A Case Study of Crop Model Applications In An Increasing Diversity of Genetically Modified Traits.

In recent years, the use of Genetically Modified (GM) cultivars has increased globally and in the US. Crop models need cultivar-specific data files for on-farm decision support. The objectives of this study were to generate GM-specific cultivar database for cotton simulation model, GOSSYM, and to validate the model under field conditions with different weather, soil, and management conditions. Experiments were conducted to develop variety files for six GM cultivars. Cultivars were grown on two different soils by varying levels of nitrogen, growth regulator, and irrigation in Mississippi during 2001-2006 growing seasons. Plant growth data such as LAI, plant height, numbers of main-stem nodes, squares and, bolls, and biomass of various plant parts were collected several times during the season. Dates of occurrences of major phenological stages and yields were recorded. Weather data needed as input for model were also obtained in a nearby weather station. Initially, cultivar parameters were modified for one specific data set. The modified model tested for the predictive capability across several management options, soil type, and years either in combination or alone. The correlation coefficient between observed and simulated yield for all cultivars ranged between 0.52 and 0.87.  We found that GOSSYM was capable of simulating GM cultivars with minor changes in cultivar-specific parameters. The GM cultivar files developed in this study will be beneficial to government agencies, researchers, growers, and consultants in using the cotton simulation model for various management decisions and in assisting policy decisions across US Cotton Belt.