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Uses of Simulation Models in Precision Cotton Farming

J. A. Landivar


 
ABSTRACT

Successful uses of precision farming technology depend on our ability to readily assess field variability and to relate the information to optimum management action. Current techniques used to assess field variability (soil sampling, plant mapping, and scouting) are tedious, slow and expensive. Simulation models can play an important role in the development of geo-referenced soil and/or plant databases for use in precision cotton farming. A crop simulation model running on real time can readily provide this information at a fraction of the cost of sampling. Initial performance evaluation of the ICEMM-cotton simulation model to a precision farming study at the King Ranch, in Kingsville, Texas shows promising uses of the models for this purpose. Actual yield in a 100-acre field ranged from 442 to 884 kg/ha with an average of 585 kg/ha. The simulated yield varied from 385 to 1089 kg/ha with a mean of 619 kg/ha. The average yield values differ by 6%. Blocks where ICEMM failed to simulate yield often showed an under estimation of vegetative growth. Slow vegetative growth in the model is often related to a failure to simulate the time course of soil water potential. Our experience on the use of ICEMM to generate geo-reference databases for precision farming applications indicated the following; (1) mechanistic, process level models are required to simulate plant growth and yield in response to inputs reflecting differences between adjacent blocks or management units. ICEMM is such a model; however, improvements and enhancements to the various subroutines are needed to improve the accuracy of the simulations, and (2) improved soil sampling techniques and laboratory analysis are needed to capture and quantify field variability in physical and chemical soil properties.



Reprinted from Proceedings of the 1999 Beltwide Cotton Conferences pp. 1384 - 1385
©National Cotton Council, Memphis TN

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Document last modified Monday, Jun 21 1999