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.
Rice (Oryza sativa L.) improvement depends on the effective utilisation of diverse germplasm and the identification of key yield-contributing traits. The present study evaluated 25 genetically diverse rice germplasm accessions during Kharif 2025 using multivariate genetic diversity, DUS-based morphological characterisation, correlation, and path coefficient analyses. The experiment was conducted in a CRBD with three replications, and observations were recorded for 10 qualitative and 11 quantitative traits. Analysis of variance revealed highly significant differences among the genotypes for all quantitative traits, indicating substantial genetic variability. Grain yield per plant exhibited a strong positive association with biological yield per plant (r = 0.99) at both the genotypic and phenotypic levels. Path coefficient analysis identified biological yield per plant (0.92) as the most influential trait, with the highest positive direct effect on grain yield. Mahalanobis D² analysis grouped the genotypes into six distinct clusters, with the maximum inter-cluster distance observed between Clusters II and VI (44.21), indicating their potential value in hybridisation programmes. DUS characterisation revealed considerable qualitative variation that facilitated varietal identification and germplasm differentiation. The findings identified promising and genetically diverse germplasm accessions that may provide useful parental material for yield improvement and the broadening of the genetic base of future rice-breeding populations.
Dhamarasingu Gayathri, A. Pandey, Madduri Usha Sri et al.· International Journal of Pla...· 0 citations
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