For most crops, timely water availability is critical for producing high yields. Even short periods without adequate soil moisture can permanently decrease yield potential. Yet most growers do not use science-based methods to manage soil moisture. This project’s vision is to deliver the truly disruptive SmartIrrigation CropFit mobile application (SI CropFit), which offers intelligent management of irrigation scheduling for the most extensively irrigated agronomic crops in the United States – corn, cotton, peanut and soybean. SI CropFit will be cost-free, engaging, dynamic, and provide actionable information to users. It will be customizable to individual fields and our expectations are that it will result in irrigation water use efficiency gains of up to 40% when compared to standard grower methods. SI CropFit will leverage irrigation scheduling apps that our team has already developed for corn, cotton, and soybean and develop a new model for peanut. SI CropFit will use meteorological data from multiple sources, satellite images, and the USDA NRCS SSURGO to drive models that will estimate daily plant available soil water within the root zone. The It will send notifications to the user when irrigation is needed. Our project consists of three phases – app development, field-testing, and on-farm evaluation to promote adoption and use. The corn, cotton, and soybean models in CropFit are now available for public use. The peanut model is in beta testing.
Project Graduate Students: Emily Bedwell (Ph.D.), Vinicius Trevisan (M.S.)