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A simple and parsimonious generalised additive model for predicting wheat yield in a decision support tool

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  • Chen, Kefei
  • O'Leary, Rebecca A.
  • Evans, Fiona H.

Abstract

Yield prediction is a major determinant of many management decisions for crop production. Farmers and their advisors want user-friendly decision support tools for predicting yield. Simulation models can be used to accurately predict yield, but they are complex and difficult to parameterise. The goal of this study is to build a simple and parsimonious model for predicting wheat yields that can be implemented in a decision tool to be used by farmers at a paddock level.

Suggested Citation

  • Chen, Kefei & O'Leary, Rebecca A. & Evans, Fiona H., 2019. "A simple and parsimonious generalised additive model for predicting wheat yield in a decision support tool," Agricultural Systems, Elsevier, vol. 173(C), pages 140-150.
    • Handle: RePEc:eee:agisys:v:173:y:2019:i:c:p:140-150
    DOI: 10.1016/j.agsy.2019.02.009
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    References listed on IDEAS

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    Cited by:

    1. Anna Florence & Andrew Revill & Stephen Hoad & Robert Rees & Mathew Williams, 2021. "The Effect of Antecedence on Empirical Model Forecasts of Crop Yield from Observations of Canopy Properties," Agriculture, MDPI, vol. 11(3), pages 1-16, March.
    2. Denis A Shah & Erick D De Wolf & Pierce A Paul & Laurence V Madden, 2021. "Accuracy in the prediction of disease epidemics when ensembling simple but highly correlated models," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-23, March.
    3. Irina Pilvere & Aleksejs Nipers & Agnese Krievina & Ilze Upite & Daniels Kotovs, 2022. "LASAM Model: An Important Tool in the Decision Support System for Policymakers and Farmers," Agriculture, MDPI, vol. 12(5), pages 1-26, May.
    4. Bazrafshan, Ommolbanin & Ehteram, Mohammad & Moshizi, Zahra Gerkaninezhad & Jamshidi, Sajad, 2022. "Evaluation and uncertainty assessment of wheat yield prediction by multilayer perceptron model with bayesian and copula bayesian approaches," Agricultural Water Management, Elsevier, vol. 273(C).

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