Aug 2026· Legume Research An International Journal· 0 citations· 18 references
Abstract
Background: Chickpea (Cicer arietinum L.) classified as one of the greatest prominent pulse crops in India and contributes substantially to nutritional security through its high protein content. Genetic improvement of chickpea requires comprehensive knowledge on degree of the variability available within breeding materials and connection among different genotypes facilitates identification of promising parents and effective selection process. Keeping in view, the present study was done to examine the heritability, genetic variability, genetic divergence and trait associations among forty one chickpea genotypes in the agroclimatic circumstances of western Uttar Pradesh. Methods: The experiment was conducted on 41 genotypes of chickpea in research farm of Department of Genetic and Plant Breeding, CCS University Meerut (UP) India. Each genotype was sown during rabi season 2021-22 utilizing Randomize block design involving three replications. Five plant were randomly selected were utilized to record data for every genotype in each replication, covering the eleven characteristic traits that were being studied. Result: ANOVA demonstrated sufficient variability among the all evaluated genotypes for each trait. The highest GCV and PCV estimates were found for no. of seeds/plant, number of pods plant, hundred seeds weight, seed yield per plant, biological yield/ plant, branches/plant, total seeds/ pods, plant height. Heritability (bs) with GA as % of mean was highest for number of seeds/plant, followed by pods/plant, biological yield/plant, 100 seed weight, seed yield/plant, no. of seeds/pod. Correlation result demonstrate the number of seeds per plant significant positive associated with seed/ plant, pods/plant, harvest index, primary branches/plant, no. of seeds/pod, biological yield/plant. Path analysis demonstrated the harvest index, biological yield, no. of seed/pod and plant height exerted greatest positive direct effects on seed yield. In contrast, hundred seed weight, branches/plant, total seeds/plant, pods/plant revealed negative direct effect on seed yield. The intra cluster distance ranged from 2.261 to 2.918 in cluster I and III, respectively. Between cluster III and II showed high inter cluster distance in compression to between cluster I and III, cluster I and II. The genotypes RHD-52, BG-372, JG-2001-115 and K-1065 were identified as suitable for early flowering and maturity, whereas JG-226, DC-18-1107, ICC-8948, JG-2001-115, ICC-7549 and P-1106 were found superior for seed yield performance.
The present study was conducted using different chickpea genotypes during the Rabi 2022–23 season at the Field Experimentation Centre, Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Uttar Pradesh. The experiment was laid out in a randomised block design with three replications to estimate genetic variability parameters and conduct correlation and path analyses for thirteen quantitative traits. Analysis of variance indicated highly significant differences among the genotypes at the 1% probability level for all traits. Phenotypic coefficients of variation (PCV) were higher than genotypic coefficients of variation (GCV) for all traits, indicating environmental influence. Most traits exhibited high heritability, except days to 50% flowering. High heritability coupled with high genetic advance as a percentage of the mean was observed for the number of primary branches, number of secondary branches, number of pods per plant, pod length, number of seeds per pod, biological yield per plant, seed index and harvest index. Correlation and path coefficient analyses indicated that plant height, days to maturity, number of seeds per pod, biological yield per plant, seed index and harvest index had positive direct relationships with seed yield per plant. These findings indicate that effective selection based on these traits may improve chickpea seed yield.
Surbhi Gour, G. M. Lal, Aditya Mohan Maharishi et al.· Plant cell biotechnology and...· 0 citations
Tomato (Solanum lycopersicum L.) is an important vegetable crop valued for its nutritional quality, wide adaptability and economic significance. The present study was conducted to evaluate genetic variability, character association and genetic diversity among tomato accessions for yield and its contributing traits. The experiment was carried out during the spring-summer season of 2020 and 2021 at the experimental field of horticulture, School of Agriculture, Lovely Professional University. A total of 26 tomato accessions, comprising 6 repatriated genotypes and 20 hybrids developed through a full diallel mating design, were evaluated in a randomised complete block design (RCBD) with 3 replications and 15 quantitative and quality-related characters. Significant variation was found among the different germplasms for all characters. Yield and yield contributing characters showed high heritability along with genetic gain, indicating major role of these characters in expression of these characters. Yield per plant exhibited a strong and positive relationship with number of fruits per plant, fruit width, fruit length and mean fruit weight. Path coefficient analysis indicated that the number of fruits per plant and reducing sugar content exerted the highest positive direct influence on yield. Principal component analysis explained 81.70 % of the total variation through five components. Cluster analysis grouped accessions into two major clusters irrespective of geographic origin, indicating wide genetic diversity. Accessions T10 and F1022 were identified as the most divergent and may serve as promising parents for yield improvement in tomato breeding programs.
S. Vinit, K. Khushboo, T. Nikhil et al.· Plant Science Today· 0 citations
Aim: This study assessed SSR-based genetic diversity among 75 chickpea (Cicer arietinum L.) genotypes to identify genetically diverse parental resources for chickpea improvement.
Study Design: Laboratory-based molecular characterisation and genetic diversity analysis using SSR markers followed by similarity and cluster analyses.
Place and Duration of Study: Molecular Biology Laboratory, Department of Biotechnology, College of Agriculture, Vijayapur, University of Agricultural Sciences, Dharwad in 2021.
