition of the essential oil with different treatments in both locations was studied (Table 5). Both GC and GC-MS analyses revealed that the major constituents of the oil that was extracted from all six fertilizer treatments in both locations were geraniol, geranial, and geranyl acetate (Tables 5). 3 mentioned compound represented 73.82-91.25% of total detected constituents with different treatments. The unknown compounds representing 0.82-19.53% of total detected constituents. Other reserchers have also reported that the major constituents of essential oils extracted from dragonhead plants are geraniol, geranial, and geranyl acetate (Davazdahemami et al., 2008; Yousefzadeh et al., 2013). However, some investigators have reported inconsistent results, which show that either citral (Nikitina et al., 2008) or linalool (Hussein et al., 2006) are the major constituents in oil from dragonhead plants. It appears that a range of contemplations, including climatic condition, geographic origin, ecological factors, genetic differences, and agricultural practices, could affect the composition of essential oil extracts from medicinal and aromatic plants (Argyropoulou et al., 2007). Geraniol (Ci0Hi8O) is a monoterpenoid and an alcohol. The functional group based on geraniol (in essence, geraniol lacking the terminal -OH) is called geranyl. It is important in biosynthesis of other terpenes. It is a by-product of the metabolism of sorbate. The content of this component was reduced in plants that received MOG organic fertilizer as both soil and foliar applications (MOG4) in comparison with control. Although MOG4 may be able to increase growth and result in high dry matter production, it contains modest essential oils, which express as dilution effect hypothesis. In plant treated with MOG3 a significant difference was observed between two locations, since geraniol content in plant grown in Piranshah was two-times more than Maragheh. This is in line with the assertion of Yousefzadeh et al. (2013) that plants differ in their response to changing soil fertility and environmental conditions. Geranial (3,7-dimethyl-2,6-octadienal) is a pair of terpenoids with the molecular formula C10H16O. The two compounds are double bond isomers. The ¿-isomer is known as geranial or citral. It also has strong antimicrobial qualities and pheromonal effects in insects (Onawunmi, 1989). The application of chemical fertilizer (N.P.K) induced a slight increase in geranial content. Mean comparison of the locations revealed that plants grown in Piranshahr had a higher content of this compound. Although, the application of MOG organic fertilizer in some case reduced the percentage of essential oils, but it increased in growth and yields of essential oils can compensate the previous loss. Geranyl acetate (3,7-Dimethyl-2,6-octadiene acetate; C12H20O2) is a natural organic compound that is classified as a monoterpene. Geranyl acetate is a natural constituent of more than 60 essential oils, including in different vegetables. Geranyl acetate and p-cymene also presented some antioxidant effects. Comparison of this organic compound between the locations showed that plants grown in Maragheh had a higher content of Geranyl acetate. The highest percentage of this compound was recorded in plant grown in Maragheh and treated with MOG3. Table 5: Essential oil composition of Dracocephalum moldavica L. influenced by different fertilizer regimes in two locations. Fertilizer Treatments Control" N.P.K MOGi mog2 mog3 MOG4 compound RÎ Pira'. Mara.d Pira. Mara. Pira. Mara. Pira. Mara. Pira. Mara. Pira. Mara. Sabinene 977 0.17 0.30 0.23 0.35 0.26 0.18 0.22 0.24 0.24 0.20 0.12 0.29 P-Pinene 989 1.77 1.30 1.93 1.82 1.29 0.89 2.24 1.62 2.13 0.87 2.03 1.26 (E)-P-ocimene 1041 0.24 0.13 0.21 0.22 0.22 0.20 0.26 0.17 0.24 0.14 0.29 0.16 y-terpinene 1056 0.89 0.51 0.85 0.819 0.18 0.74 0.98 0.65 0.92 0.45 1.11 0.31 Linalool 1109 0.60 0.98 0.76 0.98 0.78 1.12 0.85 0.89 0.82 1.00 0.65 0.85 cis Limonene oxide 1167 1.10 0.87 0.99 0.92 0.62 0.64 1.05 0.92 1.11 0.53 1.05 0.53 Citronellal 1171 0.33 0.27 0.39 0.26 0.19 0.20 0.31 0.28 0.38 0.15 0.37 0.21 Trancelimonene oxide 1180 1.73 1.38 1.73 1.50 0.93 1.00 1.67 1.43 1.69 0.83 3.03 0.75 Neral 1245 0.25 0.38 0.32 0.32 0.37 0.37 0.33 0.38 0.36 0.38 0.22 0.36 Geraniol 1267 34.18 36.03 35.14 34.06 37.93 33.23 35.71 34.37 36.28 16.81 30.84 32.11 geraNial 1289 30.91 27.77 33.92 28.01 30.05 26.78 27.84 27.32 29.34 24.60 29.32 25.82 Neryl acetate 1361 1.52 1.78 1.43 2.02 1.61 2.35 1.46 2.06 1.36 2.14 1.50 3.66 Geranyl acetate 1376 25.43 27.45 21.04 27.88 23.16 30.17 26.19 28.80 24.21 32.43 28.43 29.03 E-Caryophyllene 1482 0.23 0.20 0.24 0.21 0.14 0.10 0.24 0.25 0.26 0.14 0.24 1.45 Total 99.35 99.35 99.18 99.369 97.73 97.97 99.35 99.38 99.34 80.67 99.2 96.79 a Fertilizer treatments: MOGi: soil application at sowing stage, MOG2: foliar application when first flowers were observable, MOG3: soil application at sowing and at 5 to 6 leaf stage, MOG4: soil application at sowing and at 5 to 6 leaf stage with foliar application when first. bRl, retention indices in elution order from DB-5 column. cThe fist location: Piranshahr. d The second location Maragheh. 4 CONCLUSION Our results suggested that using liquid MOG organic fertilizer as both soil and foliar applications could result in better vegetative and reproductive growth, dry herbage yield, and essential oil yield. The results confirm that application of MOG4 fertilizer treatment provides an appropriate substitute to the use of chemical N.P.K fertilizers and can lead at the end to improving the productivity of this plant. Because organic fertilizer may improve the use efficiency of essential mineral elements and reduced the amount of chemical fertilizers application, also prevented the environment contamination from widespread application of chemical fertilizers. Results revealed that in region with cold Mediterranean climate the production of dragonhead plants will be more successful than cool sub-humid temperate climate. 5 ACKNOWLEDGMENT This work was financially supported by a grant from the Ministry of Science, Research and Technology (Iran). 6 REFERENCES Abdelaziz M., Pokluda R. Abdelwahab M. 2007. 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COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.09 Agrovoc descriptors: nicotiana tabacum, agrobacterium tumefaciens, genetic markers, dna, genetic transformation, regeneration Agris category code: f30 The impact of plasmid on regeneration and expression efficiencies of gfp gene in tobacco (Nicotiana tabacum L.) Niko PAVLIN1, Zlata LUTHAR2 Received February 17, 2014; accepted March 06, 2014. Delo je prispelo 17. februarja 2014, sprejeto 06. marca 2014. ABSTRACT Tobacco leaf explants were transformed by bacteria Agrobacterium tumefaciens (A. t.) and plasmid pBIN mgfp5-ER, which has a single copy of the green fluorescent gfp gene and A. t.-pART27 2mgfp5-ER, which has two copies of the gfp gene. Both plasmids have a built-in selection nptII gene for resistance to the antibiotic kanamycin. The presence of the green fluorescent mGFP-ER protein was detected with the epifluorescent microscope in the individual cells 3 days after transformation with A. t. -pART27 2mgfp5-ER and after 6 days in cells transformed with A.t.-pBIN mgfp5-ER. After infection by A. t.-pART27 2mgfp5-ER, in most cases the regeneration was direct, without intermediate stages of callus and faster, as the first globular structures were formed 10-12 days after transformation and a 204 % regeneration was achieved, while the first globular structure, after infection with A. t.-pBIN mgfp5-ER, occurred after 18 days and formed more callus and the regeneration was only 78.4 %. The duplex PCR analysis, performed on all 149 resulting regenerants, confirmed the presence of fragments of length 650 bp specific to the selection nptII gene and length of 422 bp specific for gfp marker gene. Key words: Nicotiana tabacum, marker gfp gene, selection nptII gene, transformation efficiencies, transgene exspression, DNA analysis IZVLEČEK VPLIV PLAZMIDA NA USPEŠNOST REGENERACIJE IN IZRAŽANJA gfp GENA V TOBAKU (Nicotiana tabacum L.) Listne izsečke tobaka smo transformirali z bakterijo Agrobacterium tumefaciens (A. t.) in plazmidom pBIN mgfp5-ER, ki ima eno kopijo zeleno fluorescentnega gfp gena in A. t.-pART27 2mgfp5-ER, ki ima dve kopiji gfp gena. Oba plazmida imata vgrajen še selekcijski nptII gen za odpornost na antibiotik kanamicin. Prisotnost zeleno fluorescentnega mGFP-ER proteina smo z epifluorescentnim mikroskopom zasledili v posameznih celicah 3 dni po transformaciji z A. t.-pART27 2mgfp5-ER in po 6 dneh tudi v celicah transformiranih z A. t.-pBIN mgfp5-ER. Regeneracija je bila po okužbi A. t.-pART27 2mgfp5-ER v večini primerov direktna, brez vmesne faze kalusa in hitrejša, saj so prve globularne strukture nastale že 10-12 dni po transformaciji ter dosežena je bila 204 % regeneracija. Prve globularne strukture po okužbi z A. t.-pBIN mgfp5-ER so se pojavljale šele po 18 dneh, nastalo je več kalusa in regeneracija je bila nižja, samo78,4 %. Pri vseh 149 nastalih regenerantih smo z dupleks PCR analizo potrdili prisotnost fragmentov dolžine 650 bp, značilnih za selekcijski nptII gen in fragmentov dolžine 422 bp, značilnih za markerski gfp gen. Ključne besede: Nicotiana tabacum, markerski gfp gen, selekcijski nptII gen, uspešnost transformacije, izražanje transgenov, DNA analiza 1 INTRODUCTION Biotechnological techniques of genetic transformation represent an integral complement and an appealing alternative to conventional plant breeding methods, since they enable a relatively rapid introduction of desirable traits into selected cultivars. With the possibility to introduce foreign 1 Sajenice 1, 8233 Mirna, e-mail: niko.pavlin@gmail.com 2 Department of Agronomy, Biotechnical Faculty, University of Ljubljana, Jamnikarjeva 101, SI-1000 Ljubljana, e-mail: zlata.luthar@bf.uni-lj.si DNA into plant cells, it has become possible to modify the expression of plant endogenous genes or to introduce novel genes of agronomical importance. Genetic transformation has become useful in improving plant properties and for the detection of gene functions in plants (Rao et al, 2009). An efficient plant regeneration system is an important prerequisite for a successful transformation procedure. Test or marker genes are genes whose gene product can be visually identified and is location determined. They enable quick identification of transformed tissues. Marker genes that can be detected by other means, such as taste or smell, can also be useful (Witty, 1989). In most cases, only a small proportion of plant cells transform, so it is necessary to include a selection gene together with the desired gene, by which transformed cells can be distinguished from non-transformed ones. The best known fluorescent protein is the green fluorescent protein (GFP) from the jellyfish (Aequorea victoria) (Haseloff and Amos, 1995), which emits green fluorescence under illumination with long-wave UV light. The wild-type gfp gene was modified in such a way that it effectively reflects in plants and the spectral properties and fluorescence change and improve (Reichel et al, 1996; Haseloff et al, 1997). Genes for the synthesis of fluorescent proteins have advantages over other marker genes because they can be visually detected in living cells without the use of invasive procedures using substrates and products that could diffuse within or between cells. Transformed cells, in which these genes express, can be identified shortly after the transformation and it can be determined whether they are dividing (Harper et al, 1999). Fluorescent proteins can also be used to monitor the destiny of transgenes introduced into cultivated plants and their impact on the environment (Stewart, 2005). Tobacco (Nicotiana tabacum L.) has been shown to be a very suitable model plant for genetic transformation because it grows quickly and successfully in tissue culture. Regeneration from leaf explants is fast and efficient (Stolarz et al, 1991). In this study, we monitored the influence of plasmid on regeneration and phenotypic expression of gfp fluorescent genes and selection nptII gene in tobacco. 2 MATERIAL AND METHODS 2.1 Plant material, plasmids and agrobacterium-mediated transformation The leave explants of micropropagated tobacco variety Havana 38 were used for transformation with two plasmids. The commercial bacterium A. t. strain LBA4404 contains plasmid pBIN mgfp5-ER or plasmid pART27 2mgfp5-ER. Plasmid pBIN mgfp5-ER is a binary vector, it contains the marker green fluorescent gfp gene and the plant selection nptII gene for resistance to the amino glycoside antibiotic kanamycin for selection of transformed plant tissues. Plasmid pART27 2mgfp5-ER is a binary vector, which contains two repetitions of mgfp5-ER gene from the vector pBIN mgfp5-ER and the same selection nptII gene. Transformation of tobacco leaves with A. t. was performed using a slightly modified method for transformation of leaves as suggested Horsch et al. (1985) and Fisher and Guiltinan (1995). Tobacco leaves were cut under sterile conditions to explants of about 1 cm2. For plasmid pBIN mgfp5-ER 60 leaf explants were prepared and for plasmid pART27 2mgfp5-ER 50 explants. Bacterial suspensions of A. t, with the appropriate plasmid included, were incubated and prepared for transformation and co-cultivated according to Oven and Luthar (2013). Then, the leaf explants were transferred onto selective MSr medium with the addition of [Fe-Na2-EDTA 0.1 mg/l, thiamine 0.1 mg/l, 6-benzylaminopurine (BAP) 1.0 mg/l, 1-naphthaleneacetic acid (NAA) 0.1 mg/l, agar 8 g/l; pH 5.8] (Stolarz et al., 1991) without acetosyringone and with the addition of timentin 150 mg/l to prevent the growth of A t. bacteria and an appropriate selection antibiotic 300 mg/l of kanamycin for the selection of tobacco transformants after infection both with A. t.