Acta agriculturae Slovenica, 121/2, 1–14, Ljubljana 2025 doi:10.14720/aas.2025.121.2.18689 Original research article / izvirni znanstveni članek Confirmation of top cross hybrids in guava using morpho-molecular markers Masuma Zahan AKHI 1, Jahidul HASSAN 1, Mohammad Sharif RAIHAN 2, M. Mizanur RAHMAN 1, Md. Sanaullah BISWAS 1, 3 Received Received May 05, 2024, accepted April 06, 2025 Delo je prispelo 5. maj 2024, sprejeto 6. april 2025 1 Department of Horticulture, Sylhet Agricultural University, Sylhet-3100, Bangladesh 2 Department of Genetics and Plant Breeding, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangladesh 3 Corresponding author: sanaullah@bsmrau.edu.bd Confirmation of top cross hybrids in guava using morpho- molecular markers Abstract: The study was conducted to confirm the genetic diversity and hybridity of seventeen guava progenies developed from top-crossing between genetically distinct green and pur- ple guava varieties. Morphological, biochemical, and molecular markers effectively identified hybrids exhibiting phenotypes from both parents. Moreover, remarkable genetic diversity was revealed among these segregants. Biplot analysis demonstrated a strong positive relationship between: (1) chlorophyll and an- thocyanin content, (2) leaf length-to-width ratio, (3) leaf area, and (4) petiole length, identifying G15 and G16 genotypes as superior top-cross hybrids. A set of 10 simple sequence repeat (SSR) markers identified 36 alleles with a mean of 3.6 alleles per primer. The polymorphism percentage was 80.83 %, with pair- wise dissimilarity ranging from 0.071 to 0.357. Four SSR prim- ers (mPgCIR03, mPgCIR08, mPgCIR11, and mPgCIR19) spe- cifically confirmed the top-cross hybrid status of G6, G8, G9, G10, G15, and G16 genotypes. These diverse genetic resources will be maintained for homozygous plant production through selfing and subsequent guava improvement programs. Key Words: genetic diversity, top cross, polymorphism, dissimilarity index, molecular marker, segregates Določitev najboljših križancev gvajave z morfološkimi in mo- lekularnimi markerji Izvleček: Namen raziskave je bil potrditi genetsko razno- likost in hibridnost sedemnajstih potomcev gvajave pridoble- jnih s križanjem genetsko različnih zelenih in škrlatnih sort. Morfološki, biokemični in molekularni markerji so potrdili, da izražajo križanci fenotipe obeh staršev, pri čemer je bila med njimi ugotovljena opazna genetska raznolikost. Biplotna analiza je pokazala močne pozitivne povezave med lastnostmi kot so: (1) vsebnost klorofila in antocianov, (2) razmerje med dolžino in širino listov, (3) v listni površini in (4) dolžini list- nih pecljev. Pri tem sta bila genotipa G15 in G16 prepoznana kot najboljša križanca. Z naborom 10 markerjev enostavnih ponavljajočih se zaporedij (SSR) je bilo določenih 36 alelov, s poprečjem 3,6 alela na marker. Odstotek polimorfizma je bil 80,83 %, parna različnost je bila med 0,071 in 0,357. Štirje SSR primerji (mPgCIR03, mPgCIR08, mPgCIR11 in mP- gCIR19) so še posebej potrdili najboljše križance med geno- tipi kot so G6, G8, G9, G10, G15 in G16. Ta raznolik genet- skih vir bo vzdrževan za vzgojo homozigotnih rastlin preko samoopraševanja v bodočih programih žlatnenja gvave. Ključne besede: genetska raznolikost, vrhunski križanci, polimorfizem, indeks različnosti, molekularni marker, seg- regacija Acta agriculturae Slovenica, 121/2 – 20252 M. Z. AKHI et al. 1 INTRODUCTION Guava (Psidium guajava L., 2n = 22), a member of the Myrtaceae family, is widely cultivated in tropical and subtropical regions worldwide for its fleshy fruits (Grat- tapaglia et al., 2012; Morton, 1987). The genus Psidium comprises approximately 150 species, of which only 20 produce edible fruits (Jitendra et al., 2017). Due to its wide adaptability, nutritional value, and medicinal im- portance, guava has gained global popularity as a profit- able crop (Medina & Herrero, 2016). Although guava is well grown in almost all parts of Bangladesh, little attention has been paid to varietal improvement. Only four released varieties are available, while different obsolete varieties like Swarupkathi, Kan- channagar, Mukundapuri, Alahabad, Strawberry guava are still under cultivation at the farmers’ level. Therefore, we assumed that a new guava variety could be developed with the introgression among the widespread varieties with desirable traits. Because of its vegetative propaga- tion means facilitates the genetic purity of the succes- sive generations. Guava is an allogamous fruit crop and self-pollination has been recorded to the extent of about 80 %. Singh (2007) reported that self-pollination in gua- va varies between 35–60  %, depending on the variety. For instance, ‘Allahabad Safeda’ shows a 50–60 % fruit set through self-pollination, while other varieties like ‘Red Flesh’ can achieve higher success rates (up to 70–80 %) under optimal conditions (Pommer & Murakami, 2009). However, 35 % natural cross-pollination occurs that cre- ates the opportunity to develop a heterozygous popula- tion with an adequate genetic variation for selecting de- sirable commercial improved variety (Purseglove, 1968). The determination of genetic diversity