Development of a cotton fiber quality simulation module and its incorporation into cotton crop growth and development model: GOSSYM

GOSSYM is a mechanistic, process-level cotton crop simulation model. It can simulate the growth and devel-opment of cotton under different environmental and management conditions and provide information on crop growth and development, various stresses, and yield. The current model version does not have the capability of simulating cotton fiber quality. Cotton fiber quality is as significant as fiber quantity. In this study, a cotton fiber quality simulation module is developed and integrated into GOSSYM. The functional relationships between the fiber quality and the major factors influencing fiber quality (temperature, water, and nutrient status) are established based on the temperature, water, and nutrient-controlled sunlit soil plant atmospheric research (SPAR) chamber experiments. In the developed model, the potential fiber quality in terms of four major fiber quality indices (fiber length, fiber strength, micronaire, and uniformity) is estimated based on the temperature function, and actual fiber quality indices are determined by reducing potential quality as a function of water and nutrient status in the crop. The newly developed model's fiber quality modeling capabilities are demonstrated using illustrative examples from a case study. Illustrated examples analyze the effect of different temperatures, nitrogen fertilizer application rates, irrigation, planting date, and atmospheric carbon dioxide concentrations on fiber quality indices. Simulation results are discussed by correlating them with underlying processes (growth and development, water, and nitrogen status), literature data, and functional relationships incorporated into the fiber quality module in GOSSYM. The model has demonstrated a reasonable simulation of fiber quality. The developed model can be a valuable tool for accurate cotton fiber quality simulations, lint yield production, fiber quality optimization, and making policy decisions under varying environmental and management conditions.