-pBIN mgfp5-ER or A. t.-pART27 2mgfp5-ER. Explants were cultured in a growth chamber at a 16/8 hour photoperiod and at temperature of24 ± 1 °C, illuminated with about 40 ^mol/m2s. After five weeks, the explants were transferred or sub-cultured on the appropriate fresh selective MSr medium. The resulting regenerants were transferred onto MS medium with the addition of the selection antibiotic kanamycin, without timentin. After five weeks, the regenerants that had successfully grown were transferred to the appropriate MS selective medium. 2.2 Expression of gfp gene Expression of fluorescent marker genes in the explants was observed 3 and 6 days after infection and at the beginning of regeneration in the rising stages of pessaries or inception. Transformed tobacco explants were examined by epifluorescent microscope (Nikkon SMZ 1000) at 20 x magnification and appropriate filters for the detection of the green fluorescence gfp gene. For the detection of green fluorescent protein mGFP5-ER (both of plasmids pBIN mgfp5-ER or pART27 2mgfp5-ER), which has an excitational maximum at 484 nm and emission maximum at 510 nm, a set of filters with EX 480/40 nm, DM 505 nm and BA 535/50 nm was used. 2.3 Molecular analysis transgenes by PCR method and agarose gel electrophoresis For determination of the presence of transgenes in 149 tobacco transformed regenerants and non-transformed - negative control, the complete DNA was isolated, according to the method of Kump et al. (1992). The concentration of isolated DNA in solution was measured using a DNA fluorimeter DyNA Quant™ 200 (GE Healthcare), according to the standard method of producer. DNA samples were diluted to 20 ng/jl. Specific multiplication of gfp and nptII genes was carried out in duplex PCR reactions using two pairs of primers: GFPla (forward: 5'-AGT GGA GAG GGT GAA GGT GAT G-3') / GFP lb (reverse: 5'-TTG TGG CGG GTC TTG AAG TTG G-3') and NPTIIla (forward: 5'-GAG GCT ATT CGG CTA TGA CTG-3') / NPTIIlb (reverse: 5'-ATG GGG AGC GGC GAT ACC GTA-3'). In a total volume of 25 (jl the PCR reaction mixture contained 5 jl of DNA and 20 jl of PCR mixture: lxPCR buffer [10 mM Tris-HCl, 50 mM KCl, 0.08% Nonidet P40] (Fermentas), 2 mM MgCl2, 0.2 mM of each dNTP, 4x0.5 jM suitable primer and 0.5 units of enzyme Taq DNA polymerase (Fermentas) were added. The PCR reaction was carried out in a cyclical thermostat GeneAmp PCR System 9700 (PE Applied Biosystems, USA) using the modified temperature model (Lakshmi et al., l998): initial denaturation of 5 min at 94 °C; 33 repeated cycles: denaturation of DNA l min at 94 °C, annealing of primers l min at 58 °C, synthesis of DNA fragments l.5 min at 72 °C; final incubation 7 min at 72 °C; samples were stored at l2 °C until analysis amplified fragments by agarose gel electrophoresis. For the separation of DNA fragments, horizontal electrophoresis was used on a l.4 % gel according Oven and Luthar (20l3). 3 RESULTS AND DISCUSSION 3.1 Regeneration of tobacco leaf explants and transgene expression After three days of A. t. -pART27 2mgfp5-ER transformation, some cells expressed the mGFP5- ER protein at the leaf explants and after 6 days, the mGFP5-ER protein expression in the cells transformed with A. t.-pBIN mgfp5-ER (Figure 1). Figure 1: Observation of the mGFP5-ER protein expression after 6 days A. t. mediated transformation of tobacco examined under an epifluorescence microscope with white light (left) and with the special filter set for detection of green fluorescence (right) Germs of the first regenerants occurred after 10-12 days after transformation with A. t. -pART27 2mgfp5-ER and after 18 days after transformation with A. t.-pBIN mgfp5-ER. After transformation A. t. -pART27 2mgfp5-ER the regeneration was mostly direct, without an intermediate callus (Figure 2), as noted by Stolarz et al. (1991). After transformation with A. t.-pBIN mgfp5-ER we obtained more callus and less regenerants. Figure 2: Observation of the mGFP5-ER protein expression in globules and regenerant after A. t. mediated transformation of tobacco examined under an epifluorescence microscope with white light (left) and with the special filter set for detection of green fluorescence (right) After five weeks, a large number of regenerants was observed after transformation with A. t.-pART27 2mgfp5-ER and less regenerants after transformation with A. t.-pBIN mgfp5-ER. Regenerants from leaf explants, in which phenotypic expression of the inserted fluorescent genes was observed, were transferred onto MS medium with the addition of an appropriate selection antibiotic. After next five weeks we obtained new regenerants. In total, 102 regenerants were obtained from 50 explants after transformation with A. t. -pART27 2mgfp5-ER and less, only 47 regenerants from 60 explants after transformation with A. t.-pBIN mgfp5-ER. The leaf explants after incubation with A. t. and an appropriate plasmid, were co-cultivated on MSr medium with added acetosyringone 100 ^M, in order to increase the infection, as described by Sunilkumar et al. (1999). In nature, phenolic substances such as acetosyringone, which are released on wounding of plant tissue, trigger the activation of genes for virulence (vir genes) in infection with Agrobacterium (Gelvin, 2003). We obtained a high percentage of transformed regenerants, which can be attributed to the acetosyringone attached to the MSr medium in the period of co-cultivation in the combination with plasmid pART27 2mgfp5-ER. After the completion of co-cultivation, timentin 150 mg/l was added to the MSr medium, which effectively inhibited the growth of the A. t. bacteria but did not adversely affect regeneration. The regenerants on the medium with timentin were distinctly dark green. Nauerby et al. (1996) reported that timentin in this concentration completely prevented the multiplication of A. t. and positively impacted on the regeneration of leaf and cotyledon explants of tobacco. Similarly, Cheng et al. (1998) emphasized that timentin is just as effective as carbenicillin and cefotaxime and does not have an inhibitory effect on the regeneration of shoots in tobacco and Siberian elm. 3.2 Molecular analysis of transgenes integration DNA analysis was performed on all 149 surviving regenerants. 40 41 42 43 44 45 46 K P S M Figure 3: Amplified DNA fragments by duplex PCR with the specific set of primers for the mgfp-ER gene (422 bp) and the specific set of primers for the nptII gene (650 bp). The figure shows only the 7 regenerants of 149. 40 - 46: transformed tobacco regenerants; K: control, non-transformed tobacco; P: plasmid; S: blind samples; M: size standard. In all 149 regenerants of tobacco transformed with A. t.-pBIN mgfp5-ER (47) and with A. t. -pART27 2mgfp5-ER (102) that were grown on selective medium, the presence of fragment length 650 bp (selection nptII gen) and fragment length 422 bp (marker gfp gene) was released (Figure 3). The transformation efficiencies achieved 204 % after the A. t.-pART27 2mgfp5-ER, and 78.4 % after the A. t.-pBIN mgfp5-ER-mediated transformation. 4 CONCLUSION As a result of transformation with A. t. -pART27 2mgfp5-ER the regeneration capacity was faster and efficient, mostly direct, without an intermediate callus, while after transformation with A. t.-pBIN mgfp5-ER more callus and 2.6 times less regenerants were obtained. 5 REFERENCES Cheng Z.M., Schnurr J.A., Kapaun J.A. 1998. Timentin as an alternative antibiotic for suppressin of Agrobacteriu tumefaciens in genetic transformation. Plant Cell Reports, 17: 646-649, DOI: 10.1007/s002990050458. Gelvin S.B. 2003. Agrobacterium-mediated plant transformation: the biology behind the "gene-jockeying tool". Microbiology and Molecular Biology Reviews, 67: 16-37, DOI: 10.1128/MMBR.67.1.16-37.2003. Fisher D.K., Guiltinan M.J. 1995. Rapid, efficient production of homozygous transgenic tobacco plants with Agrobacterium tumefaciens: a seed-to-seed protocol. Plant Molecular Biology Reporter, 13, 3: 278-289, DOI: 10.1007/BF02670906. Harper B.K., Mabon S.A., Leffel S.M., Halfhill M.D., Richards H.A., Moyer K.A., Stewart C.N. 1999. Green fluorescent protein as a marker for expression of a second gene in transgenic plants. Nature Biotechnology, 17: 1125-1129, DOI: 10.1038/15114. Haseloff J., Amos B. 1995. GFP in plants. Trends in Genetics 11: 328-329, DOI: 10.1016/0168-9525(95)90186-8. Haseloff J., Siemering K.R., Prasher D.C., Hodge S. 1997. Removal of a cryptic intron and subcellular localization of green fluorescent protein are required to mark transgenic Arabidopsis plants brightly. Proceedings of the National Academy of Science of the United States of America, 94: 21222127, DOI: 10.1073/pnas.94.6.2122. Horsch R.B., Fry J.E., Hoffmann N.L., Eichholtz D., Rogers S.G., Fraley R.T. 1985. A simple and general method for transferring genes into plants. Science, 227: 1229-1231, DOI: 10.1126/science.227.4691.1229. Kump B., Svetek S., Javornik B. 1992. Izolacija visokomolekularne DNA iz rastlinskih tkiv. Zbornik Biotehniške fakultete Univerze v Ljubljani - Kmetijstvo, 59: 63-66. Lakshmi Sita G., Sreenivas G.L., Bhattacharya A. 1998. Agrobacterium mediated transformation of sandalwood (Santalum album L.) a tropical forest tree. Plant Tissue Culture and Biotechnology, 4, 34: 189-195. Nauerby B., Billing K., Wyndaele R. 1996. Influence of the antibiotic timentin on plant regeneration compared to carbenicillin and cefotaxime in concentrations suitable for elimination of Agrobacterium tumefaciens. Plant Science, 123: 169-177, DOI: 10.1016/S0168-9452(96)04569-4. Oven K., Luthar Z. 2013. Expression and molecular analysis of DsRed and gfp fluorescent genes in tobacco (Nicotiana tabacum L.). Acta agriculturae Slovenica, 101 (1): 5-14, DOI: 10.2478/acas-2013-0001. Rao A.Q., Bakhsh A., Kiani S., Shahzad K., Shahid A.A., Husnain T., Riazuddin S. 2009. The myth of plant transformation. Biotechnology Advances, 27: 753-763, DOI: 10.1016/j.biotechadv.2009.04.028. Reichel C., Mathur J., Ecke P., Langenkemper K., Koncz C., Schell J., Reiss B., Maas C. 1996. Enhanced green fluorescence by the expression of an Aequorea victoria green fluorescent protein mutant in mono- and dicotyledonous plant cells. Proceedings of the National academy of Sciences of the United States of America, 93: 5888-5893, DOI: 10.1073/pnas.93.12.5888. Stewart C.N. 2005. Monitoring the presence and expression of transgenes in living plants. Trends in Plant Science, 10: 390-396, DOI: 10.1016/j.tplants.2005.06.003. Stolarz A., Macewicz J., Lörz H. 1991. Direct somatic embryogenesis and plant regeneration from leaf explants of Nicotiana tabacum L. Journal of Plant Physiology, 137: 347-357, DOI: 10.1016/S0176-1617(11)80144-6. Sunilkumar G., Vijayachandra K., Veluthambi K. 1999. Preincubation of cut tobacco leaf explants promotes Agrobacterium-mediated transformation by increasing vir gene induction. Plant Science, 141: 51-58, DOI: 10.1016/S0168-9452(98)00228-3. Witty M., 1989. Thaumatin II: a simple marker gene for use in plants. Nucleic Acids Research, 17: 3312, DOI: 10.1093/nar/17.8.3312. COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.10 Agrovoc descriptors: phosphorus, fertilizer application, losses from soil, climatic factors, precipitation, grasslands, grassland soils, land use, leaching, soil transport processes Agris category code: p35 The effect of land use on phosphorus dynamics in golf course soil Maja PODGORNIK1 and Marina PINTAR2 Received July 04, 2013; accepted October 08, 2013. Delo je prispelo 04. julija 2013, sprejeto 08. oktobra 2013. ABSTRACT IZVLEČEK Although, it is usually considered that P applied in fertilizers is taken up by crops or immobilized in the soil, and therefore P losses from agro systems is negligible; recent research indicates that significant P leaching out of the root zone, can occur where certain combinations of land use practice, soil properties and climate condition exist. Therefore special attention was given to dynamics of total P (TP) and plant available P in golf course soils. A field study was carried out to assess how different environmental condition and management practices affect dynamics of TP and plant available P in soil. The proportions of plant available P and TP in the golf rough significantly correlated with precipitation. Since no relationship between precipitation and the P dynamics in soil on the greens and fairways was observed. Key words: management practices, Technosols, greens, fairways, golf course, molybdate-reactive P, total P VPLIV RABE TAL NA DINAMIKO FOSFORJA V TLEH GOLFIŠČ Res je, da se dodani P z gnojenjem porabi za prehrano rastlin ali pa se v procesu imobilizacije močno veže na talne delce, vendar so novejše raziskave pokazale, da se pri določeni kombinaciji rabe zemljišč, lastnosti tal in klimatskih pogojev tudi P lahko izpira v globlje plasti tal. Zaradi spoznanja novejših raziskav o izpiranju P v globlje plasti tal smo v naši raziskavi posebno pozornost namenili dinamiki celokupnega P in rastlinam dostopnega P v tleh igrišč za golf. Z terensko raziskavo smo želeli oceniti, kako različni okoljski dejavniki in raba tal vplivajo na dinamiko celokupnega P in rastlinam dostopnega P v tleh. Rezultati raziskave so pokazali, da obstaja značilna povezava med padavinami in vsebnostjo rastlinam dostopnega P ter celokupnega P v tleh ledine na igrišču za golf. Medtem ko, povezava med padavinami in dinamiko P v tleh zelenic in čistin igrišč za golf ni bila ugotovljena. Ključne besede: tehnike upravljanja, tehnosoli, zelenice, čistine, golf igrišče, rastlinam dostopni P, celokupni P 1 INTRODUCTION Golf courses often appear to be some of the most natural environments but, as in the case of well-ordered gardens, they are products of human activity, due to the large use of energy and water