and hybridi- ty among breeding materials using morphological mark- ers represents a traditional approach that has been suc- cessfully employed for decades. However, this method presents significant constraints for breeding strategies, particularly in perennial crops (Chandra et al., 2005). Consequently, molecular markers have emerged as a su- perior alternative for varietal improvement programs, offering applications at multiple stages: (1) germplasm evaluation at variety or species level (Valdés-Infante et al., 2003; Rodríguez et al., 2004), (2) hybridity estimation (Barbour et al., 2010), (3) trait-specific association map- ping (Feria-Romero et al., 2009), and (4) linkage map- ping, quantitative trait locus (QTL) identification, and marker-assisted selection (Ritter, 2012). Among various PCR-based techniques used in hor- ticultural crop improvement, simple sequence repeats (SSRs) have proven particularly reliable for hybrid as- sessment. Compared to morphological markers, SSRs enable accurate hybrid identification at the seedling stage with greater efficiency, requiring smaller population sizes and shorter evaluation periods to select promising geno- types (Risterucci et al., 2010). In the present study, we employed two phenotypically distinct guava genotypes as parents for top-cross hybridization: a superior white- pulp cultivar (IPSA guava) and a local pink-pulp variety. Subsequent evaluation of phenotypic and genetic varia- bility incorporated both traditional and advanced breed- ing techniques to identify effective molecular markers for precise genetic diversity assessment and top-cross hybrid confirmation. 2 MATERIALS AND METHODS 2.1 PLANT MATERIALS The experiment was conducted using two cultivated varieties of guava and fifteen offspring developed from the top-crossing of these cultivated varieties. The study was carried out in the nursery and experimental field of the Department of Horticulture at Bangabandhu Sheikh Mujibur Rahman Agricultural University between 2019 and 2022. The experimental materials consisted of a top- cross population, which inherited traits from the parent plants and exhibited significant morphological variation. The parental lines included: G1: A purple guava (open- pollinated female) and G2: IPSA guava (purebred male). Additionally, 15 segregants (G3 to G17) were derived from hybridization. The plant materials are described in detail in Table 1. 2.2 EXPERIMENT DESIGN The experiment was laid out in the Randomized Complete Block Design (RCBD) with three replications where 17 genotypes were allocated randomly in each ex- perimental unit as the independent variables. For mor- phological parameters determination, nine leaves from each genotype were used in one replication and repeated three times. Different morphological markers were used following the guidelines of the International Union for the Protection of New Varieties of Plants (UPOV, 1987) and Alam et al. (2019). 2.3 QUALITATIVE CHARACTERS Fully developed leaves of the fifth and sixth position from the apex of a shoot were selected for the evalua- Acta agriculturae Slovenica, 121/2 – 2025 3 Confirmation of top cross hybrids in guava using morpho-molecular markers tion of qualitative phenotypic characters based on the leaf base and apex shape (Alam et al. 2019; UPOV 1987), the color of the leaf, twigs and vein (IBPGR 1993), leaf surface nature (curvature or twisting type) (Methela et al., 2019; Nagar et al., 2018a) and plant habitus (erect or spreading type) features (Patel 2006; Sharma et al. 2010; Nagar et al., 2018b). All the characters were observed critically in the eye estimation and expressed in descrip- tive traits. 2.4 QUANTITATIVE CHARACTERS The quantitative data of each plant of the parents and F1 generations were recorded based on the leaf length, leaf width and petiole length with the help of digital slide calipers and expressed as centimeters (Shiva et al., 2017). The leaf area (cm2) was measured in leaf length and width, and average data was used to compare the studied accessions. The leaf blade length to width was calculated by the average length of the leaf blade divided by the average width of the respective leaf blade for ran- domly selected four leaves of each genotype. 2.5 BIOCHEMICAL ASSESSMENT 2.5.1 Total chlorophyll Chlorophyll content was estimated by the SPAD chlorophyll fluorescence and acetone extraction pro- cedure. A portable chlorophyll meter (SPAD-502 Plus, Minolta Corporation, Ltd., Osaka, Japan) was used to measure the leaf chlorophyll concentration as a rational unit. Measurements were made at a central point on the leaflet between the midrib and the leaf margin of 5th and 6th leaf from the top (Colla et al. 2013). Six random mea- surements per plant were taken and averaged to a single SPAD value for each treatment. Chlorophyll was extract- ed from 200 mg of leaf samples in 10 ml of acetone (80 % acetone), and the supernatant was made up to the final volume of 25 ml and preserved in dark condition for 24 hours. The absorbance was recorded at 663 and 645 nm using a UV visible spectrophotometer. Total chlorophyll was estimated using the following formula and expressed as mg/g FW (Khan et al. 