Article Abstract

Volume 26, No. (6), 2016 (December)
SELECTION CRITERIA OF LINSEED GENOTYPES FOR SEED YIELD TRAITS THROUGH CORRELATION, PATH COEFFICIENT AND PRINCIPAL COMPONENT ANALYSIS
N. Kumar and S. Paul

N. Kumar* and S. Paul

Department of Crop Improvement, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur-176062, India

Corresponding Author: nk.kakran@gmail.com
DOI: NA
Page Number(s): 1688-1695
Published Online First: December 01, 2016
Publication Date: December 01, 2016
ABSTRACT

Twenty five linseed genotypes were evaluated to determine the selection criteria and interrelationships of seed yield and yield related traits, during rabi 2013-14 at the Department of Crop Improvement, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur, Himachal Pradesh, India. Genotypic and phenotypic correlation coefficients obtained between different traits was similar in direction, while in magnitude, the genotypic correlations were higher than the corresponding phenotypic correlations. Seed yield per plant had significant and positive association with biological yield per plant, straw yield per plant, fibre yield and 1000 seed weight. Path analysis demonstrated that biological yield per plant showed higher and positive direct effect on seed yield per plant indicating selection for this character would lead to increase of yield. Straw yield per plant, fibre yield and 1000 seed weight contributed indirectly through biological yield per plant. Conformingly, the principal component analysis (PCA) showed that biological yield per plant, straw yield per plant, fibre yield and 1000 seed weight had the most contributions, interpreting almost all the variation of traits. Indeed, to simultaneously breed of high yielding linseed varieties, biological yield per plant should firstly be considered followed by straw yield per plant, fibre yield and 1000 seed weight.

Keywords: Linseed, correlation, path coefficient analysis, principal component analysis, yield components
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Cite Score: 1.3

JCR Year: 2025

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Print ISSN: 1018-7081

Electronic ISSN: 2309-8694

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