Revisión: modelos de crecimiento y rendimiento de maíz en escenarios de cambio climático

Climate change (CC) affects the current meteorological conditions and negatively affects the yield of corn, particularly during the rainy season. To estimate the effects of CC on productivity, growth simulation models have been used under different climate change scenarios. This article reviews the models implemented globally, during the period 2006 to 2019, through Scopus and Google Scholar. The reported models are mechanistic, dynamic and stochastic, such as DSSAT-CERES-Maize, APSIM-Maize, CropSyst, AquaCrop, EPIC-Maize, CropWat InfoCrop, and WOFOST. Simulations in various scenarios report decreased corn yields in Sub-Saharan Africa (78%), China (70%), Latin America (61%) and the Middle East (45%), and increases in the European Union (71%), Belt American Corn (57%), Middle East (45%) and India (44.5%). In Mexico, there are estimates of increases in corn yields from 5 to 22% considering the effects of carbonic fertilization, and reductions of up to 49.3% under other conditions. It is necessary to deepen studies on CC effects in the different regions of the country and implement models that can be used to design adaptation and mitigation policies and strategies, given the negative effects of CC in Mexican agriculture.