2017). Chl a = [12.7 (A663) – 2.69 (A645)] [V/(1000×M] Chl b = [22.9 (A645) – 4.68 (A663)] [V/(1000×M] Sl. No. Genotypes Salient feature of the genotypes Variety /Accession 1 G1 (Female) Purple colored plant having purple colored fruit (both skin and flesh), fruit medium in size with hard seeds and astrin- gency taste Purple peyara (inferior) 2 G2 (Male) Green colored plant having less seeded, sweet and medium size fruit IPSA peyara (superior) 3 G3 Purple plant F1 Segregates of the crossing between G1 and G2 4 G4 Green plant 5 G5 Purple plant 6 G6 Green plant 7 G7 Green plant 8 G8 Purple plant 9 G9 Green plant 10 G10 Purple plant 11 G11 Green plant 12 G12 Green plant 13 G13 Green plant 14 G14 Green plant 15 G15 Purple plant 16 G16 Purple plant 17 G17 Green plant Table 1: Characteristics feature with the accession number of the parents and the derived segregates exploited in the study Acta agriculturae Slovenica, 121/2 – 20254 M. Z. AKHI et al. TChl (mg/g FM) = Chla + Chlb Where, Chl= Chlorophyll, V= Volume, M= Mass and TChl= Total chlorophyll 2.5.2 Anthocyanin Fresh leaf (100 mg) was used for anthocyanin ex- traction following Chu et al. (2013) procedure with some modifications. The leaf sample was homogenized in 3 ml of acidic ethanol (1 % HCl w/v) on an ice base and the extracted sample was incubated at 4 °C for 1 hour on the shaker with moderate shaking mode. The suspension was centrifuged with 14,000 rpm at 4  °C for 5 minutes for clarified suspension and this suspension was used for further absorbance analysis. The absorption was mea- sured with a UV- visible spectrophotometer at 530 nm and 657 nm wavelength. Quantification of anthocyanin was performed using the following equation: QAnthocyanin = (A530 – 0.25 × A657) × M –1 Here, QAnthocyanin indicated the amount of anthocy- anin, A530 and A657 were the absorptions at the indicated wavelengths and M was the mass of the plant material used for extraction (g). 2.6 MOLECULAR CHARACTERIZATION 2.6.1 Materials for molecular characterization For molecular characterization, we analyzed 12 dis- tinct guava genotypes selected from an initial pool of 17, excluding five F1 progenies that exhibited close morpho- logical resemblance to their parental lines. The genetic diversity assessment employed ten carefully selected SSR markers that demonstrated precise amplification across 10 F1 progenies and two parent plants. These markers were chosen based on their proven reproducibility, clear scorable banding patterns (150-320 bp), and prior vali- dation in guava (Psidium guajava) as reported by Rod- ríguez et al. (2007) and Kareem et al. (2018). The selected primers generated distinct polymorphic profiles suitable for genetic differentiation, showed optimal amplification efficiency, and specifically targeted known guava loci. 2.6.2 Isolation of genomic DNA The genomic DNA from the actively growing young, fresh and healthy leaves of the selected 12 geno- types was extracted following the modified CTAB (Cetyl Trimethylammonium Bromide) method (Chakrabarti et al. 2006). 150 mg of leaf materials were cut into small pieces and kept inside the mortar. Then some sand and 700 μl of DNA extraction buffer (100 mM Tris-HCl (pH 8.0), 20 mM EDTA (pH 8.0), 1.4 M NaCl, 2 % CTAB solution (w/v), 0.2 % (v/v) 2-Mercaptoethanol) was added and crushed with pestle. Crushed materials were transferred to a 1.5 ml microcentrifuge tube followed by adding 700 μl of DNA extraction buffer. This sample was incubated at 65 ℃ for one hour in a shaker with gentle shaking after thoroughly mixing by vortex mixture for 30 sec afterward, centrifuged for 15 minutes at 15000 rpm. The supernatant of 700 μl was transferred to the microcentrifuge tube, and then added 4 μl of RNase and kept 45 minutes at 37 °C. Then 700 μl of Chloroform: Isoamyl alcohol (24: 1, v/v) was added to the sample and mixed thoroughly in gentle mode. Spinning this sample at 12000 rpm for 10 minutes with the addition of and a 2/3rd volume isopropanol for spinning down the DNA pellet and supernatant was discarded carefully. The pel- lets were washed with 70 % ethanol and again spinned out at 10000 rpm for 10 minutes. After drying the pellets were dissolved in 100 μl of sterile water and stored at -20℃ until the PCR analysis. 2.6.3 PCR analysis for genotypes selection Ten SSR primers were used to amplify the DNA sample of 12 genotypes. PCR was conducted in 25 of reaction volume for each reaction and total 12 reactions were done for each 10 SSR primers. The PCR reaction mixture contained template DNA (20 ng), 1 μM forward and 1 μM reverse primers, 200 μM of dNTPs, and 10X PCR buffer, 0.1 U Taq DNA polymerase and MgCl2 solu- tion (1.5 mM). The optimization of conditions was made separately for each marker. PCR was carried out in the thermal cycler with an initial denaturation at 94 °C for 5 min; denaturation at 94 °C for 30 sec; primer annealing at 55 °C for 45 sec; extension at 72 °C for 2 min and final extension at 72 °C for 4 min. All amplifications were confirmed after running PCR product (10 μl) on agarose gels (1.5%). An 8 µl lad- der (100 bp) with 2 µl loading dye was used for compari- son. After staining with ethidium bromide (EtBr) gel was visualized with the gel documentation system. 