Characterization of black pepper (Piper nigrum L.) varieties and landraces/farmers selections for spike and berry traits

Abstract

Statistical tools such as analysis of variance, correlation, path coefficient analysis, Scott-Knott test and principal component analysis were used in the present study to characterize black pepper verities/hybrids for spike and berry traits. ANOVA indicated that fifteen traits under study were statistically significant. Traits like fresh pericarp weight and dry pericarp weight showed high positive correlation (>0.95) with spike weight. Path coefficient analysis revealed that berry weight and seed size are contributing directly to spike weight. Scott-Knott test identified Panniyur-1 and Nedumchola as the most contrasting genotypes for most number of traits studied. Based on Principal Component Analysis (PCA), first three principal components had an eigen value above unity and explained 88 per cent of cumulative variation. Principal component PC-1 accounted for maximum variation of about 42.4 percent which discriminated the genotypes based on fresh berry weight, dry seed weight and fresh pericarp weight. These traits serve as the selection criteria for improvement of yield in black pepper.