Abstract
Abstract Numerous modelling efforts have focused on maize as it is an important cereal crop for both human consumption and livestock production. Crop simulation and multi-linear regressions models can be used to quantify the likely potential impacts of climate change on maize growth and yield. Such models include AquaCrop, Agricultural Production Systems Simulator (APSIM), Decision Support System for Agro-technology Transfer (DSSAT), EPIC, CropSyst, Root Zone Water Quality Model (RZWQM2), SARRA-H, IMPACT+DSSAT, DSSAT, ALAMANC, WOFOST, ADEL, GEPIC, Empirical, MOS, GLAM-Maize, InfoCrop and EcoCrop, among others. Models give predictions utilizing meteorological, soil and crop data in numerical simulations. Various sources of climatic data are available including government meteorological and research departments, world organizations and private institutions. Climate data can also be generated using statistical and dynamical downscaling tools. The review showed that future maize growth and yield would be affected by changes in precipitation, temperature and soil fertility. Rise in temperature is the major factor altering maize yield. Nevertheless, crop simulation models have been observed to give mixed results depending on the region and the crop. Sources of uncertainty in predictions have been attributed to challenges in model parameterization, calibration and validation.
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