2.6.4 Data analysis Principal component analysis (PCA) was done us- ing the R-statistical program to distinguish F1 segregates with respective parents according to their morphologi- cal features. Marker (SSR) based data were analyzed, and Roger’s genetic distance matrices were calculated be- Acta agriculturae Slovenica, 121/2 – 2025 5 Confirmation of top cross hybrids in guava using morpho-molecular markers tween each pair of lines using DARwin software 6.0 (Per- rier and Jacquemoud-Collet 2016). 3 RESULTS 3.1 MORPHOLOGICAL CHARACTERIZATION 3.1.1 Qualitative characters Morphological qualitative traits exhibited dis- tinct visual differences between parents and their F1 segregants (Table 2, Figure 1). The female parent (G1) displayed oblanceolate leaf shapes, while the male par- ent (G2) showed elliptical leaves. Among the 15 seg- regants, we observed various leaf shapes including oblong, elliptical, lanceolate, oblong-to-elliptical, and ovate forms. While both parents shared an obtuse leaf base shape, their segregants exhibited deviations in- cluding cordate and rounded bases. Similar variation occurred in leaf apex shapes, with F1 progenies show- ing apiculate, rounded, and acute forms compared to the parents’ obtuse apices. The male parent G2 exhib- ited leaf twisting and midrib curvature - traits absent in female parent G1 - with intermediate variations ap- pearing among their segregants. Leaf surface texture varied from smooth to rough (Table 2). Ventral sur- face analysis (Figure 1a) revealed three texture types: smooth, moderately smooth, and rough. Dorsal sur- faces (Figure 1b) showed moderately smooth textures only in G2 and G11, with rough textures in all other genotypes. Branching pattern attitudes varied between parents and segregating progenies (Table 2). Spread- ing growth habits characterized genotypes G1, G4-G5, G7-G8, and G11-G14, while the remaining genotypes exhibited erect growth forms. Though the female (G1) had greyed dark purple and male (G2) had light green color fully matured leaves, their pogenies showed different leaf colors viz. yellowish green, light green, green, maroon dark pur- ple and greenish-purple. Similarly, G1 had dark red and G2 had light green twigs color while dark red, brownish red, yellowish-green, light green, light green with red streak, green with red streaks and reddish- green were observed among the segregates. Consid- erable variation for leaf vein color viz. red, dark red, reddish green and green was also noticed among the segregates, whereas G1 had red color leaf vein and G2 had green color leaf vein. Stem color variation viz. red- dish brown, greenish brown, brown was found among the segregating progenies through their two parents such as G1 had dark reddish brown and G2 had green- ish brown stem. 3.1.2 Quantitative characters Morphological data on five quantitative traits were showed significant variation among two parent guava lines and their 15 segregates (Table 3). Though, both the parents viz. G1 (9.98 cm) and G2 (9.8 cm) had almost similar fully developed leaf lengths, the segregates showed a slight variation. Among the prog- enies, the highest leaf length was found in G14 (11.80 cm) and the lowest in G8 (7.85 cm). The highest leaf width was found in G14 (6.70 cm) and the lowest was in G2 (3.93 cm). Although the parents G1 and G2 had identical petiole length (0.75 cm) but remarkable vari- ations were observed among the progenies where G14 (0.88 cm) had the highest and G8 (0.38 cm) had the lowest petiole length. Similarly, the maximum leaf area was observed in G14 (79.57 cm2) and the minimum in G8 (35.27 cm2). The highest leaf length width ratio was identified in G2 (4.37) but the lowest was in G6 (1.63) 3.2 BIOCHEMICAL ANALYSIS 3.2.1 Chlorophyll content The total chlorophyll content estimated by the SPAD meter was statistically identical in both the parents and their progenies (Table 4). However, the highest chlorophyll content (%) was measured in G10 (45.20) and the lowest in G11 (35.45). On the other hand, Chla is almost similar in two parents, viz. G1 Figure 1: Shape and color of fully developed leaf (a) ventral surface (b) dorsal surface in different guava genotypes. Acta agriculturae Slovenica, 121/2 – 20256 M. Z. AKHI et al. G en ot yp e Fu lly d ev el op ed le af sh ap e Le af b as e sh ap e Le af ap ex sh ap e Fu lly d ev el - op ed le af tw ist in g Cu rv at ur e in m id rib Le af su rf ac e na tu re Tr ee h ab it Fu lly d ev el op ed le af co lo r Tw ig co lo r Le af v ei n co lo r St em co lo r Ve nt ra l s ur fa ce D or sa l s ur fa ce G 1 O bl an ce ol at e O bt us e O bt us e A bs en t A bs en t Sm oo th Ro ug h Sp re ad in g G re ye d da rk pu rp le D ar k re d Re d D ar k re dd ish br ow n G 2 El lip tic al O bt us e O bt us e Pr es en t Pr es en t Sm oo th M od er at el y sm oo th Er ec t Li gh t g re en Li gh t g re en G re en G re en ish b ro w n G 3 O va te C or da te O bt us e A bs en t A bs en t Sm oo th Ro ug h Er ec t M ar oo n pu rp le D ar k re d D ar k re d Re dd ish b ro w n G 4 El lip tic al Ro un de d Ap ic ul at e A bs en t Pr es en t M od er at el y sm oo th Ro ug h Sp re ad