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ARS Home » Crop Production and Protection » Research » Research Project #445618

Research Project: Establishing Infrastructure to Develop Predictive Tools for Corn and Wheat Diseases

Location: Crop Production and Protection

Project Number: 0500-00102-001-033-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Jun 1, 2024
End Date: May 31, 2025

A) For corn, the overall project goals are to develop disease prediction models for corn diseases based on one or more of the following factors: presence and amount of initial inoculum, aerial spore density, production practices, and environmental variables B) For wheat, the overall project goal is to develop predictive models that will help wheat growers evaluate the risk of diseases.

A) For Corn the project goals are conducted in four objectives: 1) Develop new, and validate the accuracy of existing, disease and mycotoxin prediction models across a wide geographical region; 2) Establish the association between inoculum intensity, production factors, disease development and weather in experimental plot trials; 3) Compare spore trap technologies for detection of pathogen population levels; and 4) Disseminate corn disease information and management techniques through various outputs. To achieve objective 1, pre-planting binary gray leaf spot (GLS) logistic regression models developed by a Cooperator will be validated by testing for their accuracy in predicting the risk of GLS severity at different growth stages. In addition, new pre-planting risk assessment models using PCR-based estimates of inoculum density at or prior to planting as a predictor variable will be developed. Finally, in-season GLS and deoxynivalenol risk assessment models using summary weather variables along with cropping practice, hybrid resistance, and inoculum density variables. For objective 2, efforts will be focused on five diseases. Experiments will be established in corn fields at three locations across the state of Ohio to investigate associations among disease intensity and the following factors: (1) crop residue cover (initial inoculum), (2) planting date, (3) fungicide application at VT/R1, (4) genetic resistance, and (5) airborne inoculum density. Data from these experiments as well as similar experiments conducted by Cooperators in participating states will also be used for external validation of the models developed under objective 1. For objective 3, pathogen populations detected by the Burkard and rotorod-type spore traps at each location from 2020 to 2022 will be compared. For objective 4, data from these from these trials will be shared with stakeholders at field days and workshops. B) For Wheat, the project goals are conducted in three objectives: 1) Develop predictive models based on databases of past disease epidemics in the U.S.; 2) Quantify associations among pathogen inoculum density, disease development, and weather variables in small plot trials; and 3) Quantify associations between pathogen inoculum, disease development and weather variables in commercial fields. To accomplish objective 1, curated disease observations will be coupled with weather and cropping system data so that project cooperators will use the resulting database to establish hypotheses about the biological processes driving disease epidemics based on research literature and the experience of regional wheat disease experts. Preliminary models of disease risk based on historical observations of epidemics will be developed. For objective 2, associations among inoculum density, weather variables and disease ratings caused by four wheat pathogens will be quantified in small plots so that accurate sampling can occur. For objective 3, experiments and data collection will be collected similar to obj. 2 from three research farms and five commercial wheat fields in Ohio.