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Article
Methodology for the use of DSSAT models for precision agriculture decision support
Computers and Electronics in Agriculture
  • Kelly R. Thorp, United States Department of Agriculture
  • Kendall C. DeJonge, United States Army Corps of Engineers
  • Amy L. Kaleita, Iowa State University
  • William David Batchelor, Mississippi State University
  • Joel O. Paz, University of Georgia
Document Type
Article
Publication Date
1-1-2008
DOI
10.1016/j.compag.2008.05.022
Abstract
A prototype decision support system (DSS) called Apollo was developed to assist researchers in using the Decision Support System for Agrotechnology Transfer (DSSAT) crop growth models to analyze precision farming datasets. Because the DSSAT models are written to simulate crop growth and development within a homogenous unit of land, the Apollo DSS has specialized functions to manage running the DSSAT models to simulate and analyze spatially variable land and management. The DSS has modules that allow the user to build model input files for spatial simulations across predefined management zones, calibrate the models to simulate historic spatial yield variability, validate the models for seasons not used for calibration, and estimate the crop response and environmental impacts of nitrogen, plant population, cultivar, and irrigation prescriptions. This paper details the functionality of Apollo, and presents the results of an example application.
Comments

This article is from Computers and Electronics in Agriculture 64 (2008): 276–285, doi:10.1016/j.compag.2008.05.022.

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Open
Rights
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Language
en
File Format
application/pdf
Citation Information
Kelly R. Thorp, Kendall C. DeJonge, Amy L. Kaleita, William David Batchelor, et al.. "Methodology for the use of DSSAT models for precision agriculture decision support" Computers and Electronics in Agriculture Vol. 64 (2008) p. 276 - 285
Available at: http://works.bepress.com/amy_kaleita/37/