Estimation of genetic diversity in sweet pepper (Capsicum annuum L.) through multivariate analysis
DOI:
https://doi.org/10.3329/jsau.v11i1.82684Keywords:
Hybridization, PCA, Canonical Variate Analysis, Cluster analysis, Diversity, Sweet pepperAbstract
Sweet pepper is an important emerging exotic vegetable crop in Bangladesh, which play an essential function in the country economy, food and nutrition but there are not enough acceptable high yielding varieties. In this regard the objectives of this investigation was to ascertain the extent of genetic variation and to mark out the diverse parents among the genotypes that was collected for the purpose of implementing a hybridization program. Twenty one genotyes were employed and the analysis of variance (ANOVA) demonstrated that the genotypes exhibited significant (p<0.01) differences in the majority of the studied parameters. For the purpose of choosing diverse parents, multivariate analytical system including PCA (Principal Component Analysis), PCO (Principal Co-ordinate Analysis), CVA (Canonical Variate Analysis) and Cluster analysis were performed for yield and yield attributes. Analysis using principal components showed that the first four component were accountable for 83.40% of the total variation among the fourteen yield contributing attributes. Through the use of principal coordinate analysis, the inter-genotypic distance was calculated, resulting in the SP 01 and SP 07 genotypes exhibiting the greatest distance of 2.585. The genotypes were separated into six specific cluster (I-VI), cluster I (08) had the most genotypes, the greatest distance between clusters IV and II (17.111) was observed, and the maximum cluster mean range for individual fruit weight was recorded (67.70 to 208.71 g). Considering, the different multivariate analytical results the genotypes SP 03, SP 05 and SP 08 from Cluster I, SP 14 from Cluster II, SP 01 from Cluster IV and SP 09, and SP 17 from Cluster VI were selected for the hybridization program.
J. Sylhet Agril. Univ. 11(1): 47-58, 2024
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Copyright (c) 2024 J Ferdousi, M Zakaria, M A Hoque, N A Ivy, S R Saha, M S Islam, M I Hossain, M M Haque, T Afroz

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