Agro-Morphological Characterization and Genetic Dissection of Linseed (Linum usitatissimum L.) Genotypes
PHYTON-INTERNATIONAL JOURNAL OF EXPERIMENTAL BOTANY(2022)
Abstract
Linseed is a multipurpose crop and the crop needs further improvement to increase production and yield due to its high value and demand. This study aimed to assess the extent and pattern of genetic variability of forty linseed genotypes based on diverse agro-morphological and yield attributes. The field experiment was conducted following a Randomized Complete Block Design with three replications. Linseed germplasm showed a wide range of phenotypic expression, genetic variability and heritability for 30 studied traits. A low to high phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were observed. The lowest genotypic (sigma(2)g) and phenotypic variances (sigma(2)p) were found in capsule diameter (CD), length of calyx (LC), capsule length (CL), seed length (SL), and seed breadth (SB). High broad-sense heritability (h(2)b) with high genetic advance as a percentage of mean (GAM) were observed in days to germination started (DGS), days to 80% emergence (DE), plant height at 28 and 40 DAS, number of flowers (NFPP), filled capsules (NFCPP) and yield per plant (YPP) indicating additive gene action exists for these characters. Hierarchical cluster analysis separated 40 genotypes into five clusters, where Clusters I to V assembled with 13, 4, 4, 5 and 14 genotypes, respectively. Considering yield and yield attributes, Cluster-IV (G3, G4, G6, G10 and G31) genotypes showed promising while, Cluster-H (G2, G16, G35, G36) and Cluster-HI (GI, G33, G39 and G40) genotypes were dominant on plant morphological traits. Based on principal component analysis (PCA), few characters such as YPP, NFPP, NFCPP, days to first flowering and capsule formation, early emergence, days to branch initiation and plant heights at different growth stages revealed important and effective traits for consideration in the selection of linseed breeding programs.
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Key words
Genetic variability, heritability, genetic advance, principal component analysis, hierarchical clustering, linseed
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