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Genetic diversity for yield and fiber traits in upland cotton (Gossypium hirsutum L.) genotypes


Article Information

Title: Genetic diversity for yield and fiber traits in upland cotton (Gossypium hirsutum L.) genotypes

Authors: Rajab Ali Kaleri, Younis Malik, Tariq Majidano, Mohsin Zulqarnain Hussain Abbasi, Saleem Ejaz, Ghulam Hassan Bahalkani, Nabila Maryam Muhammad Ubaidullah Aleem, Zuhaib Saleem Asma Kaleri, Benazir Chutto, Farman Ali Kaleri, Kamran Khan Kaleri, Muhammad Irfan Ali Kaleri

Journal: Pure and Applied Biology (PAB)

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31
Y 2022-07-01 2023-06-30

Publisher: Bolan Society for Pure and Applied Biology

Country: Pakistan

Year: 2025

Volume: 14

Issue: 2

Language: en

Categories

Abstract

The present study was conducted at the CRI Cotton Research Institute in Tandojam to evaluate the genetic diversity for yield and fiber characteristics in upland cotton. The crop was grown using a randomized complete block design with 3 replications and 8 genotypes, including a single check variety. The cluster analysis divided the genotypes into four groups based on their genotypic homogeneity. Cluster 1 contains two genotypes (TH-25/23, TH-23/23), and there is a close relationship between them. Cluster 2 included two genotypes (TH-22/23, TH-24/23), cluster 3 contains genotypes TH-27/23 and Sindh-1, and cluster 4 contains two genotypes TH-26/23 and TH-28/23 with a maximum distance between them. Similarly, the presence of high loading was significantly observed in the first principal component PCA-4, 5, 6, and 7 exhibited positive loadings for sympodial branches plant-1, height of plant, and monopodial branches plant-1, respectively. A greater percentage of variance was observed in PCA-7 and PCA-8 (99.90% and 100%). Among the genotypes, TH-26/23 and TH-22/23 should be preferred for further breeding programs, and they could be utilized in hybridization and selection programs for the development of a new variety.
Keywords: Cotton; Germplasm; Fiber; Yield traits; Cluster analysis
http://dx.doi.org/10.19045/bspab.2025.140051


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