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Decision Support for Economic and Environmental Impact of Tractor Guidance on Small Crop and Livestock Farms

Author

Listed:
  • Lindsay, Karen
  • Popp, Michael
  • Ashworth, Amanda
  • Owens, Phillip

Abstract

The Tractor Guidance Analysis Model (TGA) was developed to assist small-scale crop and livestock producers, consultants, and extension personnel with analyzing the adoption of auto-steer tractor guidance to improve yields, reduce input use, extend workdays, and thereby enhance the efficiency of machinery and tractor operators. Using the Microsoft Excel® software platform, TGA utilizes default efficiency gain measurements observed at the USDA ARS Booneville Small Farm Research center and/or existing literature to provide a decision-support tool that performs partial budgeting and breakeven analyses for user-specified farm operations. For example, is the decision to invest in less accurate technology at a lower cost more economical than expensive technology with better accuracy? How sensitive are feasibility results to purported efficiency gains when field attributes such as slope and field shape irregularity change? At what level of annual use will the technology pay off with changeable equipment when growing different field crops, managing weeds on, and/or establishing pasture? This automated decision-support software provides user flexibility for operation-specific details and tracks technology-driven changes in fertilizer, fuel, seed, labor, and chemical inputs to both estimate the profitability of tractor guidance investment, the breakeven annual use needed to make the investment feasible, and the potential environmental impact.

Suggested Citation

  • Lindsay, Karen & Popp, Michael & Ashworth, Amanda & Owens, Phillip, 2018. "Decision Support for Economic and Environmental Impact of Tractor Guidance on Small Crop and Livestock Farms," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266572, Southern Agricultural Economics Association.
  • Handle: RePEc:ags:saea18:266572
    DOI: 10.22004/ag.econ.266572
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    Keywords

    Farm Management;

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