TY - JOUR
T1 - Assessment of CERES-Maize model in simulating maize growth, yield and soil water content under rainfed, limited and full irrigation
AU - Amiri, E.
AU - Irmak, S.
AU - Araji, H. Ahmadzadeh
N1 - Funding Information:
This study is based upon work that is supported by the National Institute of Food and Agriculture , U.S. Department of Agriculture, Professor Suat Irmak’s Hatch Project, under the Project Number NEB-21-155 .
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - CERES-Maize is a crop simulation model that can be applied as a tool to simulate grain yield, above-ground biomass, leaf area index (LAI), soil-water components (SWC), and other variables related to crop production. The model was calibrated and validated using long-term (2005–2010) field-measured data under full irrigation treatment (FIT), limited irrigation treatments (50%, 60% and 75% of FIT) and rainfed conditions in a transition zone between the subhumid and semi-arid climatic region in Nebraska, USA. Model performance was evaluated using the coefficient of determination (R2), absolute and normalized root mean squared errors (RMSE and RMSEn, respectively) between simulated and measured data. The RMSE between model-simulated and observed data for days after planting to flowering (DAPF) and maturity day (DAPM) were 3 and 13 days, respectively. There was an acceptable agreement between simulated and observed LAI (RMSEn = 17% and R2 = 0.79) and above-ground biomass (RMSEn = 16% and R2 = 0.95). Grain yield estimates by the model showed moderately high R2 (≥ 0.80) and moderate RMSEn (3–18%) values, confirming that the model simulated the grain yield accurately. The accuracy of the model in simulating SWC in FIT conditions was good, but with increasing water stress, the accuracy decreased. The cumulative drought stress index for photosynthesis (SIP) and drought stress index for leaf expansion (SIE) were also simulated and evaluated. There was an inverse relationship between grain yield and the SIP and SIE (R2 ≥ 0.97), indicating the potential applicability of SIP and SIE for estimating maize grain yield. Both SIP and SIE were strongly affected by the irrigation treatments. The FIT treatment had a value of 2 for cumulative SIE, indicating that this treatment was rarely exposed to drought/water stress. The results showed that irrigation and early planting date together had synergistic effects on grain yield. Delaying planting dates for the FIT led to yield reduction of 1%, 3% and 11% after planting dates of April 30, May 10 and May 20, respectively. Delay in planting date under rainfed led to greater yield reduction of 6%, 10% and 18% after planting dates of April 30, May 10 and May 20, respectively. The CERES-Maize model simulated maize crop parameters relatively accurately under rainfed, full and limited irrigation management conditions under the experimental and climatic conditions presented in this study and can be a viable tool for simulating various management scenarios for increasing maize productivity.
AB - CERES-Maize is a crop simulation model that can be applied as a tool to simulate grain yield, above-ground biomass, leaf area index (LAI), soil-water components (SWC), and other variables related to crop production. The model was calibrated and validated using long-term (2005–2010) field-measured data under full irrigation treatment (FIT), limited irrigation treatments (50%, 60% and 75% of FIT) and rainfed conditions in a transition zone between the subhumid and semi-arid climatic region in Nebraska, USA. Model performance was evaluated using the coefficient of determination (R2), absolute and normalized root mean squared errors (RMSE and RMSEn, respectively) between simulated and measured data. The RMSE between model-simulated and observed data for days after planting to flowering (DAPF) and maturity day (DAPM) were 3 and 13 days, respectively. There was an acceptable agreement between simulated and observed LAI (RMSEn = 17% and R2 = 0.79) and above-ground biomass (RMSEn = 16% and R2 = 0.95). Grain yield estimates by the model showed moderately high R2 (≥ 0.80) and moderate RMSEn (3–18%) values, confirming that the model simulated the grain yield accurately. The accuracy of the model in simulating SWC in FIT conditions was good, but with increasing water stress, the accuracy decreased. The cumulative drought stress index for photosynthesis (SIP) and drought stress index for leaf expansion (SIE) were also simulated and evaluated. There was an inverse relationship between grain yield and the SIP and SIE (R2 ≥ 0.97), indicating the potential applicability of SIP and SIE for estimating maize grain yield. Both SIP and SIE were strongly affected by the irrigation treatments. The FIT treatment had a value of 2 for cumulative SIE, indicating that this treatment was rarely exposed to drought/water stress. The results showed that irrigation and early planting date together had synergistic effects on grain yield. Delaying planting dates for the FIT led to yield reduction of 1%, 3% and 11% after planting dates of April 30, May 10 and May 20, respectively. Delay in planting date under rainfed led to greater yield reduction of 6%, 10% and 18% after planting dates of April 30, May 10 and May 20, respectively. The CERES-Maize model simulated maize crop parameters relatively accurately under rainfed, full and limited irrigation management conditions under the experimental and climatic conditions presented in this study and can be a viable tool for simulating various management scenarios for increasing maize productivity.
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U2 - 10.1016/j.agwat.2021.107271
DO - 10.1016/j.agwat.2021.107271
M3 - Article
AN - SCOPUS:85117377758
SN - 0378-3774
VL - 259
JO - Agricultural Water Management
JF - Agricultural Water Management
M1 - 107271
ER -