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Precision Farming, Myth or Reality: Selected Case Studies from Mississippi Cotton Fields

  • Jeffrey L. Willers
  • Eric Jallas
  • James M. McKinion
  • Michael R. Seal
  • Sam Turner
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 25)

Abstract

There is a lot of interest in the concept of precision farming, also called precision agriculture or site-specific management. Although the total acreage managed by these concepts is increasing worldwide each year, there are several limitations and constraints that must be resolved to sustain this increase. These include (1) collecting and managing the large amounts of information necessary to accomplish this micromanagement, (2) building and delivering geo-referenced fine-scale (i.e., change every few meters or less) prescriptions in a timely manner, (3) finding or developing agricultural machines capable of quickly and simultaneously altering the rates of one or more agri-chemicals applied to the crop according to a geo-referenced prescription, (4) the need to have personnel stay “current” with advancements in developing technologies and adapting them to agriculture, (5) refining existing and/or creating new analytical theories useful in agriculture within a multidisciplinary, multi-institutional, and multibusiness environment of cooperation, and (6) modification of agricultural practices that enhances environmental conservation and/or stewardship while complying with governmental regulations and facing difficult economic constraints to remain profitable. There are many myths that overshadow the realities and obscure the true possibilities of precision agriculture. Considerations to establish productive linkages between the diverse sources of information and equipment necessary to apply site-specific practices and geographically monitor yield are daunting. It is anticipated that simulation models and other decision support systems will play key roles in integrating tasks involved with precision agriculture. Discovering how to connect models or other software systems to the hardware technologies of precision agriculture, while demonstrating their reliability and managing the flows of information among components, is a major challenge. The close cooperation of the extension, industrial, production, and research sectors of agriculture will be required to resolve this constraint.

Keywords

Geographical Information System Precision Agriculture Global Position System Receiver Geographical Information System Software Broadcast Treatment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We are thankful for the support of Kenneth Hood, Perthshire Farms, Gunnison, MS, and Paul Good, Good’s Longview Farm, Macon, MS, for permission to work in their fields. Thanks are also expressed to Mr. Dan Woodard for providing the variable-rate applicator and writing the final nitrogen prescription that were based on the simulation model recommendations described in the Case 1 scenario. Thanks are expressed to Mr. Ronald B. Britton and Dr. Martin Wubben, USDA-ARS, Mississippi State, MS, for their assistance during the preparation of the manuscript.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Jeffrey L. Willers
    • 1
  • Eric Jallas
  • James M. McKinion
  • Michael R. Seal
  • Sam Turner
  1. 1.USDA-ARS-Genetics and Precision Agriculture Research UnitMSUSA

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