required in preparing and maintaining them. The mosaic of "greens" (turfed and carefully mown areas), "bunkers" (unvegetated sandy concave areas), thickets, ponds etc. is obtained through marked modification of the original soils or even their complete removal. The fertilizers required annually to keep greens and fairways, in good condition, can cause serious pollution of soil and waters (Suzuki et al., 1998; Certini and Scalenghe, 2006). Although, it is usually considered that P applied in fertilizers is taken up by crops or immobilized in the soil, and therefore P losses dr. University of Primorska, Science and Research Center of Koper, Garibaldijeva 1, 6000 Koper, Slovenia, University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, 6000 Koper, Slovenia, maja.podgornik@zrs.upr.si prof.dr. Biotechnical Faculty, Agronomy Department, Jamnikarjeva 101, SI - 1111 Ljubljana, Slovenia, e-mail: marina.pintar@bf.uni-lj.si 2 from agro systems is negligible; recent research indicates that significant P leaching out of the root zone, can occur where certain combinations of land use practice (over fertilization or excessive manuring), soil properties (sandy subsoil, high organic matter and the presence of preferential flow paths) and climate condition exist (Sims et al., 1998). Globally, the creation of golf courses is currently one of the most rapidly expanding types of extensive land development (Tanner and Gange, 2005). In recent years, considerable interest in golf course development has also been expressed in the Balkan region, despite the minor golf tradition and low number of domestic golfers. It is therefore expected that a large number of new golf courses will be built over the next few years in the Balkan region. Currently, thirty-two golf courses cover roughly 12 km2 in the Balkan region and their areas have been increasing in recent years (Petrova, 2005). Slovenia has the highest number of golf courses per capita in the Balkan region (Meglic, 2001). Slovenia is an agricultural country with a total area of 20 722.77 km2. The majority of the country is covered by forest (13 577.03 km2) and agricultural land (5 387.92 km2) (Yearbook Republic of Slovenia, 2007). Golf courses cover nearly 0.02 % or 3.50 km2 of the country's total area (Skumavec and Sabic, 2005). A 9-hole golf course requires approximately 0.34 km2 of land, which is seven times more than the average family farm (0.05 km2) and six times less than the average area of a commercial agricultural operation (2.20 km2) in Slovenia (Meglic, 2001). Golf course development in Slovenia typically replaces agricultural or native lands with intensively managed turf grass, and course construction involves modification of the original soil profile and land surface. Many golf course studies have documented the transport of phosphorus (P) into the groundwater if excessive loading of fertilizer is applied to sandy soil with limited P sorption capacity (Shuman 2005; Shuman, 2003). In a lysimeter study of a golf course, P levels were higher in the leachate than the threshold value for surface water (0.3 mg l-1) (Wong et al., 1998). In a greenhouse study with simulated golf greens, peak P concentrations in the leachate exceeded 20 mg l-1 (Shuman, 2001). Very few publications (Bartlett et al. 2008, Devitt et al., 2007, King et al., 2007 and McCoy and McCoy, 2009) have documented the effects of climatic conditions and land use on the P dynamics in golf course soils. The primary objective of this research was to monitor two golf courses (green, fairway and forest as part of golf rough to which no fertilizer or water for irrigation is applied) in Slovenia to assess how different environmental condition (i.e. precipitation) could affect management practices and dynamics of total P (TP) and plant available P in soil. The second objective of the study was to observe the interaction between precipitation and irrigation regimes and dynamics of TP and plant available P, because environmental condition and management practices (irrigation and fertilizer) could affect the TP and plant available P in soil. 2 MATERIALS AND METHODS An intensive monitoring study was performed on two golf courses in Slovenia, from December 2005 to December 2006. The first golf course is located in Lipica (N: 45°40'34", E: 13°53'04", Height: 320 m.a.s.l., Holes: 9, Total surface: 40 ha), in typical Karst countryside with a Mediterranean climate. The second golf course is located in Bled (N: 46°22'18", E: 14°08'15", Height above sea level: 510 m, Holes: 27, Total surface: 100 ha), on the periphery of the Julian Alps, with a subalpine climate. The choices of location were based on the different soil conditions (Table 3). During the study period, precipitation was regularly measured at both plots (Lipica and Bled). The amount of rainfall at both locations (1 024 l m-2 - Lipica and 947 l m-2 - Bled) was much lower than the 30-year historical average (1 420 l m-2 -Lipica and 1 400 l m-2 - Bled). The average monthly temperature ranges recorded were from 1.5 °C (January) to 19.8 °C (July) in Lipica and -2.2 °C (January) to 18.1 °C (July) in Bled. The golf courses operated from March to November, when the bulk of the granular NPK fertilizers were applied. Different fertilization practices and different irrigation scheduling methods were used for each of the two golf courses (Table 1). In Lipica, more water is used for irrigation due to less precipitation and higher temperatures. The total amount of the water applied to the golf greens was 15 000 m3 ha-1 y-1 in Lipica and 7000 m3 ha-1 y-1 in Bled, while the average amount of water applied to agricultural land in Slovenia in the same period was 2220 m3 ha-1 y-1 (Yearbook Republic of Slovenia, 2006). Table 1. Phosphorus (kg ha-1) and water (m3 ha-1) annual application rates for the golf courses - Lipica and Bled Phosphorus application Water application Location Land use Area (ha) Period of application Application frequency Annual application rate (kg ha-1) Period of application Sum of annual Application Annual application rate application rate frequency (m3 ha-1) and rainfall _(m3 ha-1) Lipica Fairway Fairway 2 February - October 12 April - October 1.5 April - October April 35 August October twice a month twice a year three times during growing season three times during growing season 17.5 April - October twice a day 28.3 April - October once a day 50 June - September twice a week 70 June - September twice a week 15 000 1 250 20 123 6 373 7 000 13 098 557 6 655 We monitored the concentration of plant available P (PO4-P mg kg-1) and TP (mg kg-1) in the soils of three different land uses (golf green, golf fairway and forest as part of the rough). In order to assess the quantity of plant available P and TP in the soil, fresh soil samples were collected every two weeks, with some gaps, as seen in the results. Five soil samples from five randomly chosen sites from the topsoil (10 cm deep) from each type of land use (green, fairway and rough) at both locations (Lipica, Bled) were collected before the monitoring was performed. All samples were analyzed for their concentrations in plant available P and TP. The results obtained were subjected to statistical evaluation. Evaluated standard deviation (CV %) (Table 2) has been used for further statistical analysis. During the monitoring process, subsamples were randomly collected from the topsoil (10 cm deep) from each type of land use (green, fairway and rough) at both locations (Lipica, Bled) and mixed, to form one composite sample per land. Air-dried soil samples were analyzed using aqua regia extraction methods (SIST ISO 11466, 1995) to assess TP, and ammonium-lactate (AL) extracts, which is the most appropriate method due to the pH of the soil (5.7 - 7.2) (Olsen et al., 1954), to assess plant available P. AL extract was used with the photometric molybdenum blue method (Vajnberger, 1996; Hoffmann, 1991). Table 2: The samples average concentration (mg kg-1) with standard deviation (SDS) and coefficient of variation in brackets (CV %) of soil phosphorus concentrations (total phosphorus - TP and plant available P) (N=5) Lipica Bled plant available P TP plant available P TP _s= 6.1±2.1 (27.66 %) 920±88 (9.60 %) 4.2±1.7 (40.75%) 368±22 (6.23%) Pi fi O po J <5 'o 3 O <5 a & ra rs & 7.62 0.67 0.17 0.90 89.86 22.46 41.04 3.54 8.99 27.91 5.35 11.13 7.42 8.78 4.71 1.12 2.61 8.32 7.64 5.6 10.6 72 44 6.6 Epileptic Technosol 57 6.9 60 7.0 Protocambic Leptosol 58 6.8 (Humic, Eutric) 70 6.5 Rendzic Leptosol 48 5.7 Technosol 56 7.1 (Epiarenic) 44 6.9 Leptosol (Humic, 56 7.3 Eutric) 76 6.0 Epileptic Rendzic 72 6.0 Phaeozem (Protosiltica) 1 Indicating an early stage of development of silt loam feature. STATGRAF software was used for statistical analysis. Two-sided Pearson's correlations were used to test the relationship between the parameters studied. We used the t-test for dependent samples. The significance level was set at P < 0.05. Standard deviation (SDS) and coefficient of variation (CV %) were estimated by examining samples taken before the monitoring was performed. 3 RESULTS AND DISCUSSION The variation in the quantities of TP and plant available P, which were estimated on five soil samples randomly collected from each of the three studied locations (greens, fairways and rough) at two golf courses (Lipica - 9 holes; 40 ha and Bled - 27 holes; 100 ha), can be attributed to a combination of factors including environmental conditions, vegetation cover and land management practices. Large impact on the quantities of TP and plant available P in different soil can be attributed also to soil sampling procedure. Five soil samples were collected each time but the collected soil samples were then bulked and the chemical analysis of TP and plant available P was conducted on the bulked soil samples. All sampling standard deviations during the P monitoring period were the same as the standard deviations of the five previous samples, collected before the P monitoring work started. TP and plant available P concentrations The dynamics of TP concentrations in the soil samples followed different patterns than those for plant available P. Green soils exhibited lower concentrations of TP (average concentration: Lipica - 476±128 mg kg-1; Bled - 187±112 mg kg-1) than rough soils (average concentration: Lipica -1097±125 mg kg-1; Bled - 740±187 mg kg-1). In contrast, green soils contained a much higher concentration of plant available P (average concentration: Lipica - 73±24 PO4-P mg kg-1; Bled - 41±17 PO4-P mg kg-1) than rough soils (average concentration: Lipica - 29±14 PO4-P mg kg-1; Bled - 26±17 PO4-P mg kg-1) (Fig. 1 and 2). The results are comparable to a study by Leinweber et al. (1999), in which they found that higher mean concentration of the most labile forms of P tend to occur in arable soils, and more residual (stable) P in soil under fallow or reafforestation. Cultivation and the application of P fertilizers are responsible for the decline in stable P and the higher amount of labile P in the green soil in our study. The differences in the concentrations of plant available P and TP between areas of rough and green soil mainly originate from the long-term inputs of plant residue and accumulation of organic matter in uncultivated rough areas and fertilizer application on golf greens. Organic matter is a substantial reservoir for P. The P is bound in phosphate esters, phospholipids and nucleic acids and is released into the soil solution when microbes break down organic matter (Tarafdar et al., 2001). Although the organic carbon concentration of green soils (Lipica: 1.84 %; Bled: 2.53 %) was lower than that of rough soils (Lipica: 13.26 %; Bled: 7.69 %), the plant available P concentrations of green soils (average concentration: Lipica - 73±24 PO4-P mg kg-1; Bled - 41±17 PO4-P mg kg-1) were higher than those of rough soils (average concentration: Lipica - 29±14 PO4-P mg kg-1; Bled - 26±17 PO4-P mg kg-1). The high concentration of organic carbon and low concentration of plant available P in rough soil might be partially due to the slow decomposition of plant litter and mineralization of organic matter. The mineralization of organic matter is the main source of available P for plants in a natural ecosystem (Srivastava and Singh, 1991). In contrast, the main source of plant available P in green soils are fertilizers, because the maintenance of high-quality turf grass on golf greens requires large P fertilizer inputs. According to the study results, organic matter concentration significantly influenced the level of the TP concentration in the rough soils and the high rates of fertilizer P applied to golf course is a possible cause of plant available P accumulation in the green soils. Plant available P concentrations in soil samples from the greens in Lipica (average concentration: 73±24 PO4-P mg kg-1) exceeded the concentration measured in soil samples from the fairways (average concentration: 61±27 PO4-P mg kg-1), presumably due to the low P adsorption capacity of sandy soils on the greens. In a greenhouse lysimeter study performed by Wong et al. (1998), the leachate from greens contained significantly higher plant available P than that of fairways. We observed a different pattern for TP concentrations. TP in green soil (average concentration: Lipica -476±128 and Bled - 187±112 mg kg-1) was significantly lower than in fairway soil (average concentration: Lipica - 1 021±170 and Bled -811±194 mg kg-1) and rough soil (average concentration: Lipica - 1 097±125 and Bled -740±187 mg kg-1). The higher TP concentrations in fairway soil are in contrast to the low level of TP in fairway soil measured in the aforementioned lysimeter study (Wong et al., 1998). A possible reason for the difference is that fairway soil from the lysimeter study probably reflected the interaction between a high frequency of fertilization and low fertilizer application rates. This indicates that the fertilizer application rate on the studied fairways should be reduced and application frequency should change. Such management could be expected to be less harmful to the environment and to reduce the P loading in fairway soils. 