Methodology: Seventy-five chickpea genotypes were characterised using 20 polymorphic SSR markers distributed across the genome. Genomic DNA was extracted from young leaf samples using the CTAB method, followed by PCR amplification and separation of SSR products on 3% agarose gels. The amplification profiles were scored as binary data and used to estimate genetic similarity based on the Nei and Li coefficient. Genetic relationships were assessed through UPGMA cluster analysis using NTSYSpc and marker informativeness was evaluated using polymorphic information content (PIC).
Results: The 20 SSR markers generated a total of 73 alleles across the 75 chickpea genotypes, with an average of 3.65 alleles per marker. The number of alleles per marker ranged from 1 to 6, with TA22, TA28 and TA29 exhibiting the highest allelic variation (6 alleles each). PIC values ranged from 0.419 (TA194) to 0.797 (TA28), with 17 markers recording PIC values above 0.50, indicating their high discriminatory potential. UPGMA cluster analysis grouped the genotypes into 23 distinct clusters, with Cluster II being the largest (29 genotypes), followed by Cluster I (10 genotypes), while the remaining clusters comprised fewer or single genotypes, reflecting substantial genetic differentiation among the genotypes.
Conclusion: The SSR markers effectively revealed substantial genetic diversity and distinct molecular relationships among the chickpea genotypes. The identified genetically diverse genotypes can be utilised as promising parents to broaden the breeding base and develop diverse populations for improving chickpea productivity and adaptability.
Maize (Zea mays L.) is a leading cereal crop whose genetic improvement depends largely on the availability of diverse and divergent parents. The present investigation was undertaken to assess the mean performance and to quantify the genetic divergence among thirty maize inbred lines for sixteen quantitative characters. The experiment was conducted during the Kharif season of 2023–24 at the Research Farm of the Faculty of Agriculture Science and Technology, AKS University, Satna (M.P.), India, using a randomised complete block design with three replications. Analysis of variance revealed highly significant differences among the genotypes for all sixteen characters, and wide ranges were recorded, particularly for grain yield per plant (108.69–223.99 g), flag leaf length and shelling percentage, indicating the presence of substantial genetic variability. Genetic divergence was estimated using Mahalanobis’ D² statistic, and the genotypes were grouped into four clusters by the non-hierarchical Euclidean clustering method. Clusters I and IV were the largest, each comprising ten genotypes, whereas Clusters II and III contained five genotypes each. The maximum inter-cluster distance was observed between Clusters II and III (55.18) and the minimum between Clusters I and IV (22.00). Cluster I recorded the highest mean grain yield per plant, Cluster II the tallest plants and highest test weight, and Cluster IV the highest shelling percentage with the earliest flowering, although the clusters differed only modestly in mean performance for most yield components. The genotypes HKL-163, AMI-106 and AMI-118 emerged as the most promising parents. Hybridisation between genotypes drawn from the divergent Clusters II and III is suggested for exploiting heterosis and recovering desirable transgressive segregants in maize.
Vijay Anjana, Brindaban Singh, Rajbeer Singh Gaur et al.· Plant cell biotechnology and...· 0 citations
Genetic variability and trait associations are essential for improving fruit yield in okra (Abelmoschus esculentus (L.) Moench). The present study was conducted during Kharif 2025 at the Research Farm, Department of Genetics and Plant Breeding, AKS University, Satna, Madhya Pradesh, to evaluate 17 diverse okra genotypes using a randomised block design with three replications. Thirteen quantitative traits were recorded and analysed for genetic variability, heritability, genetic advance, correlation, and path coefficient analysis. Significant differences among genotypes for most traits indicated considerable genetic variability. The phenotypic coefficient of variation was higher than the genotypic coefficient of variation for all traits, reflecting environmental influences on trait expression. High heritability coupled with high genetic advance was observed for days to 50% flowering, days to first flowering, days to first picking, and plant height, suggesting the predominance of additive gene action. Fruit yield per plant showed significant positive associations with the number of fruits per plant, fruit width, fruit weight, days to first picking, and days to 50% flowering. Path coefficient analysis revealed that days to first flowering had the highest positive direct effect on fruit yield, followed by plant height and fruit width. These traits may therefore serve as useful selection criteria for improving fruit yield and developing high-yielding okra cultivars.
Improving Kabuli chickpea (Cicer arietinum L.) productivity requires the identification of genetically diverse, high-yielding varieties. This study assessed genetic variability, trait associations, and superior varieties for breeding in Ethiopia. Thirteen Kabuli chickpea varieties were evaluated at Wegdi and Legambo districts using a randomized complete block design with three replications. Grain yield and related agronomic traits were analyzed using analysis of variance, genetic parameter estimation, correlation, and path coefficient analyses. Highly significant (P < 0.01) differences were observed among varieties for all traits, indicating substantial genetic variability. Broad-sense heritability ranged from 82.21% to 97.47%, suggesting strong genetic control. Grain yield showed positive associations with several yield-related traits. Path analysis identified traits with positive direct effects on yield, highlighting their importance as selection criteria. Qobo (4153 and 3932 kg ha⁻¹), Kasech (3839 and 3767 kg ha⁻¹), Qoqa (3673 and 3543 kg ha⁻¹), and Akuri (3083 and 2883 kg ha⁻¹) consistently produced the highest yields across locations. High genetic variability and heritability indicate strong potential for yield improvement. Qobo, Kasech, Qoqa, and Akuri are promising varieties for cultivation and use in chickpea breeding programs.
