Matching the model to the available data to predict wheat, barley, or canola yield: A review of recently published models and data

Robert Clark, Peter Dahlhaus, Nathan Robinson, Jo-ann Larkins and Elizabeth Morse-McNabb

Agricultural Systems, 2023, vol. 211, issue C

Abstract: Continued increases in global population and rising living standards in many countries are driving a surge in demand for energy and protein-rich foods. Wheat, barley, and canola are important crops that are grown and traded globally. However, climate change, geopolitical tensions and competition from other crops threaten the ability to satisfy global demand. Accurate predictions of crop production and its spatial variation can play a significant role in their reliable and efficient production, marketing, and distribution.

Keywords: Review; Yield prediction models; Agrometeorological data; Remotely sensed data; Quantitative analysis; Model performance (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:211:y:2023:i:c:s0308521x23001543

DOI: 10.1016/j.agsy.2023.103749

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