Develop and validate prediction tools for diseases affecting cotton to maximize the efficacy of management decisions and consequently reduce yield losses and input expenses.
- Expand upon the previous 3-state network of foliar spore sampling.
- Build protocols and expertise in the detection of common cotton pathogens as well as episodic and invasive pathogens.
- Initiate viral sampling and detection to facilitate inclusion of viruses in future programs.
- Initiate research to detect and interpret Aerolate mildew spores in air samples.
- Initiate research to model target spot impacts on cotton yields and detection of mutation for quinone outside inhibitors (QoI) fungicide resistance.
- Create a robust data set with site-specific weather, plant condition, and airborne pathogen load.
- Create and validate cotton disease models incorporating previously listed factors and engage with diverse modeling groups to build a structured decision-making network.
- Compare the utility of wind-sock passive spore samplers to active samplers.
- Incorporate/utilize other artificial intelligence platforms into modeling efforts (e.g., unmanned aerial vehicles).
- Create a comprehensive data set of non-NPMTI projects conducting similar research.
- Refine management recommendations based on new information gained through these applied research projects.
- Preliminary models for target spot and other diseases.
- Comparison data between passive and active spore samplers.
- Information acquired regarding factors essential for the next generation of disease risk assessment models.
- Direct quantifications of associations between disease intensity and inoculum presence and abundance throughout the growing season and impact on yield.
- Optimization of cotton-pathogen monitoring methods including spore sampling, cotton residue and/or soil samples.
- Improved understanding of weather variables that affect cotton disease development.
- Model spatio-temporal dynamics of diseases in cotton.
- Disease prediction tools for cotton.
- GUIs and Smartphone apps.
- Improved understanding of the role of site-specific weather, plant condition, and pathogen load on disease development and yield impact.
- Improved suggestions for cotton farmers on disease management.
Multiple collaborative locations will be distributed across the U.S. A team approach will be used where plant pathologists and plant epidemiologists will collaborate to develop elite forecasting tools for cotton diseases that are effective across the entire cotton production belt.
These projects provide the next generation of cotton disease prediction models that will be tested through larger multi-state projects. Farmers will make decisions based on regionally validated science-based information. These projects address specific knowledge gaps identified through interaction with cotton farmers.
Enhance communication and education/outreach for an audience including, but not limited to, producers, ginners, agricultural advisors, research community, and supply chain participants.
- Resources and recommendations related to the integrated management of cotton diseases on the Crop Protection Network (CPN) and other local state resource websites.
- Improved dissemination of cotton disease information and management techniques through an interdisciplinary approach.
- Develop public interface (GUI, apps) for new tools (i.e., pathogen models, site specific weather, plant condition, etc.).
- Training exercises (videos, webinars, etc.) for audience on how to use newly developed tools.
- Relay results to cotton breeders for Host Plant Resistance development (where and what pathogens are being detected).
Best disease management methods, validated by science-based research, are thoroughly publicized to farmers, their advisors, and processors.
- Continue to update and enhance the content of educational and outreach websites.
- Conduct surveys of farmers, consultants, and other agricultural stakeholders to assess how they acquire information about the adoption of cotton disease management techniques, and potential barriers to adoption.
- Develop tools that will help farmers assess and understand the value of adopting cotton disease management practices.
- On-farm demonstrations of best available management options for cotton diseases.
- Timely information about cotton disease risk for farmers via access to online resources and through mobile device platforms.
- Information on cotton disease management available via national websites and customized for distribution through extension programs in states where cotton is grown.
- Results from on-farm demonstrations of technologies developed by NPMTI.
Multiple collaborative locations distributed across the U.S. A team approach will be used where researchers and Extension personnel will collaborate to develop multiple outputs for cotton disease management in the U.S.
Increased adoption of practices by farmers and decision-makers will result in a reduction in yield losses and input expenses related to cotton disease.
Encourage private sector investment and utilization that will help sustain application of NPMTI tools.
Facilitate the private sector to employ prediction systems that include self-sustaining business models.
Private-sector use and promotion of NPMTI tools as well as investment in their infrastructure
- Economic analysis of sustainability of pathogen sampling, analysis, and model updates.
- Data privacy expert analysis to align NPMTI outcomes with industry best practices.
Utilization and promotion of NPMTI tools.
Communication and collaboration between U.S. researchers, Extension personnel, and industry personnel are encouraged.
Collaboration and investment from private sector will help continue the NPMTI efforts, and increased adoption of practices by farmers and decision-makers will result in a reduction in yield losses and input expenses related to cotton disease.