A method of linear correction of above-ground dry matter values, simulated by AFRCWHEAT, a mechanistic model of wheat crop, is described. It uses values of dry matter and green leaf area index observed at previous crop stages. Correction of current simulation is based upon the differences between observed and simulated values of each or both variables for previous stages. The method is tested on three wheat datasets obtained from two locations in France: Avignon and Mons, with various genotypes, sowing dates and crop conditions. A validation test using a cross validation method shows that the mean square error can be reduced down to 12 % of model error, depending on time stage and predictors. This method can be used to improve the prediction of final yield by plant process models, using remotely sensed information.
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