STUDIES ON GENETIC DIVERGENCE AND STABILITY OF LARGE SEEDED PEANUT (Arachis hypogaea L.)
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Date
2023-12-03
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Acharya N G Ranga Agricultural University
Abstract
The present investigation entitled “Studies on Genetic Divergence and Stability of Large Seeded Peanut (Arachis hypogaea L.)” was carried out in four seasons viz., kharif 2019, summer 2020, kharif 2020 and rabi 2020-21. Observations were recorded for kernel yield and its component traits in kharif 2019 to study the genetic divergence, genetic parameters, character association and direct and indirect effects of characters on kernel yield among 65 peanut genotypes. Among sixty five lines, twenty six lines were chosen for stability analysis across seasons namely, summer 2020, kharif 2020 and rabi 2020-21 to study G × E interaction.
Analysis of variance (ANOVA) for yield and confectionery traits revealed highly significant differences among the genotypes for all characters studied in kharif, 2019. An analysis of genetic parameters reveled number of mature pods per plant, number of immature pods per plant, pod yield per plant, kernel yield per plant, 100 seed weight, free amino acids, total soluble sugars and oleic and linoleic acid ratio showed high variability (GCV and PCV), high heritability coupled with high genetic advance as per cent of mean, indicating the predominance of additive gene action in expression of these characters and direct selection will be effective in improvement of such characters.
Diversity analysis showed that linoleic acid content contributed maximum variation to total variation. The 65 genotypes were divided into 10 clusters, with cluster IV having the highest number of genotypes (28) and clusters VI, VII and X had only single genotype. Maximum inter cluster D2 value was observed between cluster IX and cluster X. Cluster VI, VII, VIII, IX and X recorded high cluster mean values for most of the yield contributing and quality characters. PCA analysis revealed first five principal components PC 1 to PC 5 accounted more than 92 % of the entire variation and have latent roots greater than one. Results obtained from individual PCA (vectors X, Y, Z) and 3D plot graphed based on PCA loading scores (vectors X, Y, Z) of 65
peanut genotypes revealed that genotypes ICGV 03137 (cluster X), ICGV 171002 (cluster IX), ICGV 171004 (cluster IX) and ICGV 94215 (cluster VIII) were scattered relatively far away from other genotypes in this plot which indicates that they were more divergent and also confirming the Tocher‟s clustering. Intercrossing genotypes included in these clusters could be effective for creating variability in the respective traits.
Character association revealed plant height, number of secondary branches per plant, number of mature pods per plant, number of immature pods per plant, pod yield per plant, 100 seed weight and protein content were recorded significant positive association with kernel yield per plant both at genotypic and phenotypic levels. On the other hand, character like days to 50 % flowering showed significant negative correlation with kernel yield per plant at phenotypic level but non-significant at genotypic level. Path coefficient analysis revealed number of mature pods per plant, 100 seed weight, number of secondary branches per plant and sound mature kernel per cent were leading in determining the kernel yield of peanut through direct positive effects and indirect positive effects via different yield attributing traits.
Molecular diversity analysis revealed a total of 17 bands or DNA fragments found to be polymorphic and mean number of polymorphic bands per primer was 2.83. PIC values ranged from 0.423 for primer EM 18 to 0.742 for S 109 with an average of 0.572. The dendrogram analysis divided the total 65 genotypes into 10 diverse sub clusters. The grouping pattern of both PCA (4 groups) and PCoA (3 groups) very nearer to the dendrogram obtained through UPGMA based cluster analysis.
The ANOVA of Eberhart and Russell model revealed significant differences among genotypes for all traits which indicates the presence of substantial variation in the per se performance of all the 26 peanut genotypes. Significant differences due to environments were observed for all traits except shelling percentage and palmitic acid content indicating that the environments in which the genotypes evaluated were quite variable. The environments + (genotypes × environments) interaction was also observed to be significant for all traits studied except for 100 seed weight and palmitic acid content indicating considerable interactions of genotypes with environments (seasons). Significant genotype × environment interactions (GEI) were recorded for all traits except for days to 50 % flowering, days to maturity and 100 seed weight which inferred that differential performance of peanut genotypes under diverse environments. Mean sum of squares due to environment (linear) were found to be significant for all traits except for palmitic acid content.
Environmental index (I) revealed the fittingness of an environment for different traits of peanut. Plant height, number of primary branches per plant, number of secondary branches per plant, number of mature pods per plant, pod yield per plant, kernel yield per plant, sound mature kernel per cent and 100 seed weight were recorded higher positive values of environmental index in kharif season indicating that kharif
season was congenial for most of the yield contributing traits than summer and rabi seasons.
On the basis of stability parameters, none of the genotypes were stable for all the traits across the environments (seasons). Genotypes viz., ICGV 171334, ICGV 98432 and ICGV 99105 were observed to be stable across the seasons for high pod and kernel yield in conjunction with confectionary traits like 100 seed weight, protein content and oleic linoleic acid ratio.