Through the work described in this proposal we will generate a better understanding of how Phosphorus is contributing to SDS risk. These results may lead to updated Phosphorus recommendations for soybean producers in Kansas who are at risk for SDS. In addition, we aim to establish the infrastructure to test new and emerging products for SDS management to provide unbiased data back to producers to help inform product selection. Through a previously funded project through the Kansas Soybean Commission, we have developed a model based on pre-planting soil temperature that very accurately predicts SDS risk. In this project we aim to fine-tune that model and validate it in producer fields. By the end of this project, we hope to have a model that producers can use to assess risk at planting time. We will continue to build on previous work to develop best management practices to maximize yield for Kansas soybean producers. Finally, we will communicate these results back to Kansas soybean growers, crop agents, and the ag industry through dynamic extension programming.