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Plant Science Today (PST)

Research Articles

Early Access

Multivariate analysis of genetic variability and divergence in upland cotton (Gossypium hirsutum L.) for yield and fiber quality traits

DOI
https://doi.org/10.14719/pst.7734
Submitted
14 February 2025
Published
14-10-2025
Versions

Abstract

Cotton (Gossypium hirsutum L.) is a versatile crop with multiple applications. The evaluation of 30 upland cotton genotypes was conducted to measure variability and divergence in seed cotton yield, yield-related attributes and fiber quality traits using multivariate analyses. The investigation, conducted during the Kharif season of 2022, was laid out in a randomized block design (RBD) with three replications at the Main Cotton Research Station (MCRS), Navsari Agricultural University (NAU), Surat. Analysis of variance (ANOVA) showed significant genetic variability between the genotypes for all traits. Morphological observations identified GISV-400 as the genotype with the highest seed cotton yield (148.00 g/plant). Fiber quality analysis highlighted GISV-391 as superior in upper half mean length (28.03 mm), fiber strength (28.37 g/tex) and fiber fineness (4.80 µg/inch). Seed cotton yield per plant displayed a significant positive relationship with the number of bolls per plant and boll weight. Principal component analysis (PCA) identified five components with eigenvalues greater than one, collectively explaining 78.66 % of the total variation. The biplot revealed GISV-399, GISV-398, GISV-391, GISV-322, GISV-323, GISV-313 and GISV-402 as the most genetically diverse genotypes. Hierarchical clustering further classified the 30 genotypes into five distinct groups. To identify the best-performing genotypes, the Multi-Trait Genotype-Ideotype Distance Index (MGIDI) was employed for the ranking of genotypes at 10 % selection intensity, four genotypes (GISV-389, GISV-395, GISV-394 and GISV-391) were identified as superior. Overall, seven genotypes (GISV-389, GISV-395, GISV-394, GISV-391, GISV-398, GISV-399 and GISV-400) were consistently identified as high-performing in terms of both yield and fiber quality based on PCA, hierarchical clustering and MGIDI. Overall, the study indicated that the existing variability in tetraploid cotton can be effectively utilized through hybridization and development of mapping populations.  

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