This is an integrated research and extension project. Wheat is the third largest commodity crop in the US worth approximately $10 billion. Stakeholders are challenged by the complexity of decisions that are needed for effective wheat disease management. Our goal is to develop a decision support platform for wheat disease management to improve adoption of best management practices. The specific objectives are to: (1) develop a decision support platform for wheat disease management that integrates wheat market class, underlying disease risk, and best management recommendations, (2) conduct deep learning analyses to uncouple underlying patterns for best wheat disease management tactics at different spatial scales, (3) train the next generation of experts to "think epidemiologically", and (4) reduce the gap between knowledge on disease risk and best management practices and its application at the farm level. This project fits two important areas of the National IPM Roadmap: a) developing economical, high-resolution pest management monitoring systems and b) providing novel mechanisms for delivery of IPM tactical and strategic tools. This project also aligns with the Farm Bill for technology mechanisms. Our platform will be used to obtain user-defined data on wheat production practices and deep learning analyses will be used to study patterns that explain the variation in responses at different spatial scales. In collaboration with stakeholders, we will develop training programs where individual stakeholders can gain experience with different disease management scenarios. We expect that the technology developed in this project will be readily applied to other small grains as well.
|Effective start/end date||6/15/20 → 6/14/25|
- National Institute of Food and Agriculture: $455,000.00