Abstract :
[en] Crop simulation models are valuable tools widely applied in various climatic conditions to evaluate and recommend the optimal crop management practices in order to improve crop production, specifcally for the rainfed crop production that is mainly affected by recurrent drought and blocked by low inputs of fertilizers and by disease and crop pests. Therefore, as part of a major objective focused on the application of two models to improve wheat management practices in Moroccan rainfed areas, the purpose of this research study is using a database of measured and observed wheat growth and production state variables to calibrate and evaluate CERES-wheat and APSIM-wheat models for the simulation of wheat growth and prediction of yield of ve wheat cultivars widely used in the Moroccan rainfed areas. During three crop seasons (from 2019 to 2021), crop management information, wheat growth state variables and grain yield were collected during critical growth stages of wheat development from more than 120 of farmers’ felds covering the main agro-climatic Moroccan rainfed areas. During calibration process, measured data of two successive crop seasons (2018 and 2019) were employed to estimate the models genetic coeffcients of the five studied cultivars. Independent data sets of 2021 crop season were used to evaluate APSIM-wheat model performances. Based upon validation process, in the comparison with measured and observed collected dataset, the two models simulate with good accuracies the wheat development stages,
above-ground biomass and yield for all cultivars, whereas, the models simulation have overestimate leaf area index values. After the acceptable results of the two wheat models performances in Moroccan rainfed areas, we made certain that these models will serve as valuable tools to be applicate in improving wheat management practices of Moroccan farmers, speci cally, fertilization advices.
