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Vol. 11, Issue 11 (2022)

Principal component analysis for yield and yield attributes in black pepper (Piper nigrum L.)

Author(s):
Reshma P, Sreekala GS, Nainu Joseph, Deepa S Nair, Roy Stephen and Thomas George
Abstract:
Genetic variability is a pre-requisite for the selection of superior genotypes in any crop. Knowledge of variability and its contributing traits helps in the selection of an appropriate strategy for a breeding programme for evolving superior varieties. Therefore, the present investigation was conducted to assess the variability present in black pepper for yield and yield contributing traits. Twenty one black pepper cultivars were studied for 22 quantitative traits and summarized using principal component analysis. The first six principal components (PC1, PC2, PC3, PC4, PC5 and PC6) having eigen values greater than one accounted for 83.93% of total variability and individual variability of 28.92, 22.05, 10.86, 9.38, 6.74 and 5.99% for the respective principal components. The strongest positive correlations are obtained between lateral branch length and number of nodes lateral branch-1, juvenile leaf length and leaf length, juvenile leaf length and leaf width, leaf petiole length and spike length, spike length and number of well-developed berries spike-1, number of spikes 30 cm-2 and number of spikes vine-1, fresh berry yield and dry yield, and fresh spike yield and dry yield. In black pepper, lateral branch length, leaf petiole length, leaf width, number of spikes lateral branch-1, number of spikes vine-1, fresh spike yield, fresh berry yield, hundred fresh berry weight, hundred fresh berry volume and dry recovery can be considered for selecting genotypes with high yield.
Pages: 1055-1062  |  262 Views  126 Downloads


The Pharma Innovation Journal
How to cite this article:
Reshma P, Sreekala GS, Nainu Joseph, Deepa S Nair, Roy Stephen, Thomas George. Principal component analysis for yield and yield attributes in black pepper (Piper nigrum L.). Pharma Innovation 2022;11(11):1055-1062.

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