Performing Department
Entomology, Soils, & Plant Sciences
Non Technical Summary
In the Southeast, fungicide resistance in the brown rot pathogen Monilinia fructicola of peach is currently managed by the recently implemented Profile resistant management program. However, the program needs improvement to meet grower demands for timelier receipt of management recommendations. Our goal is to create a web application which will support the Profile resistance management program, providing real-time data processing and immediate recommendations for fungicide applications within the context of resistance management and optimum efficacy. Specific objectives are to (i) develop a web application that allows online data entry, data analysis, data transfer, and provides immediate profile-specific strategies to combat resistance, (ii) train South Carolina, Georgia, Alabama, and North Carolina county agents and specialists in using the application, and (iii) expand the web application to also become a searchable and historical database of resistance development within M. fructicola populations throughout the Southeast. Capitalizing on the expertise of the principal investigators from Clemson University and the University of Georgia (UGA), the web application will be developed through the help of the Clemson University Computer Science Department. Expertise from this department will also be utilized in subsequent agent and producer training associated with the new online functions. The web application-supported Profile resistance monitoring program will enable growers to react to problems in a much timelier manner, which in turn will improve disease control and customer satisfaction. The web application will be developed as an expert system, providing best-management recommendations based on the resistance management information and fungicide classes available for disease control. The Profile resistance management program is a multistate partnership involving South Carolina, Georgia, Alabama, and North Carolina, but principle leadership for the development of the program has resided through collaborative efforts of Clemson and UGA.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
Objectives and Anticipated Impacts (Extension) Train South Carolina, Georgia, Alabama, and North Carolina extension agents to use the application Impact: Training will: (i) raise awareness of the importance of determining resistance profiles, and (ii) develop confidence in the agents' ability to provide a correct recommendation, which in turn will make them more valuable agents to their producer clientelle. Expand the web application to also become a searchable database Impact: the searchable database will provide year- and location-specific information that may aid in the development of resistance management strategies.
Project Methods
Train South Carolina, Georgia, Alabama, and North Carolina county agents and specialists, to use the application Although we intend to make the web application very user friendly and self explanatory, we believe that a one-on-one training or training in small groups (up to 3 users) will be the most likely way to get agents to actually use it. Some agents are reluctant to use new technology in general and may not even sign up for a workshop. However, a one-on-one or one-on-two or -three training should take that fear away. Besides, there are less than 40 agents and extension specialists left in the Southeast covering all peach production areas in Georgia, South Carolina, Alabama, and North Carolina. We will also produce a quick-start guideline in form of a pamphlet that we will hand out at agent and grower meetings. This will also be available on the web. Dr. Schnabel or Dr. Brannen and a representative of the Clemson University Computer Science Department (computer science student) will take part in each training session to reflect expertise in disease management and expertise on the technical side of this application. We will walk users through each step of the web application and then ask the participants to enter hypothetical data themselves. During the training we will collect comments and suggestions for improvement of the web application from participants. This information will be discussed and potentially implemented in future versions. Expand the web application to also become a searchable database Drs. Schnabel and Brannen will both keep copies of all entries but there will also be a searchable online database established that can be accessed by all authorized personnel (administrators). The database will enable users to retrieve reports by year, location, resistance category and fungicide. The database will also have a feature summarizing data in table or figure format from a single year and multiple years. For example, on demand a table could be created showing all resistance profiles for growers who sprayed a particular spray program (DMI fungicides only) or a table could be created showing resistance profiles for a particular geographical area. Collecting and analyzing such data over one year and or several years will yield invaluable insights as to how different spray programs influence the resistance profiles of a specific location or whether a location has an impact on spray programs. We may be able to analyze how alternation of chemical classes compares to mixtures in regard to managing fungicide-resistant populations.