Assessment of Selection Criteria in Sesame by using Correlation and Path Coefficient Analysis under High Moisture and Acidic Stress Soil Condition

Abstract

Background/Objectives: To evaluate and identify the selection criteria of high yielding genotypes of sesame in high moisture and acidic soil conditions in north east India. Methods/Statistical Analysis: Hundred diverse accessions of Sesamum indicum L. were investigated in Kharif 2014 at CSIR-NEIST Jorhat. Relationships were determined between single plant seed yield (g) and leaf nodes per plant, number of pods per plant, number of pods per main stem, breadth of pod, number of seeds per pod, 1000-seed weight and number of seeds per plant. Simple phenotypic correlation coefficients among all observed components were first calculated by the SPSS statistical program (version 10) and later separated into direct and indirect effects through path coefficient analyses as suggested by Singh and Chaudhary13. Path coefficients were estimated by following Dewey and Lu5. Findings: Analysis of variance revealed significant difference among genotypes for all the characters studied. Seed yield per plant showed significant and positive association with number of pods/plant, days to maturity and number of seeds/pod. Path coefficient analyses showed number of pods/plant had maximum direct effect on seed yield followed by breadth of pods, days to maturity and number of pods on main stem. It could be concluded that the number of pods per plant, days to maturity and number of pods on main stem are promising good selection criteria for single plant seed yield improvement in sesame. Application/Improvements: This analysis proposed that sesame breeding for higher yield could be based on these characters as selection criteria.