(NPMTI) 5-Year Action Plan – Overview

Background:

Pathogens that are spread by insects or wind pose a community-wide threat to crop production. Unlike soil-borne pathogens, wind- or insect-dispersed pathogens require community efforts to alert growers to potential threats and minimize both control cost and yield/quality loss. Recent advancements in detecting and modeling the movement of human pathogens, such as SARS-CoV-2 can be adapted to plant pathogens with appropriate investment. Predictive tools for pathogens that require preventive measures such as planting resistant varieties, residue incorporation, canopy management, irrigation adjustment, or proactive crop protection treatments can provide growers with timely information to avoid crop damage.

To address the resulting threats of soil erosion, rainfall-runoff, and soil crusting, and improve the resilience of U.S. agriculture, many growers across the nation have adopted soil conservation practices, including reduced tillage and cover crops. These soil conservation practices have precluded the use of two standard disease controlling tools: 1) crop residue incorporation (i.e., sanitation) and 2) exclusion of alternate hosts.

Historically, tillage was used to bury crop residues in the soil to promote rapid decomposition of stalks, leaves, and associated pathogens, while non-crop areas were often maintained vegetation-free. With soil conservation programs, residues now remain on the surface providing necessary soil health benefits but also leaving pathogen inoculum for future crop infection. Non-crop areas now are managed as grassed waterways, filter strips, and wildlife habitat and can serve as a pathogen bridge from one crop season to the next.

Methods to forecast inoculum exposure would allow growers to take timely preventative actions such as delayed planting, resistant varieties, selective fungicides, crop growth regulators, irrigation management, targeted rotations, and, only where necessary, limited tillage, among other agronomic practices.

The last two decades have demonstrated that the U.S. is vulnerable to invasive and resurgent pathogens spreading from distant states or countries, often triggered by unusual weather. The next two decades could be even more challenging as pathogens from the South spread farther North. A forecast system would provide growers with actionable detection of pathogens before widespread damage occurs and provide public scientists with data on changes in pathogen diversity necessary to breed and deploy protective host plant resistance traits.

Ultimately, NPMTI will be a national, multi-crop disease forecasting tool that will expand to include a diversity of row crops and scientific disciplines across the United States. The current endeavor brings together a network of scientists from Land Grant universities, USDA-ARS, and cooperating national laboratories. NMPTI is foundational for leveraging human and animal infectious decision support tools for agriculture. Adaptation of these tools for key diseases of a variety of crops will facilitate disease management and preventive/mitigative actions, and planning for disease prevention. These tools offer decision support at varying temporal and spatial scales and can be used along the spectrum of engagement, from early detection to outbreak management to post-harvest investigation to host plant resistance breeding.

 

Research Areas:

Currently, NPMTI research focuses on key diseases of three agronomically-important crops: corn, cotton, and wheat, each of which has been organized as a Research Area Committee (RAC). The 5-Year Research Plans for each current RAC, as well as the plans for the two collaborating organizations – Los Alamos National Laboratory (LANL) and the National Agricultural Genotyping Center (NAGC) – are included in this document in the hopes that other researchers will submit proposals that are consistent with the goals and approach of NPMTI. Research proposals can be in support of an existing RAC, or additional annual row crops and new diseases can be proposed to help broaden the scope of NPMTI given sufficient appropriations funding.

Agricultural Appropriations budgeting is dynamic in which funding can vary from year to year. NPMTI operates under the auspices of the USDA-ARS, which administers appropriated funds, generally consistent with the recommendations of the NPMTI Executive Committee (EC). Given that most research conducted by NPMTI scientists is for multi-year projects, funding priority is given to ensure continuation of that research, as long as research benchmarks and activities (as reported in annual reports to the USDA-ARS) are consistent with the goals of NPMTI. New research will be prioritized by the RAC or, in the case of new crops and diseases, prioritized by the NPMTI EC, which is comprised of all stakeholders in the NPMTI. Prioritized research proposals are forwarded by the EC to the USDA-ARS as recommendations.

 

NPMTI Goals:

The overall goals of NPMTI are to: 1) ensure crop sustainability and crop quality; 2) improve soil health; 3) monitor pathogens and microbial diversity in the environment, including, but not limited to crop residues, soils, and air; 4) improve disease management thereby reducing yield losses; 5) increase precision of in-season disease management tactics; and 6) work towards eliminating the indiscriminate use of pesticides.

 

NPMTI Approach:

In-season risk for plant disease development can be improved to near real-time by developing a comprehensive and coherent modeling tool that integrates: 1) pre-season pathogen inoculum density in the field; 2) crop/host genetics; 3) the effects of soil type and other agronomic factors on pathogen inoculum density; 4) an air monitoring system for wind-borne pathogens; 5) the use of other artificial intelligence platforms into modeling efforts (e.g., unmanned aerial vehicles); 6) meteorological (and other agronomic data) in a coherent information and decision support system; and 7) information from historical outbreaks for specific plant diseases.

Ultimately, NPMTI will be a national, multi-crop disease forecasting tool that will expand to include a diversity of annual row crops and fields across the United States. This endeavor brings together a network of scientists from Land Grant universities, USDA-ARS, and cooperating national laboratories. Over the life of this Initiative, primary research will provide insight into crop disease epidemiology and management decisions pertaining to crop selection, hybrid/varietal selection, cover crop selection, tillage options, seed treatments, foliar fungicides, and other agronomic tools that focus on minimizing the impact of crop disease.

Service laboratories will collaborate with the primary research laboratories to develop standard operating procedures (SOPs) on focal variables (e.g., pathogen detection), which may require standardization for regional forecasting models or field-level specificity for more personalized and real-time user models. Ideally participating service laboratories will be in good standing with the International Organization for Standardization (ISO) or hold an accreditation through another certification body. Such laboratories should have SOP development experience to provide validations on the original or updated methods, as communicated by the academic primary research laboratories. Additionally, participating service laboratories will conduct interlaboratory comparisons and implement proficiency tests on SOPs as new laboratories join the Initiative. Participating laboratories with the capacity for data aggregation and analyses will also provide resources for developing the forecasting models.

Important to the ongoing progression of this Initiative is the pursuit and delivery of a comprehensive forecasting tool to the agricultural community. As collection and analysis of multiple variables begin to aggregate, the primary deliverable, a site-specific forecasting model, must be considered during all phases of research and development of the Initiative, and in particular in the early stages of the Initiative’s new research endeavors. The success of this deliverable will require collaboration with data scientists and mathematicians skilled in computational analyses that provide longevity through continual maintenance, storage, and calibration of the forecasting tool. A successful forecasting tool of this magnitude and breadth is contingent on delivering simplicity (user-friendly interface for farmers) out of complexity (advanced predictive modeling).

To see details of each RAC and the collaborating organizations, click on the respective heading