Association and diversity analysis for yield attributing traits in advance generation of green gram (Vigna radiata (L.) Wilczek)

Goyal, Lakshay; Intwala, CG; Modha, Kaushal; Acharya, Vishwas R

doi:10.22271/chemi.2021.v9.i1aa.11504

Cited by 3 publications

(4 citation statements)

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“…These results were in conformity with earlier report of Ahmad et al [5]. Goyal et al [6] for 100-seeds weight and number of pods per plant. While, negative direct effect on seed yield per plant were contributed through number of clusters per plant, days to 50 % flowering and plant height at genotypic level, indicating that the selection for these traits may have an undesirable impact on seed yield.…”

Section: Resultssupporting

confidence: 93%

Path Coefficient Analysis to Evaluate Seed Yield in Green Gram [Vigna radiata (L.) R. Wilczek]: A Comprehensive Study

Harsh,

Priyal,

Chhodavadiya

et al. 2024

IJECC

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The current empirical study on "path coefficient analysis to evaluate seed yield in green gram [Vigna radiata (L.) R. Wilczek]: a comprehensive study" was conceded to assess path analysis in 72 genotypes of green gram. On 11 traits, observations were recorded. The genotypic path coefficient analysis revealed that the number of pods per plant, 100-seeds weight and number of seeds per pod expressed positive and higher direct effect on seed yield per plant. The phenotypic path coefficient analysis revealed that the number of pods per plant, 100-seeds weight and number of seeds per pod exhibited high and positive direct effects on seed yield per plant. Whereas, negative direct effect on seed yield per plant were contributed through number of clusters per plant and plant height at phenotypic level. The residual effect was found to be 0.0755 and 0.1321 at genotypic and phenotypic path coefficient analysis respectively.

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Section: Resultssupporting

confidence: 93%

Path Coefficient Analysis to Evaluate Seed Yield in Green Gram [Vigna radiata (L.) R. Wilczek]: A Comprehensive Study

Harsh,

Priyal,

Chhodavadiya

et al. 2024

IJECC

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“…Overall, the genotypic correlation coefficients were higher than phenotypic correlation coefficients revealing that there is strong inherent association between different pairs of characters in greengram genotypes.The present studies were collaborated with the findings of the earlier researchers (Tejaswini et al, 2022 andGoyal et al, 2021) In table 1 the present study of phenotypic correlation, the most important trait seed yield per plant displayed significant and positive phenotypic correlation with number of clusters per plant, number of pods per plant, number of seeds per pod, 100 seed weight, harvest index and seed protein content and had exhibited significant and negative correlation with days to 50% flowering, days to maturity and plant height.…”

Section: Correlation Coefficient Analysissupporting

confidence: 78%

Section: Correlation Coefficient Analysissupporting

confidence: 64%

Studies on Character Association and Path Coefficient Analysis for Yield and Yield Related Traits in Greengram [Vigna Radiata (L.) Wilczek]

MISHRA,

SHWETA,

RATHORE

et al. 2023

AJMBES

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Genetic association and path coefficient analysis were studied at phenotypic and genotypic levels in 19 genotypes of greengram for various quantitative characters during kharif 2022. The experimental design which was used to conduct the experiment was a randomized block design. Analysis of variance revealed highly significant differences among the genotypes for all the characters under study indicating the presence of adequate variability among the varieties. Estimates of phenotypic coefficient of variation (PCV) were higher than genotypic coefficient of variation (GCV) for all characters. High heritability was observed with high genetic advance as mean percentage by 100 seed weight, biological yield and harvest index. Number of clusters per plant, number of pods per plant, number of seeds per pod, 100 seed weight, harvest index and seed protein content showed significant and positive phenotypic correlations in seed yield per plant. Specific seed yield per plant showed significant and positive genotypic correlation with number of clusters per plant, number of pods per plant, number of seeds per pod, 100 seed weight, harvest index and seed protein content. High magnitude of positive direct effect at phenotypic level on grain yield per plant was shown by number of clusters per plant, number of pods per plant, pod length, number of seeds per pod, 100 seed weight, biological yield, harvest index and seed protein. High intensity of positive direct effect at genotypic level on seed yield per plant, number of clusters per plant, harvest index, biological yield, plant height and number of pods per plant was applied by material.

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“…Clusters IV and VII had the greatest intercluster distance (D 2 = 40.51) indicating, wide diversity between them and the hybridization between genotypes belonging to cluster IV and cluster VII (Hum-1) may lead to formation of superior recombinants. Findings of Goyal et al (2021) showed highest inter cluster distance in cluster II and cluster IV. Gadakh et al .20 DF (days to 50% flowering), DM (days to maturity), LL (leaf length), PH (plant height), PL (pod length), NPB (number of primary branch), NCPP (number of clusters per plant), NPPC (number of pods per cluster), NPPP (number of pods per plant), NSPP (number of seeds per pod), SI (seed index), HI (harvest index), BYPP (biological yield per plant), SYPP (seed yield per plant) (2013) reported that the genotypes from cluster III and cluster IV may be utilized in hybridization programme as they had highest intercluster distance.…”

Section: Genetic Divergencementioning

confidence: 95%

Multivariate analysis for study of genetic divergence in mungbean [Vigna radiata (L.) Wilczek] genotypes

Rahangdale,

Lakhani,

Singh

et al. 2023

ECJ

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Forty mungbean genotypes were evaluated for fourteen quantitative traits, planted in Randomized Complete Block Design with three replications. Mahalanobis' generalised distance D2 was used to assess the character data and Principal Component Analysis for estimating genetic diversity and identification of superior mungbean genotypes. Following Tocher's technique, the 40 genotypes were divided into 7 clusters in accordance with their genetic distance. Among them four clusters were polygenotypic and three were monogenotypic. The genotypes of cluster IV and VII showed highest (40.51) inter cluster distance followed by cluster III and VII (39.04). Cluster V has been discovered to have the largest intra-cluster distance. In order to increase the genetic diversity of Vigna radiata, genotypes from these clusters may be crossed. Based on Principal Component Analysis results, 5 PCs explained 75.87% of the variation among the 14 parameters and had eigen values greater than unit. Only six genotypes—TJM-37, TJM-134, TJM-140, TJM-235, Shikha, and PM-1632—contained with favourable yield and quality associated PCs, and had outstanding remark for yield traits—out of all genotypes contributing their existence in more than one PC with high PC score. These lines may be used in hybridization programmes to transmit desirable features, such as high yield and high quality, to recipient mungbean genotypes, resulting in the creation of promising cultivars.

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Association and diversity analysis for yield attributing traits in advance generation of green gram (Vigna radiata (L.) Wilczek)

Cited by 3 publications

References 0 publications

Path Coefficient Analysis to Evaluate Seed Yield in Green Gram [Vigna radiata (L.) R. Wilczek]: A Comprehensive Study

Path Coefficient Analysis to Evaluate Seed Yield in Green Gram [Vigna radiata (L.) R. Wilczek]: A Comprehensive Study

Studies on Character Association and Path Coefficient Analysis for Yield and Yield Related Traits in Greengram [Vigna Radiata (L.) Wilczek]

Multivariate analysis for study of genetic divergence in mungbean [Vigna radiata (L.) Wilczek] genotypes

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