How well do crop modeling groups predict wheat phenology, given calibration data from the target population?

摘要: Predicting phenology is essential for adapting varieties to different environmental conditions and crop management. Therefore, it important evaluate how well modeling groups can predict phenology. Multiple evaluation studies have been previously published, but still difficult generalize the findings from such since they often test some specific aspect of extrapolation new conditions, or do not on data that truly independent used calibration. In this study, we analyzed prediction wheat in Northern France under observed weather current management, which a problem practical importance The results 27 are evaluated, where group encompasses model structure, i.e. equations, calibration method values those parameters affected by sampled same target population, thus limited. neither year nor site common, guarantee rigorous sites. best groups, also mean median simulations, absolute error (MAE) about 3 days, comparable measurement error. Almost all models better than using average number days sum degree On other hand, there differences between due structural emphasizes structure alone does completely determine accuracy. addition providing information our environments varieties, these useful contribution knowledge base phenology, when provided with population.