Background: Gossypium hirsutum, the most widely cultivated crop in the world has concurrent importance for both fibre quality and yield. Polygenes regulate cotton output and a variety of factors affect the characteristic. As a result, it is essential to have thorough knowledge of the relationships between different component traits and fibre quality. Thus, the aim of the study was framed to know about the correlation along with cause-and-effect relationship among the economic traits. Mathod: Eight parents and 56 hybrids made up the experimental sample for our study, which were evaluated for 18 economically significant traits. The study was conducted at Department of Cotton, Tamil Nadu Agricultural University, Coimbatore, in 2021-2022. Results: Analysis of variance was highly significant for all the traits studied. The result of correlation revealed that the traits viz., number of bolls per plant, boll weight, number of seeds per boll, upper half mean length and fibre strength had a high magnitude of positive correlation with seed cotton yield at both genotypic and phenotypic levels. Path analysis represented the direct effects of upper half mean length, uniformity index, number of bolls per plant, number of seeds per boll and fibre strength on seed cotton yield. Hence, these traits can be used as selection criteria for yield improvement in cotton.

Cotton productivity under water-stressed conditions is controlled by multiple quantitative trait loci (QTL). Enhancement of these productivity traits under water deficit stress is crucial for the genetic improvement of upland cotton, Gossypium hirsutum. In the present study, we constructed a genetic map with 504 single nucleotide polymorphisms (SNPs) covering a total span length of 4,416 cM with an average inter-marker distance of 8.76 cM. A total of 181 intra-specific recombinant inbred lines (RILs) were derived from a cross between G. hirsutum var. MCU5 and TCH1218 were used. Although 2,457 polymorphic SNPs were detected between the parents using the CottonSNP50K assay, only 504 SNPs were found to be useful for the construction of the genetic map. In the SNP genotyping, a large number of SNPs showed either >20% missing data, duplication, or segregation distortion. However, the mapped SNPs of this study showed collinearity with the physical map of the reference genome (G. hirsutum var.TM-1), indicating that there was no chromosomal rearrangement within the studied mapping population. RILs were evaluated under multi-environments and seasons for which the phenotypic data were acquired. A total of 53 QTL controlling plant height (PH), number of sympodial branches, boll number (BN), and boll weight (BW) were dissected by QTL analysis under irrigated and water stress conditions. Additionally, it was found that nine QTL hot spots not only co-localized for more than one investigated trait but were also stable with major QTL, i.e., with > 10% of phenotypic variation. One QTL hotspot on chromosome 22 flanked by AX-182254626–AX-182264770 with a span length of 89.4 cM co-localized with seven major and stable QTL linked to a number of sympodial branches both under irrigated and water stress conditions. In addition, putative candidate genes associated with water stress in the QTL hotspots were identified. Besides, few QTL from the hotspots were previously reported across various genetic architects in cotton validating the potential applications of these identified QTL for cotton breeding and improvement. Thus, the major and stable QTL identified in the present study would improve the cotton productivity under water-limited environments through marker-assisted selection.