Publications Wednesday: even better grain yield forecasts

January 15th, 2020


Using semi-empirical indices for drought, heat and cold stress measurably improves the accuracy of the C-Crop grain yield forecasting model. Digiscape early-career researcher Yang Chen and colleagues have shown this in a paper just published by Agricultural and Forest Meteorology.

One of the clever features of Dr Chen’s new Crop-SI model is the way it exploits our physiological understanding of crops: the stress indices are computed at the times in the growing season where they will impact on yields.

This research forms part of Digiscape’s Graincast project. The full paper can be found here.


Comparing the Crop-SI models' paddock-scale yield predictions with the current C-Crop model