in g Ye llo w ish g re en G re en w ith re d st re ak s Re dd ish gr ee n G re en ish b ro w n G 5 La nc eo la te C or da te A cu te Pr es en t Pr es en t M od er at el y sm oo th Ro ug h Sp re ad in g M ar oo n pu rp le D ar k re d D ar k re d Re dd ish b ro w n G 6 O bl on g C or da te O bt us e A bs en t A bs en t Sm oo th Ro ug h Er ec t Ye llo w ish g re en Li gh t g re en w ith re d st re ak G re en G re en ish b ro w n G 7 O bl on g Ro un de d Ro un de d Pr es en t Pr es en t Sm oo th Ro ug h Sp re ad in g Li gh t g re en Li gh t g re en G re en Re dd ish b ro w n G 8 O bl on g C or da te A cu te Pr es en t A bs en t Sm oo th Ro ug h Sp re ad in g G re en ish p ur pl e Br ow ni sh re d Re d Re dd ish b ro w n G 9 El lip tic al O bt us e Ro un de d Pr es en t A bs en t Sm oo th Ro ug h Er ec t Ye llo w ish g re en Li gh t g re en w ith re d st re ak Re dd ish gr ee n br ow n G 10 O bl on g C or da te O bt us e Pr es en t A bs en t Ro ug h Ro ug h Er ec t G re en ish p ur pl e Br ow ni sh re d D ar k re d Re dd ish b ro w n G 11 O va te Ro un de d Ap ic ul at e A bs en t A bs en t Sm oo th M od er at el y sm oo th Sp re ad in g G re en Li gh t g re en w ith re d st re ak G re en Br ow n G 12 La nc eo la te C or da te A cu te Pr es en t A bs en t Sm oo th Ro ug h Sp re ad in g G re en Li gh t g re en w ith re d st re ak G re en G re en ish b ro w n G 13 El lip tic al O bt us e Ro un de d A bs en t Pr es en t Sm oo th Ro ug h Sp re ad in g Li gh t g re en Li gh t g re en w ith re d st re ak Re dd ish G re en G re en ish b ro w n G 14 O bl on g to el - lip tic al O bt us e O bt us e Pr es en t A bs en t M od er at el y sm oo th Ro ug h Sp re ad in g Ye llo w ish g re en Li gh t g re en w ith re d st re ak G re en G re en ish b ro w n G 15 O bl on g Ro un de d A cu te Pr es en t A bs en t Sm oo th Ro ug h Er ec t M ar oo n pu rp le Re dd ish g re en D ar k re d Re dd ish b ro w n G 16 O bl on g Ro un de d A cu te Pr es en t A bs en t Sm oo th Ro ug h Er ec t D ar k pu rp le D ar k re d Re d Re dd ish b ro w n G 17 O va te Ro un de d O bt us e Pr es en t Pr es en t Sm oo th Ro ug h Sp re ad in g Li gh t g re en Ye llo w ish g re en G re en G re en ish b ro w n Ta bl e 2: M or ph ol og ic al ch ar ac te ris tic s o f g ua va Acta agriculturae Slovenica, 121/2 – 2025 7 Confirmation of top cross hybrids in guava using morpho-molecular markers (1.10 mg g-1 FM) and G2 (1.14 mg g-1 FM) but remark- able variations were found among the segregates (Ta- ble 4). The highest Chla was determined in G16 (1.46 mg g-1 FM); which was at par with G10 and G15and the lowest in G13 (0.86 mg g-1 FM). Meanwhile, both the parent showed differences in Chlb content denot- ed as G1 (0.56 mg g-1 FM) and G2 (0.45 mg g-1 FM). Consequently, wide variation was observed among the segregates Depicted as G16 (0.74 mg g-1 FM) had max- imum and G13 (0.37 mg g-1FM) had minimum Chlb content. Similar trends of result in the TChl content were observed in the parents G1 (1.65 mg g-1 FM) and G2 (1.59 mg g-1 FM) and the progenies of G16 (1.65 mg g-1 FM) had maximum and G13 (1.24 mg g-1 FM) had minimum TChl content. 3.2.2 Anthocyanin content The results depict that anthocyanin content was varied significantly between the parents where purple parent G1 and the green parent G2 were showed about 14.03 mg g-1 FM and 1.86 mg g-1 FM, respectively (Figure 2a). So a large variation was found among the segregates where G3 (17.89 mg g-1 FM) had maximum anthocyanin, which was at par with G16, G1, G15, G8, G5, and all these genotypes had a different shade of purple leaves. On the contrary, G6 (0.54 mg g-1 FM) had minimum anthocyanin, which was statistically similar with the genotypes G4, G11, G14, G17, G13, G2, G9, G7, G12, and all of those had a different shade of green leaves (Figure 2b). Morpho-biochemical characteristics variation visualize in Biplot of PCA analysis - The biplot (Fig- ure 3) displayed 68.4 % of the total variation observed (PC1 in Dim1 = 46.5 % and PC2 in Dim2 = 21.9 %) in the standardized data of the 17 genotypes for the studied eight morpho-biochemical traits. This biplot was visualized from two perspectives (Yan and Reid, 2008), showing a strong positive correlation among Chla, TChl, Chlb, ChlSPAD and Anth traits due to having an acute angle and covered 46.5% of the varia- tion (PC1). On the other hand, Anth and LWR; LA and PL also had a strong positive correlation that cov- ered 21.9 % of the variation (PC2). In addition, biplot analysis showed the geno- types’ trait profiles, especially those positioned far away from the origin and correlation among the traits. Therefore, the scatter plot helped select genotypes for the yield contributing traits or traits that helped in better qualitative performance. In the present biplot visualization after loading variations by PC1 and PC2, it was evident that genotypes G10 and G12 had better performance for a higher percentage of SPAD value; Genotype Leaf length (cm) Leaf width (cm) Petiole length (cm) Leaf area (cm2) Leaf length width ratio G1 9.98 ± 0.40ab 5.18 ± 0.29abcd 0.75 ± 0.10ab 51.71 ± 4.88ab 1.93 ± 0.04a G2 9.8 ± 0.71ab 3.93 ± 2.02d 0.75 ± 0.06ab 37.83 ± 19.38b 4.37 ± 4.86a G3 8.72 ± 2.46ab 