Delineating the genetic variability, correlation, path and principal component analysis in brinjal genotypes

An experiment was conducted to evaluate 25 different brinjal genotypes for growth and yield-contributing traits. Variability analysis, association studies and Principal Component Analysis (PCA) were performed to explore the relationships among traits and identify significant factors influencing performance. In the present study, high genotypic and phenotypic coefficient of variation values were observed for fruit breadth, fruit weight gram per fruit, number of fruits per plant and fruit weight gram per plant. In contrast, traits such as days to fifty per cent flowering, plant height, number of branches per plant, branch length, fruit length and fruit borer infestation exhibited medium GCV and PCV values. High heritability coupled with high GAM was noticed for all the traits. Correlation analysis on the number of fruits per plant recorded a positive and significant association with fruit weight per gram. The higher magnitude of a positive direct effect on fruit yield was exerted by the number of fruits per plant followed by fruit weight gram per fruit, plant height and fruit breadth. Principal component analysis showed three principal components with unity eigenvalues, accounting for 78.647 % of total variance. Principal Component 1 (PC1) contributed a high proportion of total variance (42.282) with an eigenvalue of 4.228. PC2 and PC3 showed total variance percentages of 24.045 and 12.32 with the eigenvalues 2.404 and 1.232, respectively.

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Journal
Plant Science Today
Published
2024-12-21
DOI
https://doi.org/10.14719/pst.5756
Citations
1
Primary Topic
Agricultural Practices and Plant Genetics
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article
Field-Weighted Citation Impact
0.60
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article

Delineating the genetic variability, correlation, path and principal component analysis in brinjal genotypes

I. Muthuvel, K. A. Shanmugasundaram
1 citations
Plant Science Today
Agricultural Practices and Plant Genetics
0.60
article

Delineating the genetic variability, correlation, path and principal component analysis in brinjal genotypes

I. Muthuvel, K. A. Shanmugasundaram
article en
1 citations

Abstract

An experiment was conducted to evaluate 25 different brinjal genotypes for growth and yield-contributing traits. Variability analysis, association studies and Principal Component Analysis (PCA) were performed to explore the relationships among traits and identify significant factors influencing performance. In the present study, high genotypic and phenotypic coefficient of variation values were observed for fruit breadth, fruit weight gram per fruit, number of fruits per plant and fruit weight gram per plant. In contrast, traits such as days to fifty per cent flowering, plant height, number of branches per plant, branch length, fruit length and fruit borer infestation exhibited medium GCV and PCV values. High heritability coupled with high GAM was noticed for all the traits. Correlation analysis on the number of fruits per plant recorded a positive and significant association with fruit weight per gram. The higher magnitude of a positive direct effect on fruit yield was exerted by the number of fruits per plant followed by fruit weight gram per fruit, plant height and fruit breadth. Principal component analysis showed three principal components with unity eigenvalues, accounting for 78.647 % of total variance. Principal Component 1 (PC1) contributed a high proportion of total variance (42.282) with an eigenvalue of 4.228. PC2 and PC3 showed total variance percentages of 24.045 and 12.32 with the eigenvalues 2.404 and 1.232, respectively.

Plant Science TodayVol. 11(sp4)
Tamil Nadu Agricultural University (IN)
Openalex Percentile: Top 20%
Agricultural Practices and Plant Genetics
0.60
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Delineating the genetic variability, correlation, path and principal component analysis in brinjal genotypes — I. Muthuvel, K. A. Shanmugasundaram · Plant Science Today (2024) | TGRS Research Map | TGRS