0 250 □ □□■□□□ □ 2 1.5 2 14 2.5 1.5 12 1.5 □ 14 2.5 acLp_ sampling data □ precipitation Lipica (mm) S green irrigation (mm) □ fairway irrigation (mm) ■ nutrient application on fairway (kg ha-1) nutrient application on green (kg ha-1) # rough —X— fairway —0— green Precipitation shown on the figures is the sum of rainfall between sampling dates. Fig. 1. Dynamics of total phosphorus - TP (mg kg-1) and plant available P concentrations (PO4-P mg kg-1) in soil samples from rough, green and fairway - Lipica 80 60 40 20 50 0 Š £ □ 20 □ 20 ■ □ 25 10 1A [BEI pHR ©©©©333©©©©©©©©©©©©o©2rfrf sampling data □ precipitation Bled (mm) § green irrigation (mm) □ fairway irrigation (mm) ® rough ■ nutrient application on fairway (kg ha-1) fairway nutrient application on green (kg ha-1) -0-green Precipitation shown on the figures is the sum of rainfall between sampling dates. Fig. 2. Dynamics of total phosphorus - TP (mg kg-1) and plant available P concentrations (PO4-P mg kg-1) in soil samples from rough, green and fairway - Bled Impact of precipitation on P concentrations It has been reported that climatic conditions also influence P dynamics in the soil (Ronggui, 2001). We found, a statistically significant correlation was found between precipitation, plant available P (Lipica r = 0.73; P = 0.005; Bled r = 0.67; P = 0.001) and TP (Bled r = 0.67; P = 0.001) in the soil of rough areas, except for the TP in the soil of the rough in Lipica (r = 0.15; P = 0.62) (Table 4). The concentrations of plant available P and TP in soil of the rough (except TP concentrations in soil of the rough in Lipica) markedly decreased with rainfall events. No correlations were observed among precipitation, plant available P and TP 250 25 20 200 150 100 50 dynamics in soil samples from the greens and fairways (Table 4). In addition to precipitation, the application of water also had an important influence on P dynamics in soil and is the governing factor in soil P consumption. In a greenhouse subsurface irrigation study, Wang and Zhang (2009) showed that the percentage of inorganic P, organic P and plant available P to total P in soil could be affected by irrigation schedules. This was confirmed by the findings of our study. A significant correlation was found for both plant available P and TP concentrations and the application of water on greens at Bled (plant available P: r = 0.89, P = 0.01; TP: r = 0.80, P = 0.05) and Lipica (plant available P: r = 0.73, P = 0.05; TP: r = 0.67, P = 0.01). No statistically significant relationship was observed between precipitation and the P dynamics in soil on the fairways (plant available P: Lipica r = 0.42, P = 0.29; Bled r = 0.71, P = 0.10; TP: Lipica r = 0.27, P = 0.51; Bled r = 0.59, P = 0.21). However, further studies should be done in order to assess how irrigation management practices enhance P availability for plants in green and fairway soil. Table 4: Correlation between the sum of precipitation between two sampling dates and soil phosphorus concentrations (total phosphorus - TP and molybdate-reactive phosphorus - plant available P) on golf courses Lipica and Bled plant available P Lipica Bled TP plant available P TP Multiple Significan Multiple Significan Multiple Significan Multiple Significan correlation ce level correlation ce level correlation ce level correlation ce level coefficient (P) coefficient (P) coefficient (P) coefficient (P) _r_(r)_&_(r)_ JS g u (§ G.73 G.GG47 G.l5 G.6l5 G.67 G.GGl G.67 G.GGl b b O G.4l G.ll G.G6 G.92 G.27 G.24 G.48 G.G3 b a ft G.2G G.44 G.l4 G.5 G.22 G.34 G.G4 G.8 b Statistically significance value (P < G.G5) Furthermore, a significant correlation was found between the TP and plant available P concentrations on the golf course in Bled. The TP concentration in soil samples from all the types of land use showed a similar temporal trend as plant available P (Fig. 2). The multiple correlation coefficients between TP and plant available P concentrations are: r = 0.77; P = 0.0001 for greens, r = 0.92; P = 0.0001 for fairways and r = 0.83; P = 0.0001 for roughs. The dynamics of TP and plant available P in the rough Bled and Lipica reflected the low plant P uptake. Rapid P uptake occurs only with high soil moisture content and that uptake is proportional to the volume of soil brought close to field capacity and the length of time that it remained moist (Simpson and Pinkerton, 1989). On the other hand, the increased moisture content of soils may enhance microbial activity and, consequently, the mineralization of soil organic matter and plant available P. P enrichment in soil solution in topsoil could increase the risk of P leaching into deeper soil layers or even into the groundwater (Sims et al., 1998). This might indicate that the increase of TP and plant available P concentrations after rainfall is due to the leaching of large amounts of plant available P from the topsoil to lower soil layers and reduction in plant P uptake. Unfortunately, no soil sampling was done below the topsoil layer. Since soil water supply (i.e., irrigation) is one of the most important issues on the observed golf courses, it has an important influence on P dynamics in the soil and is the governing factor in plant P uptake. Impact of fertilization on P concentrations In addition to soil moisture, the applied fertilizers also had a significant effect on P dynamics in the soil. Motavalli and Miles (2002) reported that the addition of fertilization, either in the form of fertilizers or manure, significantly influences the TP and plant available P in the agricultural soil. A similar P application effect on TP concentration was also observed in the golf course soil in Lipica and Bled (Fig. 1 and 2). A significant correlation was found between the TP concentrations and the application of P fertilizer on greens at Bled (r = 0.77; P = 0.0002) and fairways at Lipica (r = 0.74; P = 0.001). Although the TP concentrations increased greatly after the application of P fertilizer, no statistically significant relationship was observed between the quantity of applied P fertilizers and the level of plant available P and TP in soil samples from the greens and fairways. There were much higher concentration of plant available P and TP in the green and fairway soils in Lipica (Fig. 1) than in Bled (Fig. 2), despite that less fertilizer was applied to the golf course in Lipica. The average concentrations of plant available P (and TP) in soil from the greens and the fairways in Lipica were 73±24 and 61±27 PO4-P mg kg-1, respectively (TP: 476±128 and 1 022±170 mg kg-1) while those in the soils from Bled were 41±17 and 41±38 PO4-P mg kg-1, respectively (TP: 187±112 and 811±194 mg kg-1). The different level of soil P between the golf courses in Lipica and Bled is possibly due to their different management practices in the removal of plant biomass on the golf course and fertilizer -irrigation histories. Despite the different level of plant available P (Lipica green: 16,72 mgP2Ü5 100g-1; Lipica fairway: 131,94 mgP2Ü5 100g-1; Bled green: 9,32 mgP2Ü5100g-1; Bled fairway: 9,38 mg P2Ü5100g-1) and fertilizer management practices, AL-method placed the soil from golf course Lipica and Bled in B (6-12 mgP2Ü5100g-1) and C (13-25 mgP205100g-1)P - supplying levels, which represent an medium-optimal supplied soil with P. The level of plant available P in the green and fairway soils in Lipica and Bled probably reflected the high uptake efficiency of turf grass and impact of biomass removal on soil nutrient. As described in Hladnik (2005), annual removal of phosphorus with the biomass of cut grass is 8-13kg/ha. The impact of golf course management on P concentration The soil samples from the green Lipica had a higher plant available P concentration (average value: 73±24 P04-P mg kg-1) than those of fairway (average value: 61±27 P04-P mg kg-1), while the plant available P concentrations from green and fairway Bled were uniform (green 41±17 and fairway 41±38 PO4-P mg kg-1). The low concentration of plant available P from the fairways Lipica indicated a high P absorption capacity of the fairway soil compared to the sandy soil of the greens. There is probably a potential for P leaching into groundwater and surface water (Wong et al., 1998). On the other hand, soil samples from the greens had a lower TP concentration than soil samples collected from the fairways (Fig. 1 and 2), which might be due to a low concentration of organic carbon in the soil of greens (Lipica: 1.84%, Bled: 2.53%) in comparison with fairways (Lipica: 3.96%, Bled: 2.76%). 4 CONCLUSION The results of this study confirm that precipitation significantly alters the amounts and proportions of plant available P and TP in rough. Despite observing no significant relationship between precipitation and the P dynamics in soil on green and fairway, the dynamics of P is probably affected by the quantities of applied water. On the basis of these data, we concluded that apart from precipitation, the application of water also had an important influence on P dynamics in soil and is the governing factor in soil P consumption. Based on the estimation of contribution of precipitation and irrigation to P dynamics in soil, it was also found that the vegetation systems, fertilization management and organic matter content in soil markedly influence the P dynamics in the soil. Relatively undisturbed forest ecosystems on the rough has less plant available P (average concentration: Lipica - 29±14 PO4-P mg kg-1; Bled - 26±17 PO4-P mg kg-1) concentrations than fairways (average concentration: Lipica -61±27 PO4-P mg kg-1; Bled - 41±38 PO4-P mg kg-1) and greens (average concentration: Lipica -73±24 PO4-P mg kg-1; Bled - 41±17 PO4-P mg kg-1). Contrary to this the analyses of the same soil samples, showed that soil from the roughs exhibited significantly greater concentrations of TP (average concentration: Lipica - 1097±125 mg kg-Bled - 740±187 mg kg-1) than soils from the greens (average concentration: Lipica - 476±128 mg kg-1; Bled - 187±112 mg kg-1. In forest ecosystems most of the plant available P is supplied by the slow decomposition and recycling of plant residue through microbial processes in the soil, while the higher amounts of plant available P in golf course soils is the consequence of large amounts of fertilizer application. However, no significant relationship was found between the quantity of applied P fertilizers and the level of total P and plant available P in soil samples of the golf courses, although the total P concentration has increased after fertilizer application. The analyses of soil samples collected from the green and fairway in Lipica showed much higher values of plant available P and TP than the golf course in Bled, despite the fact that a lower quantity of fertilizer was applied to the golf course in Lipica. Despite the different level of plant available and fertilizer management practices the soil form golf course Lipica and Bled belongs to the class of optimal - medium supplied soil with phosphorous. The result of analyses of soil samples from the golf courses also demonstrated that plant available P concentrations in samples from greens exceeded the concentration measured in samples from fairways, probably due to the low P absorption capacity of sandy soils on the green. In conclusion, it is obvious that rainfall regime, water supply, organic matter, P absorption capacity and land use appeared to be the most important factors influencing the P dynamic in the soil. Therefore, modified fertilizer management of golf courses which considered all of these factors are needed to ensure better plant uptake, to minimize the risk transportation of P to groundwater and to reduce the risk of eutrophication of water bodies. 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Yearbook Republic of Slovenia, 2006. 29: p.499 Yearbook Republic of Slovenia, 2007. 33: p. 600 COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.11 Agrovoc descriptors: germplasm, genetic resources, spinacia oleracea, spinach, land varieties, biogeographic regions, agroclimatic zones, biogeography, statistical methods, methods, genotypes, genetic distance Agris category code: f30 Genetic diversity of spinach (Spinacia oleracea L.) landraces collected in Iran using some morphological traits Naser SABAGHNIA1, H.A. ASADI-GHARNEH2, Mohsen JANMOHAMMADI1 Received August 28, 2013; accepted October 16, 2013. Delo je prispelo 28. avgusta 2013, sprejeto 16. oktobra 2013. ABSTRACT Spinach has become an important vegetable crop in most regions of the world and remarkable changes in production amounts have occurred in the past decades due to demand increase in many countries. Fifty-four spinach landraces collected from diverse geographical regions of Iran were evaluated for several qualitative and quantitative traits. Landraces indicated a high variability for measured morphologic characteristics regarding results of variance analysis and descriptive statistics. The first three factors of factors analysis explained 76.8% of variation of spinach landraces. The first extracted factor can be regarded as a leaf property vector; the extracted second factor could be named as yield vector and the third factor was female plants percent vector. The dendrogram of cluster analysis generated from genotypes distance matrices showed that in a distance linkage of 800, the 54 spinach landraces could be agglomerated into sixteen clusters. The number of clusters was verified by multivariate analysis of variance test through Wilks' Lambda statistics. Some spinach landraces such as G10 G13, G38 and G41 were individual cluster and were not similar to the other collected genotypes while some of the spinach landraces were similar to each other and grouped as one cluster such as cluster 9 (C9). The cluster C14 (landrace Karaj 2) was the most favorable genotype due to good performance for most measured quantitative traits. This landrace could be recommended for commercial release after complementary experiments. Also, landraces G1 (Arak) and G3 (Urmia) indicate good potential regarding the measured traits. These landraces could be used directly as commercial cultivars or introduced in spinach breeding programs. Key words: germplasm, morphological variation, multivariate analysis, spinach IZVLEČEK GENETSKA RAZNOLIKOST AKCESIJ ŠPINAČE (Spinacia oleracea L.) ZBRANIH V IRANU, DOLOČENA Z NEKATERIMI MORFOLOŠKIMI ZNAKI Špinača je postala pomembna zelenjadnica v večjem delu sveta in znaten porast njene pridelave se je pojavil zaradi vse večjega povpraševanja v mnogih državah. 