4.53 ± 1.65abcd 0.53 ± 0.10def 42.52 ± 25.50ab 1.98 ± 0.18a G4 9.33 ± 1.03ab 4.90 ± 0.35abcd 0.65 ± 0.06bcd 45.91 ± 7.65ab 1.90 ± 0.13a G5 8.80 ± 2.11ab 4.48 ± 1.01bcd 0.40 ± 0.00ef 40.93 ± 17.93b 1.96 ± 0.11a G6 10.73 ± 1.21ab 6.60 ± 0.81ab 0.70 ± 0.08bc 71.49 ± 16.50ab 1.63 ± 0.06a G7 10.60 ± 0.84ab 5.68 ± 0.64abcd 0.50 ± 0.00def 60.41 ± 10.86ab 1.88 ± 0.17a G8 7.85 ± 2.84b 4.30 ± 0.81cd 0.38 ± 0.05f 35.27 ± 18.05b 1.79 ± 0.44a G9 10.80 ± 0.84ab 5.92 ± 0.25abcd 0.55 ± 0.10cde 64.12 ± 7.18ab 1.82 ± 0.10a G10 9.98 ± 1.97ab 4.95 ± 1.01abcd 0.53 ± 0.05def 50.74 ± 20.31ab 2.02 ± 0.17a G11 9.98 ± 1.97ab 4.95 ± 1.01abcd 0.53 ± 0.05def 50.74 ± 20.31ab 2.02 ± 0.17a G12 8.90 ± 0.28ab 4.88 ± 0.68abcd 0.40 ± 0.00ef 43.48 ± 7.10ab 1.85 ± 0.24a G13 10.73 ± 1.74ab 5.68 ± 0.88abcd 0.63 ± 0.05bcd 61.96 ± 18.57ab 1.89 ± 0.10a G14 11.80 ± 1.06 a 6.70 ± 0.65a 0.88 ± 0.05a 79.57 ± 14.67a 1.76 ± 0.03a G15 9.23 ± 0.40ab 5.65 ± 0.48abcd 0.55 ± 0.06cde 52.19 ± 5.99ab 1.64 ± 0.13a G16 10.85 ± 2.71ab 5.45 ± 1.86abcd 0.53 ± 0.05def 62.86 ± 34.62ab 2.04 ± 0.22a G17 10.70 ± 2.08ab 6.30 ± 0.76abc 0.75 ± 0.06ab 68.57 ± 21.15ab 1.69 ± 0.14a LSD0.05 3.70 2.19 0.16 37.93 3.08 Table 3: Variation in leaf length, leaf width, petiole length, leaf area and leaf length width ratio among the guava genotypes Acta agriculturae Slovenica, 121/2 – 20258 M. Z. AKHI et al. G16 could be a better choice for the maximum TChl; G16, G15, G10 were superior for a higher amount of Chla and Chlb content; G3 could be selected for the highest Anth content. 3.2.3 Analysis of correlation matrix The correlation matrix analysis among the differ- ent morphological traits (Figure 4a and 4b) revealed that a strong positive correlation was observed between Tchl and Chla (0.99) followed by Tchl and Chlb (0.97). Meanwhile, Chla has a significant correlation with Chlb (0.94). Almost similar correlation matrix was noticed between ChlSPAD and Chla (0.65); ChlSPAD and TChl (0.64) whereas it was 0.59 between ChlSPAD and Chlb (0.59). Furthermore, PL was found correlated with LA (0.58) and Chlb with anthocyanin (0.53). 3.3 MOLECULAR CHARACTERIZATION 3.3.1 Level of polymorphism Different polymorphism levels were observed among all 12 studied guava genotypes using a set of ten SSR primers (Table 5). A total of 36 alleles were generat- ed by SSR markers, with a mean of 3.6 alleles per prim- er. Among the ten primers, six (mPgCIR02, mPgCIR05, mPgCIR15, mPgCIR17, mPgCIR21, and mPgCIR25) produced both polymorphic and monomorphic bands, while the remaining four primers exhibited exclusively polymorphic banding patterns. All primers were select- ed from previously characterized guava loci (Rodríguez et al., 2007; Kareem et al., 2018). In this study, mPgCIR02, mPgCIR03, mPgCIR08, mPgCIR11, and mPgCIR19 showed clear polymor- phism, while the remaining primers displayed lower polymorphism levels. Among the SSR markers, mP- gCIR03, mPgCIR08, and mPgCIR11 each produced 4 polymorphic bands, and mPgCIR19 yielded 3 poly- morphic bands, with no monomorphic alleles de- tected. These four markers demonstrated 100  % poly- morphism, making them strong candidates for varietal improvement programs. The highest number of alleles was observed with mPgCIR02, which showed 83.33% polymorphism, while the lowest polymorphism (50%) was recorded for mPgCIR17. Figure 2: Anthocyanin pigment content (a) and variation in twig color due to having different level of anthocyanin (b) among 17 guava genotypes. Figure 3: Biplot analysis of guava genotypes for morphological and biochemical character association. (LA = Leaf area (cm2); PL = Petiole length (cm); LWR = Leaf length width ratio; Chl a = Chlorophyll a (mg g-1 FM); Chl b = chlorophyll b (mg g-1 FM); TChl = Total chlorophyll (mg g-1 FM); ChlSPAD = SPAD value of chlorophyll (%); Anth =Anthocyanin (mg g-1 FM). Acta agriculturae Slovenica, 121/2 – 2025 9 Confirmation of top cross hybrids in guava using morpho-molecular markers 3.3.2 Polymorphic information Polymorphic information observed by SSR prim- ers revealed that thirty alleles showed 83.33  % poly- Figure 4: Correlation and visualization of guava genotypes. Correlation matrix with significant value among the different vari- ables of 17 guava genotypes (a). Visualization of correlation matrix among the different variables of guava genotypes. (Blank space indicates insignificant correlation. Cyan to blue and cyan to red colors show significant (p<0.05) positive and negative correlation between traits respectively) (b). (LA = Leaf area (cm2); PL = Petiole length (cm); LWR = Leaf length width ratio; Chla = Chlorophyll a (mg g-1 FM); Chlb = chlorophyll b (mg g-1 FM); TChl = Total chlorophyll (mg g-1 FM); ChlSPAD = SPAD value of chlorophyll (%); Anth =Anthocyanin (mg g-1 FM). Genotype Chlorophyll (SPAD units) Chla (mg g-1 FM) Chlb (mg g-1 FM) TChl (mg g-1 FM) G1 38.75 ± 1.06 1.10 ± 0.004de 0.56 ± 0.02bcde 1.65 ± 0.02de G2 39.60 ± 2.12 1.14 ± 0.002cd 0.45 ± 0.01ef 1.59 ± 0.02de G3 40.30 ± 1.56 1.06 ± 0.004e 0.53 ± 0.01cde 1.58 ± 0.02de G4 38.10 ± 0.57 1.15 ± 0.028cd 0.47 ± 0.01def 1.62 ± 0.01de G5 41.05 ± 1.34 1.08 ± 0.001de 0.55 ± 0.04bcde 1.63 ± 0.04de G6 38.75 ± 0.35 0.95 ± 0.021f 0.42 ± 0.02f 1.36 ± 0.00f G7 39.70 ± 2.83 1.17 ± 0.001c 0.42 ± 0.02cde 1.71 ± 0.04d G8 39.30 ± 1.56 1.04 ± 0.002e 0.54 ± 0.01cde 1.57 ± 0.01e G9 40.70 ± 1.41 1.33 ± 0.021b 0.56 ± 0.02bcd 1.90 ± 0.04c G10 45.20 ± 4.67 1.45 ± 0.014a 0.65 ± 0.04ab 2.10 ± 0.05ab G11 35.45 ± 4.17 0.88 ± 0.007g 0.37 ± 0.02f 1.25 ± 0.03fg G12 44.25 ± 4.88 1.37 ± 0.014b 0.62 ± 0.02bc 1.99 ± 0.04bc G13 37.90 ± 1.84 0.86 ± 0.021g 0.37 ± 0.01f 1.24 ± 0.01g G14 40.65 ± 1.91 1.35 ± 0.014b 0.65 ± 0.04ab 1.99 ± 0.05bc G15 42.95 ± 5.16 1.44 ± 0.028a 0.65 ± 0.04ab 2.09 ± 0.02ab G16 36.95 ± 10.54 1.46 ± 0.021a 0.74 ± 0.03a 2.20 ± 0.05a G17 38.05 ± 0.64 0.87 ± 0.028g 0.39 ± 0.01f 1.26 ± 0.01fg LSD0.05 14.79 0.07 0.11 0.13 Table 4: Variation in Chlorophyll content (SPAD units), Chla, Chlb and TChl in different guava genotypes Acta agriculturae Slovenica, 121/2 – 202510 M. Z. AKHI et al. morphism among the total alleles and six alleles showed monomorphism of 16.67 %. The overall percentage of polymorphic alleles was 80.83 %. All primers produced specific, effective, and measurable alleles. The ampli- fied alleles ranged from 220-1250 bp (Figure 5; Table 5). A representative image of mPgCIR08 primer showed the allelic difference between the parents and segre- gates (Figure 5). The average polymorphic information content (PIC) was found 0.576 among the genotypes. The primer mPgCIR03 showed highest (0.693) poly- morphic information followed by mPgCIR08 and mP- gCIR11. Thus, the primer mPgCIR03, mPgCIR11, and mPgCIR19 were shown effective for the selection of top cross hybrids and genetic diversity study. Determination of genetic relatedness with dis- similarity matrix - A dissimilarity matrix using ten SSR markers was used to estimate the genetic relatedness of analyzed accessions of guava species. The dissimilarity matrix (Figure 6, Table 5) represented the pair-wise dis- similarity value ranged from 0.071 to 0.357. The lowest value was observed between the G8 and G14 (0.071); thus, these are the closest genotypes. Similarly, a lower value (0.097) was found between the genotypes G5 and G16; 0.103 was found between G6 and G8; 0.111 was found for three pairs of G2 and G9; G4 and G9; G6 and G14. So, it can be said that G5 and G16; G6 and G8; G2 and G9; G4 and G9; G6 and G14 were closer genotype pairs. Contrary, the highest dissimilarity matrix value (0.357) was found among G1 and G15; G6 and G15 gen- otype pairs indicated these genotypes were not closely Sl No. Name of primer Sequences (5'-3') Observed size (bp) NA NPA PIC QMA %PA 1 mPgCIR02 F: AGTGAACGACTGAAGACC R: ATTACACATTCAGCCACTT 220-1250 6 5 0.569 1 83.33 2 mPgCIR03 F: TTGTGGCTTGATTTCC R: TCGTTTAGAGGACATTTCT 220-800 4 4 0.693 0 100 3 mPgCIR05 F: GCCTTTGAACCACATC R: TCAATACGAGAGGCAATA 220-800 3 2 0.567 1 66.67 4 mPgCIR08 F: ACTTTCGGTCTCAACAAG R: AGGCTTCCTACAAAAGTG 220-800 4 4 0.676 0 100 5 mPgCIR11 F: TGAAAGACAACAAACGAG R: TTACACCCACCTAAATAAGA 220-800 4 4 0.650 0 100 6 mPgCIR15 F: TCTAATCCCCTGAGTTTC R: CCGATCATCTCTTTCTTT 240-780 3 2 0.576 1 66.67 7 mPgCIR17 F: CCTTTCGTCATATTCACTT R: CATTGGATGGTTGACAT 300-700 2 1 0.393 1 50 8 mPgCIR19 F: AAAATCCTGAAGACGAAC R: TATCAGAGGCTTGCATTA 220-800 3 3 0.671 0 100 9 mPgCIR21 F: TGCCCTTCTAAGTATAACAG R: AGCTACAAACCTTCCTAAA 300-1250 4 3 0.476 1 75 10 mPgCIR25 F: GACAATCCAATCTCACTTT R: TGTGTCAAGCATACCTTC 200-780 3 2 0.546 1 66.67 Total ------ ----- 36 30 06 808.34 Percentage/Average* 3.6* 83.3 0.575 16.67 80.83* Table 5: Polymorphic information of ten SSR markers with their sequences NA number of alleles, NPA number of polymorphic alleles, PIC polymorphism information content, QMA quantity of monomorphic alleles, PPA percentage of polymorphic alleles, SSR simple sequence repeat and *indicates the average values of QAA and PPA produced by each primer Acta agriculturae Slovenica, 121/2 – 2025 11 Confirmation of top cross hybrids in guava using morpho-molecular markers related. Furthermore, a higher level of dissimilarity was also observed in several genotypes such as G15 and G14 (0.333); G2 and G15 (0.313); G16 and G15 (0.310). 4 DISCUSSIONS The effectiveness of SSR markers for early-stage se- lection and screening of plants has been well established for assessing genetic diversity and identifying pure hy- brids (Maravilla et al., 2017; Dawson et al., 2013; Tuler et al., 2015). In this study, we evaluated twelve guava genotypes using ten SSR primer pairs, among which four primers (mPgCIR03, mPgCIR08, mPgCIR11, and mPgCIR19) demonstrated 100 % polymorphism. These results align with previous findings by Ma et al. (2019), Dinesh et al. (2017), Campos-Rivero et al. (2017), and Urquía et al. (2019), who reported 90-97  % polymor- phism using SSR markers for genetic diversity analy- sis and hybrid confirmation. Notably, Kanupriya et al. (2011) identified 23 microsatellite markers that success- fully discriminated among nine guava varieties. Besides molecular markers, morpho-biochemical markers are helpful for variety identification and are reli- able in establishing the genetic relationships across more extensive and diverged accessions of guava (Padilla- Ramirez and Gonzalez-Gaona 2008). In this study mor- phological traits viz. fully developed leaf shape, leaf base and apex shape, leaf twisting, midrib