Genetic Variability and Diversity Analysis in Sesame (*Sesamum indicum* L.)

Author Draft June 2025, Volume 1, Issue I. doi: 10.5281/zenodo.15726530 Genetic Variability and Diversity Analysis in Sesame (Sesamum indicum L.) Gayathri G * Kerala Agricultural University Dijee Bastian Kerala Agricultural University Abstract Sesame (Sesamum indicum L.) is an ancient oilseed crop of significant nutritional and economic value, but its productivity remains suboptimal due to limited genetic improvement. This study assessed genetic variability, correlation patterns, and genetic divergence among 40 sesame genotypes to identify superior parents for breeding programs. Evaluating nine quantitative traits, including days to flowering, plant height, branches per plant, and oil content, in a randomized block design with three replications, revealed significant genetic variation. High heritability and genetic advance were recorded for traits such as days to flowering (95.98%) and seed yield per plant (98.69%). Number of capsules per plant showed the highest direct effect on seed yield. Mahalanobis D² analysis grouped the genotypes into six clusters, with plant height contributing the most to total divergence. The study identified genotypes from divergent clusters (III, IV, V, and VI) as potential parents for hybridization to develop high-yielding varieties with improved oil content. Keywords: Sesame, genetic variability, heritability, correlation, path analysis, genetic divergence, breeding. Author Draft 2Genetic Variability and Diversity Analysis in Sesame (Sesamum indicum L.) 1. Introduction Sesame (Sesamum indicum L., 2n=2x=26) represents one of humanity’s most ancient cultivated oilseed crops, with archaeological evidence suggesting its cultivation dates back over 4,000 years (Bedigian 2015). Known by various vernacular names including Gingelly, Ellu in Malayalam, and Tila in Sanskrit, this crop holds profound cultural and religious significance, particularly in Indian traditions where sesame seeds feature prominently in Hindu religious ceremonies (Wei et al. 2015). The ancient Sanskrit etymology supports the hypothesis that sesame may have been the source of the first extracted vegetable oil, underlining its historical importance in human nutrition (Pathak et al. 2014). Modern nutritional analysis reveals that sesame seeds contain 50–60% oil of exceptional quality, comparable to olive oil in its nutritional profile (Uzun et al. 2008;Anilakumar et al. 2010). Sesame oil demonstrates remarkable stability compared to other edible oils, primarily attributed to its rich content of natural antioxidants including sesamin, sesaminol, sesamol, sesamolinol, and squalene (Namiki 2007;Kamal-Eldin et al. 2011). The oil’s high concentration of polyunsaturated fatty acids, combined with its cholesterol-lowering and blood pressure-reducing properties, has renewed scientific and commercial interest in this ancient crop (Sankar et al. 2006;Gouveia et al. 2014;Dalibalta et al. 2020). Recent genomic studies have revealed the complex genetic architecture underlying sesame’s agronomic traits, with high-throughput sequencing technologies enabling the identification of quantitative trait loci (QTLs) associated with yield components and stress tolerance (Zhang et al. 2013;Wang et al. 2016;Yu et al. 2019). These advances have opened new avenues for marker-assisted selection and genomic breeding approaches (Wei et al. 2016;Dossa et al. 2017). Despite its nutritional superiority and agricultural advantages—including drought tolerance, low input requirements, and suitability for crop rotations due to its extensive taproot system (Ashri 2007)—sesame productivity remains disappointingly low. India, while leading globally in both cultivation area (1.8 million hectares) and production (0.87 million tonnes), achieves an average productivity of only 483 kg/ha, significantly below China (1,200 kg/ha) and Turkey (1,100 kg/ha) (FAO 2020;Yahaya et al. 2021). 