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|Title:||Wheat modelling in Morocco unexpectedly reveals predominance of photosynthesis versus leaf area expansion plant traits|
|Authors:||CONFALONIERI Roberto; BREGAGLIO Simone; CAPPELLI Giovanni; FRANCONE Caterina; CARPANI Marta; ACUTIS Marco; EL AYDAM Mohamed; NIEMEYER Stefan; BALAGHI Raid; DONG Qinghan|
|Citation:||AGRONOMY FOR SUSTAINABLE DEVELOPMENT vol. 32|
|Type:||Articles in periodicals and books|
|Abstract:||Wheat is the staple food of 1.5 billion people worldwide and projected trends in global demand and productivity warn against food security risks over the next decades. Large-area crop monitoring and yield forecasting represent key issues to support agricultural policies, especially in developing countries. Among the existing monitoring systems, the most sophisticated are based on crop simulation models. Published reports of sensitivity analyses performed on different crop models show that parameters involved with leaf area expansion are often considered as the most relevant. Here we performed a multi-year spatially-distributed Monte Carlo-based sensitivity analysis of the models WOFOST and CropSyst for wheat simulation in Morocco. Due to the high number of sensitivity analyses to be performed, a 2-step procedure was adopted, with the Morris method used to identify parameters with a negligible effect and the Sobol' one applied on those remaining. Environmental and management information were derived from the European Commission MARS database. Our results show that parameters directly involved with photosynthesis played a major role: they explained more than 75% of the total output variance for CropSyst and more than 70% for WOFOST. Instead, parameters involved with the processes related to leaf area expansion resulted less relevant. The geographical patterns in terms of the relevance of parameters and processes shown by the same models under heterogeneous conditions could provide useful guidelines for driving breeders efforts towards specific plant traits, in the light of developing phenotypes suitable for specific conditions, e.g., varieties with a higher level of thermal adaptation in the Southern regions. This is the first time a multi-year spatially-distributed sensitivity analysis is carried out on two complex agro-ecological models.|
|JRC Directorate:||Sustainable Resources|
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