curvature, leaf sur- face nature, tree habit, the color of fully developed leaf, twig, leaf vein and stem showed remarkable variations. The variations of leaf characteristics in guava were also reported in some recent studies (Alam et al. 2019; Methe- la et al. 2019; Nagar et al. 2018a; Nagar et al. 2018b). In an experiment, Dubey et al. (2016) found leaf length ranged from 10.75 cm to 13.95 cm, leaf width from 4.36 cm to 7.08 cm, and leaf area from 65.1 cm2 to 95.71 cm2. The observed leaf width value of this study was well sup- ported by the findings of El-Sisy (2013) who found that leaf width was varied from 4.0 cm to 6.9 cm. El-Sharkawy and Othman (2009) stated that the leaf petiole length of five guava genotypes ranged from 0.84 cm to 0.55 cm. El-Sisy (2013) also reported that leaf area ranged from 30.67 to 88.33 cm2 which were similar with the findings of this study. Chlorophyll and anthocyanin are the two most es- sential pigments in leaves (Croft and Chen 2017). Chlo- rophyll, commonly responsible for green color, is an es- sential pigment for converting light into chemical energy and the increased synthesis of anthocyanins is the main reason leading to purple coloration (Croft et al. 2017). In this study chlorophyll SPAD value among the parent and their segregates were well supported by the previ- ous study done by Afifi et al. (2019), who found about 35.47 % to 47.47 % chlorophyll content variation among the guava genotypes. In all the case, the Chla content in leaf was found higher than the Chlb. The possible reason could be that Chla is the primary pigment while others, including Chlb are accessory pigments (Srichaikul et al. 2011). Anthocyanin is responsible for the colors (red, purple, and blue) of leaves, stems, roots, flowers and fruits (Khoo et al. 2017) that reflect the color variation among the segregates. It might happen because the par- ents used in the hybridization process possess different colors with the significant anthocyanin variation that strongly influenced the pigmentation variation of their segregates. Again, biplot analysis of morpho-biochemical traits is considered an efficient way of suitable genotype selection and magnitude of the relationship among the agronomic traits (Farshadfar et al. 2013). Sau et al. (2017) Figure 5: Polymorphic profile of primer mPgCIR08 for 12 guava genotypes. Hybridity testing of guava hybrid using the mPgCIR08 SSR marker. M= 100 bp ladder, Lane 2 and 3 indi- cated the two parent genotypes and lane 4-13 indicated their offspring genotypes viz. lane 3= G3, Lane 4= G4, lane 5= G5, lane 6= G6, lane 7= G8, lane 8= G9, lane 9= G10, lane 10= G14, lane 11= G14, lane 12= G15 and lane 13= G16. Lane 6, 8 and 12 (arrow) represents top cross hybrids (G6, G9 and G15) guava. Figure 6: Dendrogram showing genetic relationship among 10 segregating guava progenies and their two parent genotypes based on SSR marker analysis. Acta agriculturae Slovenica, 121/2 – 202512 M. Z. AKHI et al. conducted biplot analysis to identify the principal yield attributes and considerable variations were observed in yield and yield contributing characters. From the biplot and correlation matrix analysis, a strong positive correla- tion was observed between Tchl and Chla (0.99) followed by Tchl and Chlb (0.97) in the present study that is sup- ported by the findings of Santos et al. (2017). 5 CONCLUSIONS Genetic diversity assessment and top-cross hybrid selection were conducted using morphological, phys- io-chemical, and molecular markers. Among the SSR primers tested, mPgCIR03, mPgCIR08, mPgCIR11, and mPgCIR19 effectively identified top-cross hybrids de- rived from the G1 × G2 hybridization scheme. Results revealed that progenies G5, G6, G8, G9, G10, G15, and G16 showed the highest segregation, exhibiting mor- phological characteristics from both parents. The study demonstrated that morphological variation and antho- cyanin pigmentation serve as valuable selection criteria when combined with molecular markers for identifying superior hybrid progenies. These findings provide sig- nificant insights for hybridization programs and progeny selection in tropical guava, particularly when based on phenotypic characterization. Furthermore, the devel- oped segregating progenies represent valuable genetic resources that can serve as foundation material for future guava improvement programs targeting desirable traits. 6 ACKNOWLEDGMENTS This research work was supported by the Research Management Wing of Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangla- desh. 7 CONFLICT OF INTEREST The authors declare no conflict of interest. 8 AUTHOR CONTRIBUTIONS The funding for the work was received through Md. Sanaullah Biswas. Md. Sanaullah Biswas, Mohammad Sharif Raihan and M. Mizanur Rahman conceptualized the initial work and the planned activities of this work. Masuma Zahan Akhi and Md. Sanaullah Biswas carried out the field experiment and performed the laboratory experiments. Masuma Zahan Akhi and Md. Sanaul- lah Biswas collection of the data. Masuma Zahan Akhi and Jahidul Hassan organized, analyzed and interpreted the data. Masuma Zahan Akhi and Md. 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