Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars

Gbegbelegbe Sika, Cammarano Davide, Asseng Senthold, Robertson Richard, Chung U., Adam Myriam, Abdalla O., Payne T., Reynolds Matthew P., Sonder K., Shiferaw B., Nelson G.. 2017. Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars. Field Crops Research, 202 : 122-135.

https://doi.org/10.1016/j.fcr.2016.06.010

Article de revue ; Article de recherche ; Article de revue à facteur d'impact

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Quartile : Q1, Sujet : AGRONOMY

Résumé : Climate change is expected to impact global food supply and food security by affecting growing conditions for agricultural production. Process-based dynamic growth models are important tools to estimate crop yields based on minimum inputs of climate, soil, crop management, and crop cultivar parameters. Using region-specific cultivar parameters is critical when applying crop models at a global scale because cultivars vary in response to climate conditions, soils, and crop management. In this study, parameters were developed for modern cultivars representing all 17 CIMMYT wheat Mega Environments (MEs) using field experimental data and genetic cultivar relationships for the CROPSIM-CERES model in DSSAT v 4.5 (Decision-Support System for Agrotechnology Transfer). Cultivar performance was tested with independent CIMMYT breeding trial field experiments across several locations. Then crop simulations were carried out at 0.5 × 0.5 ° pixels for global wheat-growing areas, using cultivars representing MEs, soil information, region-specific crop management, and initial soil conditions. Aggregated simulated wheat yields and production were compared to reported country yields and production from Food and Agriculture Organization (FAO) statistics, resulting in a Root Mean Square Error (RMSE) of 1.3 t/ha for yield and 2.2 M t/country for country production. Some of the simulated errors are relatively large at country level because of uncertainties in pixel information for climate, soil, and crop management input and partly because of crop model uncertainties. In addition, FAO yield statistics have uncertainties because of incomplete farm reports or poor estimates. Nevertheless, this new cultivar-specific, partially-validated global baseline simulation enables new studies on issues of food security, agricultural technology, and breeding advancement impacts combined with climate change at a global scale.

Mots-clés Agrovoc : modèle de simulation, Triticum durum, rendement des cultures, variété, amélioration des plantes, sécurité alimentaire, modélisation des cultures, changement climatique, adaptation aux changements climatiques, expérimentation au champ, essai de variété