The Azodyn crop model as a decision support tool for choosing cultivars

We evaluated the Azodyn wheat crop model as a cultivar decision support tool using a set of 14 genotypes, tested in 21 contrasting environments. The results showed that the Azodyn crop model satisfactorily simulated yield and grain protein content for a large range of genotypes and environments, as shown by a root mean square error of 1.4 Mg ha(-1) and 1.7 g 100 g MS-1, respectively. The comparison between the observed and the simulated rankings of genotypes showed a ranking error of the model of one rank or less. The model was able to identify the best genotype to be used to obtain the highest yield in 20 cases out of 33 and the highest grain protein content in 48 cases out of 64. As a new way to evaluate crop models as a decision support tool for cultivar choice, we compared the Azodyn predictive accuracy against the cultivar yield and grain protein average generally used by cultivar growers as a predictive model. We showed that in the main production conditions, the Azodyn predictions fit the yield and grain protein content observed better than the average.