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Diversification Assessment in Cotton for Lint Quality, Disease Response and Economic Attributes by Multivariate Analysis

Diversification Assessment in Cotton for Lint Quality, Disease Response and Economic Attributes by Multivariate Analysis

Muhammad Jamil1*, Kamran Javed1 and Imran Akhtar2

1Cotton Research Station, Vehari, Pakistan; 2Regional Agricultural Research Institute, Bahawalpur, Pakistan.

*Correspondence | Muhammad Jamil, Cotton Research Station, Vehari, Pakistan; Email:


Genetic erosion is a major pitfall in man directed evolution faced by cotton crop in Pakistan during recent years. Present study was carried out at Cotton Research Station, Vehari during 2019-20. The main purpose was to explore the genetic diversity in the strains under study. Principal component analysis, along with agglomerative hierarchical clustering tools were employed. Twenty-four recently bred upland cotton strains bearing diversified origin were configured in triplicate following Randomized Complete Block Design (RCBD). The data for novel attributes were recorded. Analysis of variance results indicated that a significant level of variation was existing among the strains for disease index, plant population and micronaire value at (p<0.05), while means for all other study traits were found highly significant at (p<0.01). Descriptive statistics illustrated presence of sufficient range in the studied traits. Out of 11 principal components (PC), first 5 PC indicated Eigen value >1 and contributed 75.826% towards cumulative variability. Yield related traits plus lint quality attributes depicted positive loading behavior, while disease index (-0.215) and plant population (-0.054) showed negative loading attitude in PC-1. Similarly, boll counts plant-1 (0.778) and fiber length (0.480) indicated strong positive loading trend, whereas fiber fineness (-0.742) and ginning out turn (-0.709) showed negative loading attitude towards PC-2. The correlation analysis indicated presence of significant (0.632) association at (p<0.01) between fiber fineness and ginning out turn. Whereas disease index showed negative association with all studied traits except monopodial branches. All strains were categorized in two clusters. The strains included in clusters 1 inclusive of check cultivar CIM-602 were distinguished by 44% higher within class variance than strains in cluster 2 respectively. The cotton strains S-1918 and S-1923 were found most diverse and can be utilized in future gene pyramiding schemes to breed cotton cultivars with broad genetic base. 


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Sarhad Journal of Agriculture


Vol. 38, Iss. 3, Pages 759-1159


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