Climate change has increased the sensitivity of cropping systems to environmental variability, making the genetic dissection of G \(\times\) E and phenotypic plasticity essential for adaptive breeding. In this study, a recombinant inbred line population of upland cotton was evaluated across 16 environments from multi-year and multi-location field trials to assess the plasticity of yield- and fiber-quality traits. By integrating the Finlay–Wilkinson regression model with CERIS sliding-window analyses, 13 key meteorological factors and 4 principal component variables were identified, together with their effective time windows. QTL mapping based on trait plasticity slopes and environmental response slopes detected 172 environment-associated loci. A major locus at 188 Mb on chr10 influenced boll weight and seed index in response to multiple environmental variables, including photoperiod, cumulative radiation, growing degree days, and the product of radiation and photoperiod, suggesting a key regulatory site for environmental signal perception. Haplotype analysis further supported functional divergence of alleles within this region in relation to environmental adaptation. Overall, this study identifies critical environmental factors shaping cotton yield and fiber quality and reveals multiple G \(\times\) E–related loci underlying environmental responsiveness and phenotypic plasticity, providing a theoretical foundation for environmentally informed precision breeding.
