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Research Article Open access CC BY 4.0

Genetic Variability and Association Analysis of Lisianthus (Eustoma grandiflorum (Raf) Shinn) Advanced Lines Under Mid Hill Conditions of Himachal Pradesh, India

M. R. Dhiman, Raj Kumar, Chander Parkash, Sandeep Kumar

International Journal of Environment and Climate Change · pp. 104–115 · Published 15 Mar 2022

10.9734/ijecc/2022/v12i530679

Abstract

The present investigation was designed to assess the extent of variability, genetic advance, heritability and interrelation of different traits of 19 lisianthus genotypes at ICAR-IARI Regional Station, Katrain, Kullu, HP during 2019–2021. The mean performance of different genotypes exhibited considerable range together with large value for most of the characters. The trend of variability at genotypic level was similar to that of at phenotypic for some of the characters. The path analysis clearly indicated that total number of flowers per plant was directly associated with plant height and number of shoots per plant. It is imperative that these traits should be prioritized while improving number of flowers per plant in lisianthus. The cluster analysis revealed existence of diversity among the evaluated genotypes. The first principal component analysis (PCA) score explained 33.798% of the total variation mainly associated to genotype and flower yield. The PCA biplot was effective in showing the genetic distance among the genotypes and their discrimination based on key traits of importance in lisianthus. Genotypes Ktlis-1, Ktlis-17, Ktlis-5, Ktlis-9 and Ktlis-7 were superior among the tested genotypes therefore could be exploited in lisianthus breeding to improve flower yield. Hence, the characters showing high heritability along with high genetic gain should be given due attention in the development of desirable genotypes through simple selection. Further, Genotypes from different clusters identified for specific characters may be used as parent for lisianthus breeding programme with an objective to improve the specific traits.

Lisianthus PCA path coefficient analysis clustering genetic variability

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