2. Materials and methods The experimental material comprised 40 sesame genotypes obtained from four major sources: Kerala Agricultural University (7 varieties), Tamil Nadu Agricultural University (7 varieties), All India Coordinated Research Project on Oilseeds cultures (20 accessions), and National Bureau of Plant Genetic Resources Regional Centre, Vellanikkara (6 accessions). Sl. No. Genotype Source Sl. No. Genotype Source 1 KYM-1 ORARS, Kayamkulam 21 AVTS-06-9 ORARS, Kayamkulam 2 Soma ORARS, Kayamkulam 22 AVTS-06-10 ORARS, Kayamkulam Author Draft Journal of Sustainable Technology in Agriculture 3 Sl. No. Genotype Source Sl. No. Genotype Source 3 Surya ORARS, Kayamkulam 23 IVTS-06-2 ORARS, Kayamkulam 4 Tilak ORARS, Kayamkulam 24 IVTS-06-3 ORARS, Kayamkulam 5 Tilatara ORARS, Kayamkulam 25 IVTS-06-6 ORARS, Kayamkulam 6 Tilarani ORARS, Kayamkulam 26 IVTS.06.8 ORARS, Kayamkulam 7 CO-1 TNAU, Coimbatore 27 IVTS.06.12 ORARS, Kayamkulam 8 SVPR-1 CRS, Srivilliputhur 28 IVTS.06.13 ORARS, Kayamkulam 9 VRI-1 RRS, Vridhachalam 29 IVTS.06.15 ORARS, Kayamkulam 10 VRI-2 RRS, Vridhachalam 30 IVTS.06.16 ORARS, Kayamkulam 11 TMV-3 RRS, Vridhachalam 31 IVTS.06.22 ORARS, Kayamkulam 12 TMV-4 RRS, Vridhachalam 32 IVTS.06.26 ORARS, Kayamkulam 13 TMV-5 RRS, Vridhachalam 33 IVTS.06.27 ORARS, Kayamkulam 14 TMV-6 RRS, Vridhachalam 34 IVTS.06.28 ORARS, Kayamkulam 15 AVTS.06.1 ORARS, Kayamkulam 35 TCR-2511 NBPGR Regional Station, Vellanikkara 16 AVTS.06.3 ORARS, Kayamkulam 36 TCR-2527-C NBPGR Regional Station, Vellanikkara 17 AVTS.06.4 ORARS, Kayamkulam 37 TCR-3279-A NBPGR Regional Station, Vellanikkara 18 AVTS.06.5 ORARS, Kayamkulam 38 TCR-3105 NBPGR Regional Station, Vellanikkara 19 AVTS.06.6 ORARS, Kayamkulam 39 TCR-4865 NBPGR Regional Station, Vellanikkara Author Draft 4Genetic Variability and Diversity Analysis in Sesame (Sesamum indicum L.) Sl. No. Genotype Source Sl. No. Genotype Source 20 AVTS.06.7 ORARS, Kayamkulam 40 YLM-17 Krishi Bhavan, Alathur Table 1: List of sesame genotypes studied The experiment was conducted during October 2007 to February 2008 at the Department of Plant Breeding and Genetics, College of Horticulture, Vellanikkara. Seeds were sown in a randomized complete block design with three replications. Plot dimensions maintained a spacing of 45 cm between rows and 20 cm between plants, following standard agronomic practices for the region.Observations were recorded on ten randomly tagged plants per genotype for nine quantitative characters: days to flowering, plant height (cm), number of branches per plant, number of capsules per plant, capsule length (cm), number of locules per capsule, 1000-seed weight (g), seed yield per plant (g), and oil content (%). 