54 akcesij špinače, nabranih v različnih delih Irana, je bilo ovrednotenih na osnovi številnih kvalitativnih in kvantitativnih znakov. Akcesije so pokazale veliko variabilnost v merjenih morfoloških znakih glede na rezultate analize variance in opisne statistike. Prvi trije faktorji faktorske analize so pojasnili 76.8 % variabilnosti akcesij špinače. Prvi faktor od teh je bil povezan z lastnostmi listov, drugi s pridelkom in tretji z deležem ženskih rastlin. Dendrogram klasterske analize, generiran na osnovi izračunanih distanc med genotipi je pokazal, da lahko na osnovi distančne povezave 800, 54 akcesij špinače združimo v 16 skupin. Število skupin je bilo potrjeno z multivariatno analizo variance s pomočjo Wilks' Lambda statistke. Nekatere akcesije kot na primer G10 G13, G38 in G41 so bile samostojne skupine in niso bile podobne drugim zbranim genotipom, med tem ko so si bile druge akcesije podobne in so se uvrstile v eno skupino, npr. skupino 9 (C9). Skupina C14 (akcesija Karaj 2) je bila najboljši genotip glede na dobre vrednosti za večino merjenih kvantitativnih znakov. To akcesijo bi lahko priporočili za komercialno uporabo po dopolnih preizkusih. Tudi akcesiji G1 (Arak) in G3 (Urmia) kažeta dober potencial glede na merjene znake. Ti akcesiji bi bili lahko neposredno uporabljeni kot komercialni sorti ali vključeni v žlahtniteljski program špinače. Ključne besede: genski material, morfološka variabilnost, multivariatna analiza, špinača 1 Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Maragheh, Maragheh, Iran 2 Department of Horticulture Science, Islamic Azad University, Khorasgan Branch, Isfahan, Iran 1 INTRODUCTION Spinach (Spinacia oleracea L.) is an edible and annual plant that grows rapidly and has the ability to survive over moderate winter. It is versatile which is used as a salad, a cooked vegetable or as a component of many other cooked meat and vegetable dishes (Sensoy et al., 2011). Leafy vegetables are an important part in the human diet and spinach is one of the dark green leafy vegetables which contains high beta carotene and folate, and is also a good source of vitamin C, calcium, iron phosphorous, sodium and potassium (Dicoteau, 2000; Avsar, 2011). Spinach as dioecious specie with both male and female plants is an herbaceous leafy vegetable in the family of Amaranthaceae (Salk et al., 2008) and its leaves are alternate, simple, from ovate to triangular-based, with larger leaves at the base of the plant and small leaves higher on the flowering stem (Vural et al., 2000). Today, China, the United States, Indonesia, Japan and Turkey are among the largest commercial producers of spinach (FAO, 2011). Iran is the one of the spinach producers with about 105 thousand tons per year based on FAO statistics. The average yield of spinach in Iran is 2096 kg ha-1 while world's average yield is 2420 kg ha-1 (FAO, 2011). Also, the average yield of spinach in China is 2768 kg ha-1, in the United States is 2360 kg ha-1, Indonesia is 3424 kg ha-1, Japan is 12471 kg ha-1, and Turkey is 9249 kg ha-1 (FAO, 2011). Spinach is native to southwest Asia and commonly thought to have originated in Iran (Nonnicke, 1989; Swiader and Ware, 2002) and was first mentioned by the Chinese as the herb of Persia. It was first cultivated in North Africa, came to northern Europe by way of Spain, documented in Germany and then was a common garden vegetable by 1500 in England and France (Dicoteau, 2000; Swiader and Ware, 2002) Although, hybrids cultivars of spinach were introduced in the 1950's and they have become the major type of spinach cultivars (Morelock and Correll, 2008), but Iranian farmers currently use native spinach landraces, which have good adaptability to different local conditions. The yield performance of these landraces is very low (typically about 2000 kg ha-1) compared with the highest global yields (12471 kg ha-1, produced in Japan; FAO 2011). Therefore, it is essential for Iran to has had spinach breeding program for increasing the genetic potential of yield as well as other important traits. Since Iran is a centre of genetic diversity of many cultivated plants, including wheat, alfalfa, spinach and etc, it is essential to conserve these important resources. Most of the spinach accessions are landraces which are highly adapted to specific environmental conditions and are useful sources of genetic variation (Asadi and Hasandokht, 2007). However, utilization of the genetic potential of different germplasms needs detailed knowledge about these genetic collections (Morelock and Correll, 2008), including characterization, evaluation and classification. Multivariate procedures are useful for characterization, evaluation and classification of germplasm collections when a large number of accessions are to be assessed for several traits. The usefulness of multivariate procedures for handling morphological variation in plant genetic resources has been proved in many crops; wheat (Damania et al., 1996; Sorghum (Ayana and Bekele, 1999). The generated information of multivariate procedures can be useful for identifying different accessions that have explained traits for crossing, for planning efficient plant improvement program. Also, it is possible to establish core collections for revealing the structure of variation in plant genetic resources and for investigating some aspects of crop evolution (Perry and McIntosh, 1991; Ayana and Bekele, 1999). Some investigations have been performed in the past on Iranian spinach germplasm collections, but most of them studies are limited with either using only univariate statistics or studying samples from a limited geographical range (Benedictos, 1999; Asadi and Hasandokht, 2007; Eftekhari et al., 2010). The objective of this investigation was to determine the structure of distribution of morphological variation for 10 quantitative traits and 9 qualitative traits in 54 accessions of native Iranian spinach germplasm collections sampled from a wide geographical range of Iran and identify groups of accessions with similar quantitative traits. 2 MATERIALS AND METHODS 2.1 Trial protocol Fifty-four native Iranian spinach germplasm collections were collected as seed in Iran, and then evaluated in the field in a randomized complete block design (RCBD) replicated four times. Each spinach germplasm was collected as seed multiplied by the farmers. The geographical properties of the 54 sites of the collected spinach landraces are given in Table 1. Field soil was calcareous, loamy structure, low organic matter, and low salt content. Also, it had poor nitrogen and phosphorous and adequate potassium. Fertilization was carried out by spreading 80 kg N ha-1 (half of N at sowing stage and half of N at seedling emergence). Sowing was done manually at the rate of 50 kg seed ha-1. Each plot contained six 3 m long rows with 25 cm between rows and plot size was 4.5 m2. Control by hand weeding was carried out twice when the weed density was high, in the pre-flowering and post-flowering stages. The harvested plot size was 2.5 m2 (four 2.5 m rows at the center of each plot). Several quantitative traits consist on leaf length (LL), leaf width (LW), petiole length (PL), petiole diameter (PD), leaf area (LA), leaf numbers in flowering (LN), days to flowering (DF), female plants percent (FP), fresh yield (FY) and dry yield (DY) were measured. Also, various qualitative traits consist on leaf texture (LT, 1=smooth, 2=slight crinkled, 3= crinkled), seed type (ST, 1=smooth, 2=prickly), stem anthocyanin (SA, 1=very low, 3=low, 5 intermediate, 7=high, 9=very high), petiole attitude (PA, 1=erect, 2=semi-spared, 3= spared), vegetative leaf shape (VL, 1=elliptic, 2=broad elliptic, 3=circular, 4=ovate, 5=broad ovate, 6=triangular), reproductive leaf shape (RL, 1=smooth, 2=pointy); leaf edge (LE, 1=smooth, 2= rippler); leaf color (LC, 1=yellow-green, 2=grey-green, 3=blue-green); seed color (SC, 1=yellow-green, 2=grey-green, 3=blue-green) were measured. 2.2 Statistical analysis The datasets were first tested for normality by Anderson and Darling normality test using MINITAB version 16 (2010) statistical software. Analysis of variance was performed to evaluate differences among measured quantitative traits and the accessions were compared by LSD (least significant differences) criteria. The factor analysis (Cattell, 1965), which consisted of the reduction of a large number of correlated variables to a much smaller number of groups of variables called factors. After extraction, the matrix of factor loading was submitted to a varimax orthogonal rotation, as applied by Kaiser (1958). The array of communality, the amount of variance of a variable accounted by the common factors together, was estimated by the highest correlation coefficient in each array as suggested by Seiller and Stafford (1985). The 54 spinach accessions were clustered using the SPSS 16 (SPSS, 2008), which grouped the accessions into different clusters. The measure of dissimilarity was Euclidean distance and the clustering method was un-weighted pair group method using centroids or UPGMC (Sneath and Sokal, 1973). The number of clusters was determined using multivariate ANOVA via Wilks' lambda statistics. Table 1: Geographical properties of the 54 locations where spinach landraces are collected No. Name Longitude Latitude Altitude (meter) No. Name Longitude Latitude Altitude (meter) 1 Arak 49 ' 41 ' E 34 05 ' N 1755 28 Qum 50 ' 53 ' E 34 38 ' N 930 2 Ardestan 52 ' 22 ' E 33 23 ' N 1205 29 Gochan 58 ' 30 ' E 37 06 ' N 1240 3 Urmia 45 ' 04 ' E 37 33 ' N 1340 30 Kashan 51 ' 27 ' E 33 59 ' N 950 4 Esfahan 1 52 ' 02 ' E 32 32 ' N 1525 31 Karaj 1 50 ' 97 ' E 35 82 ' N 1300 5 Esfahan 2 51 ' 35 ' E 33 10 ' N 1570 32 Karaj 2 50 ' 85 ' E 35 80 ' N 1350 6 Bojnord 57 ' 19 ' E 37 28 ' N 1070 33 Karaj 3 50 ' 87 ' E 35 86 ' N 1230 7 Brojerd 48 ' 45 ' E 33 53 ' N 1580 34 Kerman 57 ' 05 ' E 30 17 ' N 1775 8 Beenab 46 ' 05 ' E 37 53 ' N 1290 35 Kermanshah 47 ' 65 ' E 34 31 ' N 1400 9 Birjand 59 ' 21 ' E 32 87 ' N 1491 36 Lahijan 1 50 ' 14 ' E 37 26 ' N -11 10 Tabriz 46 ' 18 ' E 38 04 ' N 1366 37 Lahijan 2 50 ' 11 ' E 37 16 ' N -10 11 Chamkahriz 51 ' 18 ' E 32 18 ' N 1685 38 Langrood 50 ' 14 ' E 37 19 ' N -25 12 Khoramabad 48 ' 21 ' E 33 29 ' N 1200 39 Mako 44 ' 55 ' E 39 28 ' N 1182 13 Drood 48 ' 70 ' E 33 40 ' N 1326 40 Mobarake 51 ' 30 ' E 32 21 ' N 1900 14 Rahimabad 51 ' 57 ' E 32 28 ' N 1550 41 Maragheh 1 46 ' 16 ' E 37 21 ' N 1477 15 Rahnan 1 51 ' 36 ' E 32 41 ' N 1545 42 Maragheh 2 46 ' 20 ' E 37 24 ' N 1485 16 Rahnan 2 51 ' 40 ' E 32 42 ' N 1525 43 Mashahad 59 ' 36 ' E 36 18 ' N 979 17 Zabol 61 ' 29 ' E 31 01 ' N 475 44 Malekan 1 46 ' 06 ' E 37 08 ' N 1302 18 Zanjan 48 ' 40 ' E 36 40 ' N 1650 45 Malekan 2 46 ' 09 ' E 37 03 ' N 1291 19 Saveh 50 ' 05 ' E 35 10 ' N 998 46 Minandab 46 ' 06 ' E 36 57 ' N 1314 20 Salmas 44 ' 76 ' E 36 19 ' N 1398 47 Mianeh 47 ' 72 ' E 37 41 ' N 1100 21 Sanandaj 46 ' 89 ' E 35 31 ' N 1518 48 Hamadan 48 ' 31 ' E 34 48 ' N 1850 22 Sirjan 55 ' 40 ' E 29 27 ' N 1735 49 Varamin 1 51 ' 39 ' E 35 19 ' N 915 23 Shiraz 1 52 ' 22 ' E 29 37 ' N 1540 50 Varamin 2 51 ' 38 ' E 35 11 ' N 911 24 Shiraz 2 52 ' 12 ' E 29 17 ' N 1320 51 Varamin 3 51 ' 28 ' E 35 19 ' N 923 25 Shirvan 57 ' 92 ' E 37 40 ' N 1492 52 Varamin 4 51 ' 38 ' E 35 23 ' N 918 26 Salehabad 50 ' 57 ' E 34 31 ' N 970 53 Varamin 5 51 ' 35 ' E 35 19 ' N 905 27 Ajabsher 45 ' 55 ' E 37 28 ' N 1330 54 Yazd 54 ' 21 ' E 31 53 ' N 1215 3 RESULTS AND DISCUSSION All of the quantitative dataset was normal according to Anderson and Darling normality test, and so no transformation was applied for traits (data not shown). Some descriptive statistics including minimum value, maximum value, arithmetic mean and coefficient of variation (CV) for all measured traits (variables) of 54 spinach genotypes are presented in Table 2. For example, the minimum amount of fresh yield was 5949.60 kg ha"1, the maximum amount of fresh yield was 44957.00 kg ha"1 and the average fresh yield of studied genotypes was 22151.82 kg ha"1. The maximum leaf length was 15.98 cm; the minimum leaf length was 5.87 cm and the average leaf length was 10.16 cm. The maximum, minimum and average leaf numbers at flowering time were 24, 12 and 16.93, respectively. The maximum percent of female plants was 84 %, the minimum percent of female plants was 20 %, and the average percent of female plants was 54.88 %. Such information can be derived for the other traits from Table 2. Regarding CV values which ranges from 6 (in days to flowering) to 40 % (in fresh yield) in quantitative traits and ranges from 32 (in leaf edge) to 46 % (in vegetative leaf shape) in quantitative traits, indicates remarkable variation among 54 spinach landraces (Table 2). The results of factor analysis are given in Table 3. When fitting the factor analysis