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ARS Home » Southeast Area » Mississippi State, Mississippi » Crop Science Research Laboratory » Genetics and Sustainable Agriculture Research » Research » Publications at this Location » Publication #223641
Title: Precision farming, myth or reality: Selected case studies from Mississippi cotton fields

Author
item Willers, Jeffrey
item JALLAS, ERIC - CIRAD, FRANCE
item McKinion, James
item SEAL, M - SPECTRAL VISIONS
item TURNER, SAM - REITRED ARS

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 4/1/2008
Publication Date: 5/1/2009
Citation: Willers, J.L., Jallas, E., McKinion, J.M., Seal, M.R., Turner, S. 2009. Precision farming, myth or reality: Selected case studies from Mississippi cotton fields. In: Papajorgiji, P.J., Pardalos, P.M., editors. Advances in Modeling Agricultural Systems. New York, NY: Springer Science. p. 243-272.

Interpretive Summary: Precision agriculture is a promising technology; however, several limitations involving the management of geo-referenced information hamper its wide-scale application upon commercial production farms. These limitations discussed in this presentation include (1) collecting and managing the large amounts of information necessary to accomplish this micro-management, (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) keeping personnel current with advancements in developing agricultural technologies, (5) refining existing and/or creating new analytical theories useful in agriculture within a multi-disciplinary, multi-institutional and multi-business environment of cooperation, and (6) modifying current practices to enhance environmental conservation and stewardship while complying with governmental regulations, economic constraints, and remain profitable. This chapter develops 4 case studies from the production of cotton to illustrate how these limitations are today’s reality of applications of precision agriculture. The purpose of the chapter is to define these limitations so that developers and/or users of precision agricultural applications can build better solutions for the future.

Technical 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 micro-management, (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) keeping personnel current with advancements in developing agricultural technologies, (5) refining existing and/or creating new analytical theories useful in agriculture within a multi-disciplinary, multi-institutional and multi-business environment of cooperation, and (6) modifying current practices to enhance environmental conservation and stewardship while complying with governmental regulations, economic constraints, and 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.