3. Results Analysis of variance in Table 2revealed highly significant differences (P < 0.01) among genotypes for days to flowering, plant height, and number of capsules per plant, indicating substantial genetic variation suitable for breeding programs. Source df 𝑋1𝑋2𝑋3𝑋4𝑋5𝑋6 Replication 2 1.66 0.09 0.19 20.96* 0.29 0.20 Treatment 39 32.34** 1153.46** 12.47 255.09** 4.31 3.30 Error 78 0.45 0.96 0.12 1.43 0.019 0.17 Table 2: Analysis of variance (ANOVA) for yield and related traits in sesame genotypes In Table 2, the traits represented by 𝑋1to 𝑋6are as follows: 𝑋1– Days to flowering 𝑋2– Plant height (cm) 𝑋3– Number of branches per plant 𝑋4– Number of capsules per plant 𝑋5– Seed yield per plant (g) 𝑋6– Oil content (%) Author Draft Journal of Sustainable Technology in Agriculture 5 Character Range Mean ± SE GCV (%) PCV (%) ℎ2(%) GA (%) ECV (%) 𝑋118.73 – 34.80 27.35 ± 0.39 11.92 12.17 95.98 24.06 2.44 𝑋231.40 – 107.97 53.44 ± 0.56 36.68 36.72 99.75 75.46 1.83 𝑋34.27 – 12.13 5.85 ± 0.20 34.67 35.15 97.28 70.45 5.79 𝑋49.96 – 50.93 24.54 ± 0.69 37.47 37.78 98.34 76.54 4.87 𝑋51.82 – 2.26 2.01 ± 0.02 5.15 5.57 85.50 9.82 2.12 𝑋64.00 – 8.00 4.05 ± 0.00 7.81 7.81 100.00 16.08 0.00 𝑋73.11 – 3.21 3.15 ± 0.02 0.91 0.97 88.30 1.76 1.04 𝑋81.35 – 7.02 3.47 ± 0.08 34.48 34.71 98.69 70.56 3.97 𝑋945.53 – 50.17 48.65 ± 0.24 2.10 2.26 85.87 4.01 0.85 Table 3: Genetic parameters for different traits in sesame genotypes In Table 3, the characters denoted by 𝑋1to 𝑋9are: 𝑋1– Days to flowering 𝑋2– Plant height (cm) 𝑋3– Number of branches per plant 𝑋4– Number of capsules per plant 𝑋5– Capsule length (cm) 𝑋6– Number of locules per capsule 𝑋7– 1000-seed weight (g) 𝑋8– Seed yield per plant (g) 𝑋9– Oil content (%) Genetic parameters include: Genotypic coefficient of variation (GCV), Phenotypic coefficient of variation (PCV), Broad-sense heritability (ℎ2), Genetic advance as percentage of mean (GA), Environmental coefficient of variation (ECV), and Standard error (SE). Considerable variation was observed across all studied traits. Days to flowering ranged from 18.73 days (KYM-1) to 34.8 days (Tilarani) with a mean of 27.35 days. Plant height showed extensive variation from 31.40 cm (IVTS-06-12) to 107.97 cm (Soma), averaging 53.44 cm. Seed yield per plant, the most variable trait, ranged from 1.35g (IVTS-06-22) to 7.02g (SVPR1) with a mean of 3.47g. Author Draft 6Genetic Variability and Diversity Analysis in Sesame (Sesamum indicum L.) The genetic parameters for the traits studied as a part of the experiment are presented in Table 3. Number of branches per plant (51.83%) and capsules per plant (43.56%) show the highest variability, indicating excellent prospects for selection and breeding. Low variability in 1000seed weight (2.95%) suggests this trait is more genetically stable across genotypes. All traits exhibited high broad-sense heritability exceeding 85%. The highest heritability was observed for locules per capsule (100%) followed by plant height (99.75%), seed yield per plant (98.69%), and number of capsules per plant (98.34%). The significant genetic variation observed across all studied traits provides a robust foundation for sesame breeding programs. High heritability estimates (>85%) for all traits indicate that observed phenotypic variation primarily reflects genetic differences rather than environmental effects, facilitating effective selection strategies (Allard 1960;Kumar and Garg 2016). The combination of high heritability with high genetic advance for days to flowering, plant height, number of branches per plant, number of capsules per plant, and seed yield per plant suggests predominant additive gene action, making these traits responsive to simple selection methods (Burton 1952;Singh and Chaudhary 2006). Genotypic correlation coefficients generally exceeded phenotypic correlations, indicating strong genetic associations among traits. Seed yield per plant showed significant positive correlations with days to flowering (𝑟 = 