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Future

In: Machine Learning and Artificial Intelligence for Agricultural Economics

Author

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  • Chandrasekar Vuppalapati

    (San Jose State University)

Abstract

Agriculture is filled with uncertainties, risks, losses, and back-breaking work. Yet, the returns on agriculture, especially for small farmers, are miniscule or, in some cases, non-existent. No wonder, many small farms have disappeared in the United States, and the same trend can be witnessed worldwide. There are two kinds of risks that farmers face: internal and external farm risks. Internal farm risk is easily controlled by the farmers. The risks are related to soil, fertilizers, phenological stages of a crop, and personal/family issues. The risks related to external farm, for example, commodity price variations, macroeconomic conditions, real-time price models’ unintended consequences, trade wars, sudden changes in people tastes and perception of a food commodity, and global climate change, are something beyond farmers’ control.

Suggested Citation

  • Chandrasekar Vuppalapati, 2021. "Future," International Series in Operations Research & Management Science, in: Machine Learning and Artificial Intelligence for Agricultural Economics, chapter 0, pages 551-551, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-77485-1_8
    DOI: 10.1007/978-3-030-77485-1_8
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