Principal Component Analysis Approach for Yield Attributing Traits in Okra (Abelmoschus esculentus L.) Genotypes

Abstract

The research work was investigated among 55 okra accessions in RCBD with three replications and was evaluated for seventeen phenotypic characteristics of okra principal component analysis at the Agriculture Research Farm, Lovely Professional University, Phagwara (Punjab). According to principal component analysis (PCA), six of the seventeen (PC1 to PC6) PCs had eigenvalues above 1.0 and a cumulative variance of around 75.52.  PC 1 alone accounted for the highest variance of 25.38 by PC1, followed by PC 2 with 15.98%. The outcomes of this investigation might be used as a foundation for defining and implementing subsequent okra breeding initiatives. Days to the 1^st flowering, days to the 50% flowering and days to the first fruit harvest appear above the average variance contribution of each PC in the screen plot. Biplot analysis of PC1 and PC2 in contribution dim.1 revealed 25% and dim.2 revealed 16%.