0.321∗), plant height (𝑟 = 0.633∗∗), number of branches per plant (𝑟 = 0.552∗∗), number of capsules per plant (𝑟 = 0.956∗∗), locules per capsule (𝑟 = 0.312∗), and oil content (𝑟 = 0.438∗∗). Trait 𝑋1𝑋2𝑋3𝑋4𝑋5 𝑋11.000 0.956** 0.633** 0.552** 0.438** 𝑋20.956** 1.000 0.625** 0.683** 0.423** 𝑋30.633** 0.625** 1.000 0.582** 0.491** 𝑋40.552** 0.683** 0.582** 1.000 0.367* 𝑋50.438** 0.423** 0.491** 0.367* 1.000 Table 4: Genotypic correlation coefficients among traits in sesame genotypes In Table 4, the traits denoted by 𝑋1to 𝑋5are: 𝑋1– Seed yield per plant (g) 𝑋2– Number of capsules per plant 𝑋3– Plant height (cm) 𝑋4– Number of branches per plant 𝑋5– Oil content (%) Correlation significance: p< 0.05 (), p* < 0.01 (**) Number of capsules per plant shows the strongest positive correlation with seed yield (𝑟 = 0.956∗∗), making it the most reliable indirect selection criterion. Plant height and branches per plant also show strong positive associations, indicating coordinated plant architecture development. The strong positive correlation between number of capsules per plant and seed yield (𝑟 = 0.956∗∗) confirms this trait as the most reliable selection criterion for yield improvement. Author Draft Journal of Sustainable Technology in Agriculture 7 Trait Direct Effect 𝑋1𝑋2𝑋3𝑋4𝑋5𝑋6𝑋7 Total Correlation 𝑋1-0.108 – - 0.016 - 0.070 0.453 - 0.032 0.001 - 0.004 0.321 𝑋20.077 - 0.023 – - 0.136 0.698 0.027 - 0.011 0.001 0.633 𝑋3-0.231 - 0.032 0.046 – 0.769 0.008 - 0.008 0.000 0.552 𝑋41.106 - 0.044 0.049 - 0.160 – 0.016 - 0.009 - 0.002 0.956 𝑋50.106 - 0.033 0.019 - 0.016 0.169 – - 0.004 - 0.002 0.240 𝑋60.022 - 0.069 - 0.004 0.019 0.109 - 0.011 – 0.004 0.109 𝑋7-0.020 - 0.004 0.041 - 0.093 0.512 0.021 0.054 – 0.469 Table 5: Direct and indirect effects of different traits on seed yield in sesame In Table 5, the traits denoted by 𝑋1to 𝑋7are: 𝑋1– Days to flowering 𝑋2– Plant height (cm) 𝑋3– Number of branches per plant 𝑋4– Number of capsules per plant 𝑋5– Capsule length (cm) 𝑋6– 1000-seed weight (g) 𝑋7– Oil content (%) Path analysis as depicted in Table 5revealed that number of capsules per plant exerted the highest positive direct effect (1.106) on seed yield per plant, followed by capsule length (0.106), plant height (0.077), and 1000-seed weight (0.022). Conversely, number of branches per plant showed the highest negative direct effect (-0.231), followed by days to flowering (-0.108) and oil content (-0.020). The residual effect was 0.203, indicating that approximately 80% of variation in seed yield was explained by the studied traits. The negative direct effect of branches per plant (−0.231) despite positive correlation suggests indirect benefits through increased capsule production. Plant height contributes mainly through indirect effects via capsule production. The analysis explains 79.66% of yield variation, indicating good model adequacy. 3.1. Genetic divergence analysis Mahalanobis 𝐷2analysis revealed that plant height contributed maximum to total divergence (69.74%), followed by days to flowering (7.56%) and seed yield per plant (6.67%). This indicates plant height as the primary discriminating factor among genotypes. Plant height is the major contributor to genetic divergence among sesame genotypes, followed by flowering time and seed yield components as depicted in Figure 1. Author Draft 8Genetic Variability and Diversity Analysis in Sesame (Sesamum indicum L.) Figure 1: Contribution of traits to total genetic divergence 3.2. Cluster analysis The 40 genotypes were grouped into six distinct clusters. Cluster I was