model, the first three factors explained 76.8 % of variation for spinach landraces. The first factor extracted can be regarded as a leaf property vector (Table 3). It has high loadings for five traits as leaf length, leaf width, petiole length, leaf area and leaf numbers in flowering, which all of them were the related to leaf characteristics. This factor accounted for 50.6 % of the total variation in spinach landraces data set. The extracted second factor could be named as yield vector and accounted for 15.4 % of the total data variability. It has high loadings for days to flowering, petiole diameter, fresh yield and dry yield traits, which petiole diameter, fresh yield and dry yield were the related to yield performance. The third factor is a female plants percent vector (Table 3) which shows this trait had high loadings in this factor and accounted for 10.7 % of the total data variability. It seems that leaf property vector as the most important factor and yield vector are more influent characteristics among nine measured quantitative traits. Table 2: Descriptive statistics of the measured traits in 54 spinach landraces Traits Max. Min. Average CV Leaf length (cm) 15.98 5.87 10.16 0.17 Leaf width (cm) 10.50 2.61 6.31 0.24 Petiole length (cm) 13.3 4 8.40 0.22 Petiole diameter (mm) 14.6 6 10.62 0.15 Leaf area (cm2) 118.8 11.2 53.88 0.36 Leaf numbers in flowering 24 12 16.93 0.14 Days to flowering 183 137 162.36 0.06 Female plants percent 84 20 54.88 0.20 Fresh yield (kg ha-1) 44957.00 5949.60 22151.82 0.40 Dry yield (kg ha-1) 4286.90 526.00 2161.66 0.38 Leaf texture 3 1 1.74 0.43 Seed type 2 1 1.24 0.35 Stem anthocyanin content 9 1 1.52 0.46 Petiole attitude 3 1 1.85 0.37 Vegetative leaf shape 6 1 1.65 0.46 Reproductive leaf shape 2 1 2.31 0.44 Leaf edge 2 1 1.57 0.32 Leaf color 3 1 2.02 0.39 Seed color 3 1 2.39 0.45 LT, Leaf texture (1=smooth, 2=slight crinkled, 3= crinkled); Seed type (1=smooth, 2=prickly); SA, Stem anthocyanin (1=very low, 3=low, 5=intermediate, 7=high, 9=very high); PA, Petiole attitude (1=erect, 2=semi-spared, 3= spared); VL, Vegetative leaf shape (1=elliptic, 2=broad elliptic, 3=circular, 4=ovate, 5=broad ovate, 6=triangular); RL, Reproductive leaf shape (1=smooth, 2=Pointy); LE, Leaf edge (1=smooth, 2= Rippler); LC, Leaf color (1=yellow-green, 2=grey-green, 3=blue-green); SC, Seed color (1=yellow-green, 2=grey-green, 3=blue-green). Table 3: Factor components loadings of quantitative traits obtained from 54 spinach landraces. F1 F2 F3 Leaf length (cm) 0.66 0.40 0.27 Leaf width (cm) 0.92 0.11 0.04 Petiole length (cm) 0.86 0.12 -0.08 Petiole diameter (mm) 0.21 0.78 0.10 Leaf area (cm2) 0.89 0.29 0.13 Leaf numbers in flowering 0.63 0.41 -0.11 Days to flowering 0.07 0.66 0.12 Female plants percent 0.04 0.03 0.97 Fresh yield (kg ha-1) 0.33 0.90 -0.08 Dry yield (kg ha-1) 0.27 0.92 -0.11 Eigen value 5.1 1.5 1.1 % Variance 50.6 15.4 10.7 % Cumulative variance 50.6 66.0 76.8 To better understand the relationships among the quantitative traits of spinach landraces, the relationships are graphically displayed in a plot of factor 1 and factor 2 (Fig. 1). In this plot, the first factor axis mainly distinguishes the methods of leaf width from the other quantitative traits. The second factor axis separates leaf length and petiole length from the other remained quantitative traits (Fig. 1). Therefore, regarding two factors' loading scores, nine measured quantitative traits could be divided into three groups: leaf width as the first group, leaf length and petiole length as the second group, and petiole diameter, leaf area, leaf numbers in flowering, days to flowering, female plants percent, fresh yield and dry yield. Cluster analysis is a tool for classifying objects into groups. Agglomerative hierarchical clustering methods use the elements of a proximity matrix to generate a tree diagram or dendrogram. The dendrogram generated from genotypes distance matrices showed to clearly group them (Fig. 2). In a distance linkage of 800, the examined 54 spinach landraces could be agglomerated into sixteen clusters. The number of clusters was verified by multivariate analysis of variance test through Wilks' Lambda statistics (data not shown). The related spinach landraces of each sixteen clusters and their qualitative traits are given in Table 4. Some spinach landraces such as G10 G13, G38 and G41 were individual cluster and were not similar to the other collected genotypes while some of the spinach landraces were similar to each other and grouped as one cluster such as cluster 9 (C9) which consist on G17, G12, G23, G37, G28, G34, G36, G40, and G48. Figure 1: Plot of two first factor analysis of nine traits for the 54 spinach genotypes. LL, Leaf length (cm); LW, Leaf width (cm); PL, Petiole length (cm); PD, Petiole diameter (mm); LA, Leaf area (cm2); LN, Leaf numbers in flowering; DF, Days to flowering; FP, Female plants percent; FY, Fresh yield (kg ha-1); DY, Dry yield (kg ha-1). Figure 2: Hierarchical cluster analysis of the 54 spinach genotypes based on Ward's method using measured traits. The mean and LSD (least significant differences) values of the quantitative traits of sixteen clusters are given in Table 5. The highest leaf length (LL) was belong to cluster C7 (12.57 cm) and the lowest LL was belong to cluster C2 (6.78 cm); and it is clear that, there are good variations in length of spinach landraces. According to the LSD values, sixteen clusters could be divided to six distinct groups based on leaf length. Larger leaves are found at the base of the plant and small leaves are found higher on the flowering stem (LeStrange et al., 1999; Avsar, 2011). The cluster C14 had the largest leaf width (8.18 cm) and the cluster C1 had the smallest leaf width (3.76 cm). According to the LSD values of leaf width, sixteen clusters could be divided to five distinct groups. Both leaf length and leaf width are important traits in spinach yield performance (Asadi and Hasandokht, 2007). Due to high variability of these two traits which is observed in studied landraces, it is possible to establish a breeding program to increase leaf yield in spinach. The longest petiole length (PL) was seen in the cluster C11 (9.87 cm), while the shortest PL was seen in the cluster C1 (5.51 cm). The LSD values of petiole length divided the sixteen clusters into three distinct groups. The long petiole length is essential for machinery harvesting and genetic improving for having long petiole length is one of the breeding targets of spinach (Eftekhari et al., 2010). Also, the relative length of petiole is a commercial factor for the producing of spinach canner. The most petiole diameter (PD) as 12.81 mm was observed in the cluster C15 and the low PD as 7.5 mm was observed in the cluster C2 (Table 5). There are not any general correlations among petiole length and petiole diameter, but plants that produce the largest petioles also produce in general the thickest (Pandey and Kalloo, 1993; Avsar, 2011). The largest leaf area (LA) was belong to cluster C14 (76 cm2) and the smallest LA was belong to cluster C1 (24.06 cm2). The largest size of leaf area produces the longest leaf length both in absolute length and relative to petiole length, and conversely, the shortest petioles. This would seem to show that the most of petiole length growth was made relatively in early stages, when conditions favorable for growth occurred; growth in leaf length was more rapid than growth in petiole length. The cluster C14 had the most leaf numbers in flowering time (20 leaf) while the cluster C5 had the lowest leaf numbers in flowering time (12.33 leaf). Harvest of spinach plants of marketable size is depending on leaf number and it is correlated with the length of growing period. Spinach is mainly grown for fresh leaves and both the number of leaves and leaf area determine yield performance. However, a high variance was observed for number of leaf in this study which depicted a broad base of the studied landraces for these traits. This maximizes the scope of selection for these traits in the germplasm assayed. Also, the different environmental conditions influences on leaf numbers production and it seem that leaf production per day to be highest under long-day and moderate temperature conditions (Pandey and Kalloo, 1993). The early flowering cluster was C4 with 146.67 days to flowering and the late flowering clusters were C7 and C8 with 171 days to flowering (Table 5). The higest percent of female plants (64.67%) was seen in cluster C8 and the lowest percent of female plants (46%) was seen in cluster C4. The high fresh yielding landrace was cluster C16 (36429.50 kg ha-1) and the low fresh yielding landrace was cluster C1 (7452.34 kg ha-1). The LSD values of fresh yield divided the sixteen clusters into nine distinct groups. Finally, the high dry yielding landrace was cluster C15 (3405.66 kg ha-1) and the low dry yielding landrace was cluster C1 (727.97 kg ha-1). The LSD values of dry yield divided the sixteen clusters into six distinct groups. It seems that there are remarkable variation in both fresh and dry yield of 54 spinach landraces and these genotypes could be used for increasing yield in future spinach improvement programs. Regarding all quantitative traits, it seems that cluster C14 which contain only landrace Karaj 2 was the most favorable genotype due to good performance for most measured quantitative traits. Its leaf texture was smooth and so could accumulate low amounts of nitrate, and it had low amounts of anthocyanin (Table 4). Petiole shapeof landrace Karaj 2 is semi-spared and regarding the long petiole length simply could be used for machinery harvest. This landrace has many of good characteristics for proper performance and could be recommended for commercial release after complementary experiments. The finding of such good spinach landrace in this study at Iran as its origin indicates the high potential of native landraces in origin of plants. After cluster C14, cluster C16 which consist on landraces G1 (Arak) and G3 (Urmia) indicate good potential regarding the measured traits. The leaf texture of these landraces was moderate (slight crinkled), and their anthocyanin content was acceptable (low). The leaf color of both Arak and Urmia landraces was grey-green which is suitable for frizzing industries (Table 4). However, these landraces could be used directly as commercial cultivars or introduced in spinach breeding programs due to high potential in most measured qualitative and quantitative characteristics. Clusters C12, C13 and C15 had good performances for some important traits such as dry yield and are useful sources of genetic variation for improving yield performance in spinach. There were landraces G8 (Beenab), G9 (Birjand), G11 (Chamkahriz), G14 (Rahimabad), G15 (Rahnan 1), G16 (Rahnan 2), G22 (Sirjan), G50 (Varamin 2) in these clusters which are collected from different geographical regions of Iran. It seems that these landraces were variable from other aspects which are not measured in this study. Finally every one of the 54 spinach landraces which is used in this investigation maybe had at least one important trait resource and could be enter to different spinach breeding program based on the breeder target(s). Spinach is a very important source of nutrients and is dispersed throughout Iran as its origin and all over the world. Plant materials of present investigation were chosen because there are not many studies on spinach especially on landraces. A total of 54 spinach landraces were collected from different geographical regions of Iran which provided morphological data for the landraces. The dendrogram of cluster analysis for the dataset showed 16 groups. Multivariate PCA analysis of morphological data was performed for 3 parameters and the analysis showed good separation of the quantitative traits on the plot based on first two PC. This investigation provided suitable information that may be useful to plant breeders who wish to find the most distinct spinach landraces. For germplasm collections, the results of present investigation may aid to conserve more distinct accessions and to eliminate similar accessions to preparing proper spinach gene-bank in Iran. In future studies, a plant breeder may select two distinct accessions and hybridize them to create a new generation and to obtain one or more new cultivars with favorable characteristics such as resistance to biotic and abiotic stresses. In conclusion, it was seen that characterization of spinach landraces based on the morphological traits was suitable to assess the genetic diversity among collected spinach landraces. Results of this investigation also can aid to define strategies for further collection. Since our results show that the pattern of observed variation is governed by morphological traits, future germplasm collections should aim to investigate genetic variation via different molecular markers. Also, it is essential to explore variation using more landraces which are collected geographically and climatically from different regions, instead of collecting extensively within individual regions. However, a high variability was observed for most measured traits and obtaining more diverse collections especially exotic germplasm is not needed for future breeding in spinach. Table 4: The genotypes of 16 clusters and their qualitative characteristics Class Landraces LT ST SA PA VL RL LE LC SC C1 G5, G20 2 1 5 2 4 1 1 2 2 C2 G38 1 1 1 3 6 2 2 2 3 C3 G41 3 1 7 2 3 1 1 3 3 C4 G10 3 1 3 1 2 1 2 3 1 C5 G13 1 1 1 2 5 1 2 2 2 C6 G53, G33, G26, G45, G43, G7 2 1 5, 7 2 2,3 1 2 3 3 C7 G24 2 1 7 2 1 1 1 3 3 C8 G4 1 1 9 2 2 1 2 1 2 C9 G37, G40, G36, G48, G28, G23, 1 , 3,5, 1, 3 1, 2 2, 2 G34, G17, G12 1 9 2 3 C10 G49, G44, G42, G51, G52, G54, 2 1, 1, 2, 1, 2 2 2, G35, G27, G47, G18, G19, G6 2 5 3 2 1 3 C11 