Climate-Resilient Cotton Breeding: AI and Multi-Omics Take on Drought and Heat Stress

A new review in Discover Plants lays out how researchers are combining multi-omics, AI, genome editing, and nanotechnology to speed up cotton breeding for a changing climate. The work targets drought, heat, irregular rainfall, and pest pressure, all of which have stalled cotton yields. Because cotton has a large and complex allotetraploid genome, traditional breeding has struggled to keep pace with rising environmental stress. The review explains how pan-genomic approaches and machine learning can improve trait selection accuracy by 10 to 20 percent over older statistical models. It also covers targeted edits to genes controlling fiber length, strength, and stress defense, plus methods to silence toxic gossypol in seeds so cottonseed can become safer food and feed. The authors note that field validation and regulatory pathways will determine whether these lab gains actually reach farmers.