the largest with 30 genotypes, while Clusters III, IV, V, and VI each contained single genotypes. Maximum intercluster distance was observed between Clusters III and IV (𝐷2= 75.04), indicating maximum genetic divergence between these groups. Cluster Genotypes Total Number of Genotypes I IVTS-06-2, IVTS-06-3, YLM-17, AVTS-06-6, TCR-4865, TCR-3105, VRI-2, IVTS-06-16, IVTS-06-8, AVTS-06-10, TCR-2527-C, IVTS-06-15, AVTS-06-5, AVTS-06-4, IVTS-06-6, AVTS-06-3, AVTS-06-7, AVTS-06-1, AVTS-06-1, IVTS-06-28, IVTS-06-27, IVTS-06-13, TCR-2511, IVTS-06-12, TCR-3279-A, TMV-4, TMV-5, IVTS-06-26, TMV-6, VRI-1 30 II Tilatara, CO-1, Tilak, Tilarani, TMV-3, Surya 6 III IVTS-06-22 1 IV Soma 1 V SVPR-1 1 VI KYM-1 1 Table 6: Cluster distribution of sesame genotypes based on Mahalanobis 𝐷2analysis Cluster means revealed distinct patterns across groups which are represented in Table 7Cluster VI (KYM-1) showed the earliest flowering (18.73 days) and highest oil content (50.17%), while Cluster IV (Soma) exhibited the tallest plants (107.97 cm) and maximum branches per plant (10.80). Cluster V (SVPR-1) demonstrated the highest seed yield per plant (7.02g). Author Draft Journal of Sustainable Technology in Agriculture 9 Character Cluster I Cluster II Cluster III Cluster IV Cluster V Cluster VI Days to flowering 27.17 30.77 21.41 25.73 28.13 18.73 Plant height (cm) 44.13 81.58 61.33 107.97 59.30 95.60 Branches per plant 5.20 8.39 7.34 10.80 4.73 5.00 Capsules per plant 21.42 36.07 9.96 41.20 45.43 26.07 Seed yield per plant (g) 3.07 4.59 1.36 5.77 7.02 4.79 Oil content (%) 48.35 49.54 49.33 49.23 49.53 50.17 Table 7: Cluster means for yield and related traits in sesame based on Mahalanobis D² analysis The clustering of genotypes from the same geographical origin into different groups confirms that genetic drift and selection pressure can create greater diversity than geographical separation (Pandey et al. (2015); Singh et al. (2020)). This finding has important implications for breeding programs, suggesting that local germplasm may harbor unexploited genetic diversity. Cluster V (SVPR-1) shows highest yield potential, Cluster IV (Soma) exhibits superior plant architecture, and Cluster VI (KYM-1) offers early maturity with high oil content. Strategic crosses between distant clusters (III × IV) could maximize genetic variation in breeding populations. Recent molecular diversity studies using SNP markers have corroborated these findings. Wang et al. (2016) analyzed 705 sesame accessions using genome-wide SNPs and found similar clustering patterns, with genetic diversity being more strongly associated with breeding history than geographical origin. The maximum divergence between Clusters III and IV (𝐷2= 75.04) in our study corresponds to regions of low genetic similarity identified in genomic studies (Dossa et al. 2017). Based on comprehensive evaluation, several genotypes emerged as superior performers across multiple traits as depicted Figure 2. SVPR-1 demonstrated the highest seed yield (7.02 g/plant), while KYM-1 showed the earliest flowering and highest oil content. Soma exhibited exceptional plant architecture with maximum height and branching. Discussion The combination of high heritability with high genetic advance for days to flowering, plant height, number of branches per plant, number of capsules per plant, and seed yield per plant suggests predominant additive gene action, making these traits responsive to simple selection methods (Burton 1952;Singh and Chaudhary 2006). These findings align with recent reports