© 2022 PP House Genetic Component Analysis and Determination of Optimum Number of Clusters Based on Morpho-Physiological Traits in Wheat Sourik Poddar, Sahanob Nath, Rupsanatan Mandal, Suvendu Kumar Roy and Saikat Das Print ISSN 0976-3988 Online ISSN 0976-4038 Artcle AR3212 DOI: HTTPS://DOI.ORG/10.23910/1.2022.3212 Research Article International Journal of Bio-resource and Stress Management Dept of Genetics and Plant Breeding, Uttar Banga Krishi Vishwavidyalaya, Coochbehar, West Bengal (736 165), India RECEIVED on 03 rd August 2022 RECEIVED in revised form on 17 th November 2022 ACCEPTED in fnal form on 01 st December 2022 PUBLISHED on 19 th December 2022 IJBSM December 2022, 13(12):1440-1449 htps://pphouse.org/ijbsm.php Citaton (VANCOUVER): Poddar et al., Genetic Component Analysis and Determination of Optimum Number of Clusters Based on Morpho-Physiological Traits in Wheat. International Journal of Bio-resource and Stress Management, 2022; 13(12), 1440-1449. HTTPS:// DOI.ORG/10.23910/1.2022.3212. Copyright: © 2022 Poddar et al. Tis is an open access article that permits unrestricted use, distribution and reproduction in any medium after the author(s) and source are credited. Data Availability Statement: Legal restrictions are imposed on the public sharing of raw data. However, authors have full right to transfer or share the data in raw form upon request subject to either meeting the conditions of the original consents and the original research study. Further, access of data needs to meet whether the user complies with the ethical and legal obligations as data controllers to allow for secondary use of the data outside of the original study. Confict of interests: Te authors have declared that no confict of interest exists. T he present study was conducted at the instructional farm, Uttar Banga Krishi Vishwavidyalaya, Pundibari, Cooch Behar, West Bengal, India during the rabi season (November–March) of 2020–2021 aimed at to evaluate the performance of CIMMYT nursery (19 th HTWYT) under Terai zone of West Bengal to assess genetic diversity and clustering them into optimum number of clusters using 12 morpho phenetic traits along with 02 physiological traits and also against spot blotch disease. ANOVA showed non-significant variation among the genotypes for all the 15 quantitative traits under study. The genotypes were also being screened against spot blotch disease and 29 were found highly susceptible, 14 were susceptible to highly susceptible and 06 were susceptible category whereas only the local check DBW 187 was found moderately susceptible to susceptible. The optimum number of clusters was determined by using K mean clustering algorithm which revealed optimum number of cluster of two. Cluster I consisted of 24 wheat genotypes and Cluster II consisted 26 wheat lines. Among the two clusters, higher diversity was present in cluster I (276.67) than cluster II (249.684). Principal component analysis (PCA) for all the 15 traits revealed only five components having Eigen value >1.00. Among them PC 1 and PC 2 accounted for 36.53% and 12.05% variance respectively. Grain yield was found to be positively associated with 08 traits such as awn length, biological and grain yield, grain per spike, harvest index while negatively correlated with tiller m -1 , mean canopy temperature depression, AUDPC%. ABSTRACT Wheat, genetic divergence, K mean clustering, PCA KEYWORDS: Open Access saikat.ubkv@gmail.com Corresponding 0000-0003-1277-8664 Natural Resource Management 1440