Submitted to: Intnl Conference On Geospatial Information In Agriculture And Forestry
Publication Type: Proceedings
Publication Acceptance Date: 10/1/2001
Publication Date: 11/1/2001
Citation: SASSENRATH COLE, G.F., THOMSON, S.J. USE OF THE NEW COTTON PRODUCTION MODEL (CPM) FOR PRODUCTION DECISIONS IN COTTON. INTNL CONFERENCE ON GEOSPATIAL INFORMATION IN AGRICULTURE AND FORESTRY. 2001. Interpretive Summary: Site-specific management offers potential savings for farmers. However, sound management practices must be developed for each unique management zone. Many factors contribute to the variability of crop growth and yield including cultivar, field topography, soil nutrient and textural characteristics, and environment. Development of realistic management practices requires attention to each of these factors and their interaction. Crop simulation models can be used to test the potential outcome of management inputs as a function of these various factors. Simulation models offer farmers a tool for development of realistic, sound management practices for the varying conditions observed within production fields. In this study, the recently developed Cotton Production Model (CPM) is introduced and described. The model is then used for developoment of fertilizer rate and timing schemes for two soil types common to the lower Mississippi Delta. The economic impact of the difference in soil response to fertilization is discussed, along with a method for implementation of variable rate management.
Technical Abstract: The promise of precision agriculture is the optimization of input use through sub-field management to accommodate within field spatial variability. Paramount to the realization of these potential benefits is the ability to develop optimal management scenarios that account for the variant edaphic and environmental conditions. The ability to incorporate the particular soil, environmental, and cultivar differences into a management decision support tool requires expertise from a broad spectrum of knowledge. Crop simulation models offer the potential for use in management decision support for crop production. This study describes the current state of crop modeling for cotton, with the introduction of the Cotton Production Model. The background and output of the model are described, and model simulations are presented for fertilizer rate and timing on two soil types of the lower Mississippi alluvial flood plain. Implementation of the model for predicting optimal scenarios for cotton production is discussed.