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This technical report describes a statistical model for predicting wheat crop yields in Canadian prairie provinces. The model incorporates a crop water stress index (SI) as an explanatory variable to account for the influence of soil water on yields. A Bayesian model is developed that jointly models crop yields across 40 agricultural regions, allowing strength to be borrowed between nearby regions to improve predictions. The model provides efficient predictions by extracting a low-dimensional summary of the

Author

Frontiers

Language

EN