Department of Crop Science
Dr. Gail Wilkerson

Professor of Crop Science and Statistics

2404B Williams Hall
Campus Box 7620
Raleigh, NC 27695-7620

Office: 2404B Williams Hall
Phone: 919.515.5816
Fax: 919.515.5855

Curriculum Vitae

Gail Wilkerson
Dr. Gail Wilkerson

The major goal of Dr. Wilkerson’s research program is to improve crop and turf management decision-making through the application of computer technology. Research has been concentrated in the following areas: 1) development of computerized crop and pest management decision aids; 2) evaluation of scouting protocols through a combination of field research and simulation experiments, and 3) development of physiologically based models of crop growth, pest population dynamics, and crop/pest interactions. Recently, Dr. Wilkerson has turned her attention to developing Web-based applications, and to evaluating the possibility of using information on climate variability and climate forecasts to improve crop and pest management decision-making.

Dr. Wilkerson is involved in a multi-state, multidisciplinary project that has extended the Web-based AgroClimate to North Carolina This program, developed by the Southeast Climate Consortium, is designed to reduce risks of climate variability for farmers, foresters, water-resource managers, and others. Most of the tools on AgroClimate have now been modified to include North Carolina. Another project, funded by the NOAA Sector Applications Research Program (SARP), is exploring ways to use climate information to predict and reduce residential irrigation demands. Changes in turfgrass quality are being related to a drought index, which is based on a simple soil water balance model. Simulation studies using historical climate data will identify irrigation strategies that reduce water usage while maintaining turfgrass quality.

Crop growth models are being used around the world to help explain and predict crop response to soil characteristics, weather patterns, pest infestations, and management strategies. Due to the complexity of these models, most require large amounts of information in order to correctly simulate crop growth throughout the season. Lab personnel have been working for a number of years on ways to facilitate creation, organization, and maintenance of the data files required by these models. Work has focused on developing relational databases to store large amounts of data, and computer programs to access and use the data. These programs help to organize data as needed by the crop simulation models, filter information to create simulation files as needed, automate simulations, analyze results of these simulations, and display results in tabular and graphical form.


Peanut Risk Management Decision Aid:
Peanut Production in the Carolinas and Virginia:
Turf Disease ID:
Turf Disease Management:
Turf and Weed ID:
Turf Weed Management:
Turfgrass/Cultivar Selection:
WebHADSS (Herbicide Application Decision Support System):
SoyVar (Soybean Variety Selection):

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