Use of CERES-Maize to study effect of spatial precipitation variability on yield

Effects of climate change on maize production, and potential adaptation measures: a case study in Jilin Province, China

“…Thus, the CERES-Maize model has the capacity to provide critical information for identifying potential adaptation options. The model has been widely validated across different climate and soil conditions for different varieties (Wu et al 1989, Maytín et al 1995, O'Neal et al 2002, Gungula et al 2003, Soler et al 2007, Braga et al 2008. In Jilin, Jin et al (1996Jin et al ( , 2002 used it in the projection of maize yields at specific locations based on the double CO 2 climate scenarios derived from 3 GCMs, and suggested several adaptation options.…”

Identifying irrigation and nitrogen best management practices for aerobic rice–maize cropping system for semi-arid tropics using CERES-rice and maize models

“…CERES (Crop Estimation through Resource and Environment Synthesis)-Rice and -Maize are process-based models embedded in DSSAT simulate the main processes of crop growth and development such as phenological development, canopy leaf area growth, dry matter accumulation and grain yield. The CERES-Rice andMaize models were evaluated by many researchers across locations (Sarkar and Kar, 2006;Timsina and Humphreys, 2006;O'Neal et al, 2002;Behera and Panda, 2009;Liu et al, 2011;He et al, 2012;Salmerón et al, 2012;Jeong et al, 2014;Ngwira et al, 2014) with good agreements between predicted and observed values. Even though simulation results generally will have some uncertainties associated with inputs and model parameters, but still the simulation models can be effectively utilized as a scientific tool to increase the resource use efficiency of cropping systems (Timsina and Connor, 2001;Sarkar and Kar, 2008;Timsina and Humphreys, 2006;Timsina et al, 2008).…”

Corn‐yield estimation through assimilation of remotely sensed data into the CSM‐CERES‐Maize model

“…It is equally important to consult local practising agronomists. Some laboratory and field observational data obtained in similar studies (O'Neal et al 2002), grown under similar conditions, were used as the initial values in a previous phase to adapt some model coefficients to the regional context. All data were transformed and reprojected to a 1-km resolution with a Universal Transverse Mercator (UTM) projection.…”