G29, G21, G46, G39, G30, G31, G25, G2 1, 2 1 7, 1, 2 1 1, 2 1, 2 3 C12 G50, G11, G14, G9 2 2 1 2 1,3 1 2 2 2 C13 G22, G16, G8 1 1 5, 9 2 4 1 1 2 3 C14 G32 1 1 3 2 1 1 1 1 1 C15 G15 1 1 9 3 2 2 1 1 2 C16 G3, G1 2 2 3 2 1 1 1 2 1 LT, Leaf texture (1=smooth, 2=slight crinkled, 3= crinkled); Seed type (1=smooth, 2=prickly); SA, Stem anthocyanin (1=very low, 3=low, 5=intermediate, 7=high, 9=very high); PA, Petiole attitude (1=erect, 2=semi-spared, 3= spared); VL, Vegetative leaf shape (1=elliptic, 2=broad elliptic, 3=circular, 4=ovate, 5=broad ovate, 6=triangular); RL, Reproductive leaf shape (1=smooth, 2=pointy); LE, Leaf edge (1=smooth, 2= rippler); LC, Leaf color (1=yellow-green, 2=grey-green, 3=blue-green); SC, Seed color (1=yellow-green, 2=grey-green, 3=blue-green). Table 5: The quantitative characteristics of 16 clusters of spinach landraces Class LL LW PL PD LA LN DF FP FY DY C1 7.20 3.76 5.51 8.67 24.06 14.33 150.50 53.17 7452.34 727.97 C2 6.78 4.64 8.05 7.50 31.67 16.67 162.00 53.33 9158.45 973.10 C3 10.73 5.54 7.63 10.63 47.84 18.33 147.67 59.67 10787.81 1109.33 C4 8.89 4.94 7.13 10.43 38.59 14.00 146.67 46.00 15783.36 1534.02 C5 8.08 5.78 7.05 9.50 35.17 12.33 169.33 52.33 14811.47 1546.44 C6 10.01 5.66 7.95 10.07 47.75 15.83 152.72 54.50 13111.50 1365.14 C7 12.57 6.57 8.30 12.57 69.97 17.33 171.00 62.33 28633.95 2729.43 C8 12.50 6.08 8.77 12.77 68.93 18.00 171.00 64.67 27509.96 2669.30 C9 10.64 7.02 8.93 10.51 58.65 17.37 165.27 55.93 23377.59 2302.94 C10 9.98 6.24 8.20 10.37 52.58 16.58 160.94 53.71 20891.73 2057.99 C11 10.54 7.58 9.87 9.97 61.37 16.83 168.00 64.67 24355.39 2131.18 C12 10.45 6.86 9.51 11.67 58.17 19.33 170.33 48.78 33168.25 3240.43 C13 10.90 6.32 9.39 12.20 59.79 18.00 169.56 57.89 31702.52 3103.02 C14 10.63 8.18 9.79 11.81 76.00 20.00 166.00 46.33 35384.93 3167.40 C15 11.01 6.12 9.01 12.81 60.31 17.00 170.67 61.33 34545.36 3405.66 C16 10.88 7.05 7.83 12.29 68.36 19.50 170.17 54.50 36429.54 3291.19 LSD 0.88 0.86 1.03 0.79 11.00 1.34 5.56 7.05 3395.16 314.65 LL, Leaf length (cm); LW, Leaf width (cm); PL, Petiole length (cm); PD, Petiole diameter (mm); LA, Leaf area (cm2); LN, Leaf numbers in flowering; DF, Days to flowering; FP, Female plants percent; FY, Fresh yield (kg ha-1); DY, Dry yield (kg ha-1). 4 REFERENCES Asadi HA, Hasandokht MR (2007) An evaluation of genetic diversity of Iranian spinach landraces. 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SPSS Inc., 2008. SPSS 16 for Windows, SPSS User's guide. SPSS Inc, Chicago, IL. USA. (http://www.spss.com). Swiader JM, Ware GW (2002) Producing Vegetable Crops 5th ed. 481-498 Interstate. Vural H, Esiyok, D, Duman I (2000) Vegetable Production. Bornova, Izmir, Turkey: Aegean University Press. 440 p. COBISS Code 1.01 DOI: 10.14720/aas.2014.103.1.12 Agrovoc descriptors: lens culinaris, lentils, statistical methods, methods, genotypes, environment, crop yield, arid zones, semiarid zones Agris category code: f30 Graphic analysis of yield stability in new improved lentil (Lens culinaris Medik.) genotypes using nonparametric statistics Naser SABAGHNIA1*, Rahmatollah KARIMIZADEH2, Mohtasham MOHAMMADI2 Received November 16, 2012; accepted Janury 25, 2014. Delo je prispelo 16. novembra 2012, sprejeto 25. januaija 2014. ABSTRACT IZVLEČEK Yield stability is an interesting feature of today's lentil breeding programs, due to the high annual variation in mean yield, particularly in the arid and semi-arid areas. The genetic effects including genetic main and genotype x environment (GE) interaction effects for grain yield of eighteen lentil (Lens culinaris Medik.) genotypes were studied with fourteen nonparametric stability statistics. Results of five distinct nonparametric tests of GE interaction and combined ANOVA showed there were both additive and crossover interaction types and genotypes varied significantly for grain yield. According to most of the nonparametric stability statistics, genotypes G5, G6, G8 and G18 were the most stable genotypes. Considering mean yield versus stability values via their plotting, indicates that genotypes G2, G11 and G14 following to G5, G16 and G18 were the most favorable genotypes. None of the nonparametric stability statistics were correlated with mean yield and so had static concept of stability. Our results confirmed that rankings of genotypes within environments and using mean yield information permit ease of interpretation of nonparametric results. Finally genotypes G2 (FLIP 92-12L), G11 (Gachsaran) and G14 (ILL 6206) were found to be the most stable and high mean yielding genotype and thus recommended for commercial release. Such an outcome could be used to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts for lentil and other crops. Key words: adaptability, dynamic stability, genotype x environment interaction GRAFIČNA ANALIZA STABILNOSTI PRIDELKA NOVIH IZBOLJŠANIH GENOTIPOV LEČE (Lens culinaris Medik.) Z UPORABO NEPARAMETRIČNE STATISTIKE Stabilnost pridelka je zaradi velikih letnih nihanj, še posebej v aridnih in semi-aridnih območjih, zanimiva lastnost v današnjih žlahtniteljskih programih pri leči (Lens culinaris Medik.). Pri 18 genotipih leče smo s 14 neparametričnimi statističnimi testi, ki vrednotijo stabilnost pridelka, preučevali glavne vplive genotipa in interakcije med genotipom in okoljem (GO) na pridelek zrnja. Rezultati petih neparametričnih testov GO interakcij, ter parametrične ANOVA so pokazali, da so se genotipi značilno razlikovali v pridelku zrnja tako v povezanjih kot prekrižanih interakcijah. Gleda na večino neparametričnih testov stabilnosti pridelka so se genotipi G5, G6, G8 in G18 izkazali kot najbolj stabilni. Primerjava povprečnih pridelkov in stabilnosti je pokazala, da so genotipi G2, G11, G14 in G5, G16 ter G18 najbolj primerni. Nobeden izmed neparametričnih testov stabilnosti ni koreliral s povprečnim pridelkom, kar kaže na njihov statičen značaj. Naši rezultati potrjujejo, da rangiranje genotipov po povprečnem pridelku za vsake okoljske razmere posebej omogoča uporabo rezultatov neparametričnih testov. Na koncu so bili genotipi G2 (FLIP 92-12L), G11 (Gachsaran) in G14 (ILL 6206) prepoznani kot najbolj stabilni, z velikim povprečnim pridelkom in priporočeni za komercialno uporabo. Takšni izsledki bi lahko bili uporabljeni za ponazoritev napovedovanj in resnejših priporočil kot tudi pomoč pri določanju stabilnost pridelave leče in drugih poljščin. Ključne besede: prilagodljivost, dinamična stabilnost, interakcije med genotipom in okoljem 1 Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Maragheh, Maragheh, Iran. 'Corresponds to: sabaghnia@maragheh. ac.ir 2 Dryland Agricultural Research Institute (DARI), Gachsaran, Iran 1 INTRODUCTION Iran is one of the foremost countries in terms of lentil (Lens culinaris Medik.) production and sowing area in the world, and is followed by Canada, Turkey and India. Although, the lentil is the second grain legume crop after the chickpea in Iran but its average yield (489 kg ha"1) is not acceptable for many local farmers (Sabaghnia et al., 2008). According to the latest statistics from The Food and Agricultural Organization of the United Nations, 162000 ha were used for lentil production and 79000 t of production were obtained in 2000 (FAOSTAT, 2010). This low yield performance of the cultivated lentil cultivars in comparison to the highest global yields (14580 kg ha"1, produced in Canada; FAOSTAT, 2010), encouraged Dryland Agricultural Research Institute (DARI) of Iran for performing an important lentil"breeding program in recent years, supported by the International Center for Agricultural Research in Dry Areas (ICARDA). Like to the other crops, increasing the potential of yield is an important target of lentil breeding programs. The new improved genotypes are evaluated in multi"environment trials to test their performance across different environmental conditions. In most trials, crop yield fluctuates due to suitability of genotypes to different conditions which is known as genotype x environment (GE) interaction (Kang, 1998). In presence of GE interaction, a genotype does not exhibit the same phenotypic characteristics under test environments and various genotypes respond differently to a specific environment. GE interaction exploration and yield stability is an area of current interest and the success of plant breeding efforts depend on the identification of superior genotypes from stability and yield aspects. Exploring, measurement and interpretation of GE interaction can be aided by different statistical modeling and a number of statistics, parametric as well as nonparametric have been proposed for the study of yield stability (Huehn, 1996). These statistical models can be linear formulations (Eberhart and Russell, 1966), multiplicative formulations such as additive main effects and multiplicative interaction (Zobel et al., 1988), or nonparametric procedures (Huehn, 1979). The use of nonparametric statistics in the assessment of yield stability had several benefits. In this approach, no assumptions about the observations are needed and there is less sensitivity to measurement errors or to outliers (Huehn, 1990a). Also, additions or deletions a few genotypes do not cause distortions and these statistics are useful in situations where parametric statistics fail due to the presence of large non" linear GE interaction (Huehn, 1990b). In most cases the plant breeder is concerned with non" additive (crossover) GE interaction and so yield stability measuring based on rank-information, seems more relevant and usefulness. Therefore, the nonparametric statistics are widely used in the selection of favorable genotypes especially when the interest lies in crossover GE interaction (Nassar and Huehn, 1987; Huehn, 1996; Mut etal., 2009). Although, it is demonstrated that the nonparametric procedures are less powerful than their parametric methods but Raiger and Prabhakaran (2000) have shown that when the number of genotypes is large, the power efficiency of the nonparametric statistics will be quite close to the parametric statistics. According to both GE interaction types, additive (non-crossover) and crossover (non-additive), several nonparametric tests based on ranks were proposed by different authors. These methods of Bredenkamp (1974), Hildebrand (1980) and Kubinger (1986) for testing of additive GE interaction and methods of de Kroon and van der Laan (1981) and, Azzalini and Cox (1984) for testing of crossover GE interaction were introduced. Also, several nonparametric stability statistics proposed by Huehn (1979), Kang (1988), Ketata et al. (1989), Fox et al. (1990), and Thennarasu (1995) which are identifying genotypes with similar ranking across environments as the most stable genotypes. Nassar and Huehn (1987) developed two distinct statistical tests as Z1 and Z2 for the two first nonparametric stability statistics of Huehn (1979) which known as ' and ! . The objectives of present study were to (1) test presence of GE interaction through different nonparametric tests, (2) interpret GE interaction via ranks obtained by nonparametric stability statistics of 18 lentil genotypes over twelve environments, (3) visually assess how to vary rank statistics versus yield performances based on the plot, (4) determine promising favorable genotype(s) with high mean yielding and good stability, and (5) investigate interrelationships among different nonparametric stability statistics in lentil dataset. 2 MATERIALS AND METHODS 2.1 Plant Material and Field Conditions The study included 18 lentil genotypes (16 new improved lines and 2 cultivars) that were grown in 4 different locations under rainfed conditions during the 2007-2009 growing seasons. The names of studied lentil genotypes are given in Table 1. Table 1. Geographical properties and mean yield of the 18 lentil genotypes, studied in 4 locations Code Location Altitude Longitude (meter) Latitude 55! ■■' 12! ■■■ E 37! ■■' 16! ■■■ N 47! ■■' 19! ■■■ E 34! ■■■ 20 ! ■■■ N 50! ■■■ 50 ! ■■■ E 30! ■■■ 20 ! ■■■ N 58! ■■■ 07 ! ■■■ E 37 ■■' 19! ■■■ N Soil Texture Rainfall Yield (mm) (kg ha"1) Gorgan Kermanshah Gachsaran Shirvan 45 1351 710 1131 Silty Clay Loam 367 767 Clay Loam 455 1923 Silty Clay Loam 460 1747 Loam 267 384 All trials were arranged in accordance with a randomized complete block design with 4 replicates. The experimental plots consisted of 4 rows, each 4 m in length with 25 cm row spacing. The planted plot size was 4 m2 and the harvested plot size was about two 3.5 m rows with 1.75 m2. All trials were fertilized with 20 kg of N ha-1 and 80 kg of P2O5 during sowing stage. Weeds were controlled by hand twice in the high weed density (pre-flowering and post-flowering stages). The test locations (Gorgan, Gachsaran, Kermanshah and Shirvan) were selected as sample of lentil growing areas of Iran and to vary in latitude, rainfall, soil types, temperature and other agro-climatic factors. Gorgan in the north-east of Iran is characterized by semi-arid conditions with sandy loam soil. Gachsaran, in southern Iran, is relatively arid and has silt loam soil. Kermanshah in the west of Iran is characterized by semi-arid conditions with clay loam soil. Gachsaran, in southern Iran, is relatively arid and has silt loam soil. Shirvan in the north-east of Iran is characterized by moderate conditions, relatively high rainfall and have clay loam soil. Some of the important properties and the location of the experimental environments are given in Table 2. Table 2: The name and yield (kg ha -) of 18 lentil genotypes studied in multi-environmental trials Code Name Type Yield Code Name Type Yield G1 G2 G3 G4 G5 G6 G7 G8 G9 FLIP 96-7L FLIP 92-12L FLIP 96-13L FLIP 96-8L FLIP 96-4L FLIP 96-14L ILL 5583 FLIP 96-9L ILL 6002 Line Line Line Line Line Line Line Line Line 1418.73 1365.64 1287.29 1272.07 1324.46 1096.53 1304.15 1191.14 1329.48 