Background: A complex quantitative characteristic yield is heavily impacted by the environment. The productivity of groundnut can be increased less effectively through direct selection for grain yield. The current study aimed to study the variation among diverse groundnut genotypes. Methods: Phenotypic data was collected on seven quantitative and six qualitative characters for 24 genotypes under study carried out in randomised block design (RBD). GRAPES software has been used for analysis. Result: Analysis of variance revealed significant differences among the genotypes for all the characters indicating the prevalence of ample genetic variability within the genotypes. Significant positive associations were observed for primary branches, secondary branches, 100-pod weight, shelling per cent, protein and zinc content. Path analysis revealed that plant height, primary branches per plant, hundred pod weight, shelling percent, protein content and zinc content are the most important characters which could be used as selection criteria for effective improvement of pod yield. Using GRAPES software, Fourteen Principal components are extracted based on mean values of which the first five PCs showed 73.24% variation with eigen values more than 1. Biplot constructed by Principal component analysis revealed Hundred pod weight and hundred kernel weight as important traits for study.
Background: A complex quantitative characteristic, yield is heavily impacted by the environment. The productivity of groundnuts can be increased less effectively through direct selection for grain yield. The study aimed to determine the genetic diversity. Methods: The Mahalanobis D2 statistic was used to quantify the genetic diversity among 24 genotypes of groundnut for seven quantitative and six qualitative criteria. Result: There is sufficient diversity among genotypes, as evidenced by the fact that all of the features in the ANOVA showed significance. High GCV and PCV values were seen for the traits primary-branches/plant (PB), secondary-branches/plant (SB), pod yield/plant (PY), sucrose content (SC), total free aminoacids (TFA), total soluble solids (TSS) and iron content (IC), demonstrating that these traits were well chosen. High heritability and genetic progress as a percentage of mean were observed for plant height, PB, SB, PY, Hundred-pod weight (100-PW), SC, TFA, TSS and IC, demonstrating additive gene-action is in charge of these traits. Twenty-four genotypes were divided into nine clusters using Tocher’s method of clustering, with cluster I being the biggest with sixteen genotypes. Cluster VII and Cluster IX had the greatest inter-cluster distance, which showed that their individuals were more diverse (26.91). In order to obtain transgressive segregants for yield and yield parameters, taking into consideration the cluster distances and cluster means in the current experiment, an emphasis should be focused on establishing crossings between genotypes from clusters VII and VIII that are promising.
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