G10 G11 G12 G13 G14 G15 G16 G17 G18 ILL 6030 Gachsaran ILL 7523 ILL 6468 ILL 6206 ILL 62-12 FLIP 82-1L CABRALIA FLIP 92-15L Line Cultivar Line Line Line Line Line Cultivar Line 1187.98 1374.14 1334.75 1292.16 1401.88 1307.35 1272.40 1203.28 1314.63 2.2 Nonparametric Statistical Methods Conventional combined analysis of variance as well as nonparametric tests for presence of GE interaction was done. Three nonparametric tests including Bredenkamp (1974), Hildebrand (1980) and Kubinger (1986) procedures were applied for additive GE interaction and two nonparametric tests including de Kroon and van der Laan (1981) and Azzalini and Cox (1984) procedures were applied for crossover GE interaction. These nonparametric tests have been described in detail by Huehn and Leon (1995) and Truberg and Huehn (2000). For computing of the above mentioned statistics, a SAS-based computer program was used. Huehn (1979) developed six nonparametric stability statistics, which Kang and Pham (1991) and Kaya and Taner (2002) described only four s(1) S(2) S(3) S.6> and ' statistics. The two other nonparametric statistics are expressed as follows: XI r'J - ru\ S,(5) = ^- for k genotypes and n environments, the value of 7th genotype in jth environment is xtj, where i = 1,2,..., k , j = 1,2,..., n, Tj as the rank of the ith genotype in the jth environment, and rj as the mean rank across all environments for the ith genotype. Ketata et al. (1989) proposed plotting mean rank across environments against standard deviation of ranks for all genotypes (or) or plotting mean yield across environments against standard deviation of yields for all genotypes (omy )■ The formula for calculating both standard deviations are expressed as: X (rn -R)2 j=1_ n-1 X (r¡j - r,)2 S(4) =il jL 1 X (rj -x-)2 j=1 n -1 Nonparametric stability statistics as Top, Mid and Low were introduced by Fox et al. (1990) as n n nonparametric superiority measure (NSM) using stratified ranking of the genotypes and their ranking was done at each environment separately and the number of environment at which the genotype occurred in the top, middle, and bottom third of the ranks was computed. Kang's (1988) rank-sum is another nonparametric stability statistics where both mean yield and Shukla's (1972) stability variance are used as selection criteria. Thennarasu (1995) proposed the use of the four nonparametric statistics based on the corrected ranks. In other word, the ranks of genotypes in each environment were determined according adjusted values (x* = xij - xi ). For calculation of these nonparametric stability statistics, SAS-based computer programs of Lu (1995) and Hussein et al. (2000) were used. 3 RESULTS The residuals mean squares were not correlated to environment mean yield (r = 0.12, P > 0.05) thus the data were not transformed. Variances homogeneity test via Bartlett procedure (x2 = 25.1, P < 0.05) showed that the mean squares of individual environments were homogeny and so the combine analysis of variance could be done. Analysis of variance was conducted to determine the effects of year, location, genotype, and their interactions on grain yield of lentil genotypes (Table 3). Table 3: Combined ANOVA of lentil performance trial yield data Source DF Mean Squares Year (Y) 2 8400774ns Location (L) 3 3962077ns YxL 6 ** 4579496 R (YxL) 36 38152 Genotype (G) 17 320003** YxG 34 80769 ns LxG 51 * 134137 YxLxG 102 ** 84021 Error 612 31713 Genotypes and locations were regarded as fixed effects, while years were regarded as random effects. The main effect of Y, L and Y * L were tested against the replication within environment (R/Y*L). The main effect of G was tested against the G * Y * L interaction and the G * Y * L interaction was tested against error term. The main effects of year (Y) and location (L) were not significant (P > 0.05), but their interactions (YL) were highly significant (P < 0.01). The main effect of genotypes was significant (P < 0.01), the genotype * year interaction (GY) was not significant (P > 0.05), the genotype * location interaction (GL) was significant (P > 0.05) and three way interactions (GYL) or GE were highly (P < 0.01) significant (Table 3). The GE interaction, which arising from the lack of genetic correlation among environments, must be used to understand in breeding program. Analyses of the quantitative traits like grain yield indicate important sources of genetic variation attributed to GE interactions (Gauch et al., 2008). The relative large contributions of GE interaction in grain yield of lentil which found in this study is similar to those found in other multi-environmental trials studies of lentil in rain-fed conditions (Mohebodini et al., 2006; Sabaghnia et al., 2008). Table 4: Analysis of GE interaction using different non-parametric tests on 18 durum lentil genotypes grown in 12 environments Nonparametric tests Nonparametric tests df Z2 P-value Additive Bredenkamp 187 894.05 0.00 < Hidebrand 187 364.21 0.00 < Kubinger 187 385.67 0.00 < Crossover de Kroon-van der Laan 187 368.46 0.00 < Azzalini-Cox 187 305.31 0.00 < The results of various nonparametric tests verified the results combined ANOVA. According to chi-squares statistics of Bredenkamp (1974), Hildebrand (1980) and Kubinger (1986) producers, the existence of additive (non-crossover) GE interaction; and based on de Kroon and van der Laan (1981) and Azzalini and Cox (1984) producers, the existence of crossover (nonadditive) GE interaction were demonstrated (Table 4). The high significance of GE interactions for lentil grain yield via combined ANOVA and five nonparametric tests indicated the genotypes exhibited both crossover and non-crossover types of GE interaction. In other word, results of nonparametric tests are in agreement with the ANOVA, but provide more specific information about the nature of GE interactions from additive and crossover aspects. Cooper and Byth (1996) explained that the large magnitude of GE interaction due to the more dissimilarity of the genetic systems controlling the physiological processes conferring adaptation to different environments. The values of the first two nonparametric stability S (!) S (2) statistics of Huehn (1979), ' and ' , indicated that genotype G18, followed by G5 and G11 were the most stable genotypes (Table 5). Nassar and Huehn (1987) and Flores et al. (1998) pointed out that the Sf"1 and S;(2) are associated with the static or biological concept of stability and define stability in the sense of homeostasis. However, the stability property alone is of limited use and for a successful genotype testing program, both stability and mean yield must be considered simultaneously. Graphic analysis of yield ... (Lens culinaris Medik.) genotypes using nonparametric statistics Table 5: Nonparametric stability statistics for grain yield of 18 lentil genotypes evaluated in 12 environments Sf(1) S<2) S<3) S (4) S! (5) s, (6) Top Mid Low RS NP(1) NP(1) NP? NPi(4) jr j my 25.00 16.67 16 5.42 1.806 0.919 0.525 5.67 420.82 33.33 8.33 9 5.21 1.157 0.743 0.385 4.76 401.19 25.00 41.67 21 4.54 0.454 0.527 0.290 4.80 375.57 41.67 33.33 25 4.04 0.385 0.434 0.320 5.33 376.62 66.67 0.00 9 3.96 0.396 0.388 0.259 3.89 391.36 25.00 75.00 22 4.46 0.262 0.282 0.087 2.53 319.74 50.00 25.00 24 4.21 0.411 0.478 0.300 4.90 379.45 33.33 58.33 23 3.71 0.239 0.335 0.179 4.31 345.34 33.33 25.00 24 6.04 0.863 0.615 0.414 5.95 392.23 25.00 58.33 33 5.63 0.388 0.516 0.268 5.83 347.71 58.33 0.00 9 3.63 0.483 0.533 0.339 3.80 399.98 33.33 25.00 13 4.58 0.509 0.506 0.310 4.68 391.93 41.67 33.33 14 3.88 0.456 0.406 0.284 4.60 378.08 50.00 0.00 15 4.88 0.750 0.792 0.330 3.52 415.54 41.67 25.00 19 4.71 0.523 0.534 0.325 5.05 387.68 58.33 16.67 25 3.71 0.371 0.416 0.284 4.75 375.91 8.33 50.00 32 6.96 0.535 0.549 0.333 6.42 358.98 50.00 8.33 9 2.88 0.338 0.435 0.254 3.52 385.67 G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 G13 G14 G15 G16 G17 G18 7.61 6.52 6.18 6.15 4.83 5.92 5.86 6.03 7.45 7.74 5.02 6.56 5.26 6.85 6.08 5.76 7.98 4.53 42.00 31.24 28.09 26.82 16.57 25.36 24.81 25.55 41.18 43.54 18.27 30.45 19.90 34.42 27.66 23.91 49.30 14.81 73.75 44.24 32.99 39.44 23.75 5.58 34.02 18.57 57.60 38.19 29.75 33.77 30.38 26.97 38.11 31.48 51.59 20.64 18.81 15.79 15.90 17.69 12.89 8.38 16.26 14.29 19.74 19.35 12.60 15.52 15.26 11.69 16.75 15.74 21.31 11.67 4.83 4.30 3.99 4.58 3.29 2.00 4.04 3.63 5.03 4.83 3.22 3.92 3.85 2.83 4.29 3.56 5.83 2.92 12.08 9.16 6.24 6.93 5.64 1.90 6.24 3.95 8.93 5.92 7.25 6.59 6.02 6.71 6.99 5.42 7.95 5.30 58.33 58.33 33.33 25.00 33.33 0.00 25.00 8.33 41.67 16.67 41.67 41.67 25.00 50.00 33.33 25.00 41.67 41.67 G!7 <110 * at Oi au oia o: V «« V «11 OH ao * ail C17 oje 91 V 04 ail 01»01 • aii at 0« OS S" ait ou at 419 04 01 cu 014 02 «• ai« V t" sir 01 G. V « <"• «to <34 « «5* at 01» * oti® Figure 1: Plot of the mean yield versus Huehn's (1979) nonparametric stability statistics (A) s^, (B) S^ , (C) s^ (D) sP, (E) S(5) and (F) s<6). Figure 1A represents plot portrayed by mean yield values and s,(1) nonparametric stability statistic. This figure is divided by grand mean yield and average s,(1) values into four sections. Therefore studied lentil genotypes are classified as Group I, with stable low yield characteristics; Group II, with high yield stable genotypes; Group III, with unstable low yield properties; Group IV, with unstable high yielding genotypes (Table 6). Among these groups, only Group II is acceptable for recommending as the most favorable genotypes which are consist on G3, G4, G5, G7, G11, G13, G15, G16 and G18 (Table 6). According to Figure 1A, genotypes G2, G3, G4, G5, G7, G11, G12, G13, G15, G16 and G18 were identified as the most stable genotypes regarding both mean yield and S(2) nonparametric stability statistic. Table 6: Grouping of 18 lentil genotypes based on mean yield and nonparametric stability statistics Group I Group II Group III Group IV sf) G6, G7 Remained genotypes G10, G17 G1, G2, G9, G12, G14 sf G6, G8 Remained genotypes G10, G17 G1, G9, G14 s« G6, G8, G10 Remained genotypes G17 G1, G2, G9 S(4) G6 G5, G11, G14, G18 G8, G10, G17 Remained genotypes S(5) G6, G8 G5, G11, G14, G16, G18 G10, G17 Remained genotypes s^ G6, G8, G10 Remained genotypes G17 G1, G2, G9, G11 NP,(1) G6, G8 Remained genotypes G10, G17 G1, G2, G9 NP (2) G6, G8, G10, G17 Remained genotypes — G1, G2 Np3) G6, G8, G10, G17 Remained genotypes — G1, G2, G9, G14 np(4) G6, G8, G10 G3, G5, G13, G16, G18 G17 Remained genotypes G6, G8 G5, G11, G14, G18 G10, G17 Remained genotypes ^'my G6, G8, G10, G17 — — Remained genotypes RS G5, G12, G13, G18 G2, G11, G14 — G1, G9, G12 NSM G17 Remained genotypes G6, G8, G10 G3, G4, G7, G13, G16 Group I, Stable and low yield; Unstable and high yield Group II, Stable and high yield; Group III, Unstable and low yield; Group IV, According to S( ) and S( ) nonparametric statistics, genotypes G6, G8 and G18 were the most stable genotypes while based on S^ and S i(5) nonparametric statistics, genotypes G6, G14 and G18 were the most stable genotypes (Table 5). Kang and Pham (1991) found that the S(3) and Si(6) nonparametric statistics would be useful tools for selecting simultaneously for yield and yield stability while Ebadi-Segherloo et al. (2008) pointed out that the S(4) and S(5) nonparametric statistics were similar to the Si(1) and Si(2) statistics, and explore GE interaction with the biological concept of stability. Figure 1C showed that all genotypes expect G1, G2, G6, G8, G9, G10 and G17 were the most favorable genotypes based on s,(3) and mean yield. According to Fig. 1D, genotypes G5, G11, G14 and G18 and according to Fig. 1E, genotypes G5, G11, G14, G16 and G18 were identified as the favorable genotypes with high mean yield and stability. Also, Figure 1F indicated that all genotypes expect G1, G2, G6, G8, G9, G10, G11 and G17 were the most favorable genotypes based on S(6) and mean yield. Finally, according to the most of the nonparametric stability statistics of Huehn (1979), genotypes G5, G6 and G18 were the most stable genotypes while based on the related figures and considering mean yield, genotypes G5, G11, G14, G15, G16 and G18 were the most favorable genotypes. It seems that using graphic presentation of the nonparametric statistics of Huehn (1979) which usually reflect static concept of stability could aid in detecting the most favorable genotypes with high mean yield and stability. Thus, genotypes G11 and G14 following to genotypes G5, G15 and G14 are recommended as the most favorable genotypes. The nonparametric statistic NPi(1) showed that genotypes G8, G11, G16 and G18 were the most stable genotypes while based on the nonparametric statistic NPi (2), genotypes G6, G8, G16 and G18 were the most stable genotypes (Table 5). Many lentil genotypes (except G1, G2, G6, G8, G9, G10 and G17) were grouped in Group II and the most favorable genotypes considering NPi(1) and mean yield (Figure 2A). Relatively, similar results were observed in Fig. 2B which identified the most favorable genotypes based on NPt (2) and mean yield. According to the nonparametric statistic NPi(3), genotypes G5, G6 and G8 were identified the most stable genotypes while the nonparametric statistic NPt (4) indicated genotypes G6, G8 and G18 as the most stable genotypes (Table 5). Regarding mean yield and NPt (3) (Figure 2C), all genotypes except G1, G2, G6, G8, G9, G10, G14 and G17 were as the most favorable genotypes while considering NPi(4) and mean yield (Figure 2D), genotypes G3, G5, G13, G16 and G18 were detected as the most favorable genotypes. 01 G2 017 <« G8 G8 OH 013G3G25 C11 G4 «07 Qi 4 *G1ft 1250 F.ltin YHU G1 GU GS 09 017 G10 * GB 06 03 019 G11 ♦ * G12 G7 * G17 Q1 G9 02 - * * 010 GS 06 Off 1150 Main Ti»: Figure. 2: Plot of the mean yield versus Thennarasu's (1995) nonparametric stability statistics (A) NP^, NPt (2), (C) NPt (3) and (D) NPt (4) (B) According to