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Assessment of CERES-Maize model in simulating maize growth, yield and soil water content under rainfed, limited and full irrigation

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  • Amiri, E.
  • Irmak, S.
  • Araji, H. Ahmadzadeh

Abstract

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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  • Amiri, E. & Irmak, S. & Araji, H. Ahmadzadeh, 2022. "Assessment of CERES-Maize model in simulating maize growth, yield and soil water content under rainfed, limited and full irrigation," Agricultural Water Management, Elsevier, vol. 259(C).
    • Handle: RePEc:eee:agiwat:v:259:y:2022:i:c:s0378377421005485
    DOI: 10.1016/j.agwat.2021.107271
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    References listed on IDEAS

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    1. Kaur, Rajbir & Arora, VK, 2018. "Assessing spring maize responses to irrigation and nitrogen regimes in north-west India using CERES-Maize model," Agricultural Water Management, Elsevier, vol. 209(C), pages 171-177.
    2. Kadiyala, M.D.M. & Jones, J.W. & Mylavarapu, R.S. & Li, Y.C. & Reddy, M.D., 2015. "Identifying irrigation and nitrogen best management practices for aerobic rice–maize cropping system for semi-arid tropics using CERES-rice and maize models," Agricultural Water Management, Elsevier, vol. 149(C), pages 23-32.
    3. Malik, Wafa & Dechmi, Farida, 2019. "DSSAT modelling for best irrigation management practices assessment under Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 216(C), pages 27-43.
    4. da S. Andrea, Maria Carolina & Boote, Kenneth J. & Sentelhas, Paulo C. & Romanelli, Thiago L., 2018. "Variability and limitations of maize production in Brazil: Potential yield, water-limited yield and yield gaps," Agricultural Systems, Elsevier, vol. 165(C), pages 264-273.
    5. Zhang, Huihui & Ma, Liwang & Douglas-Mankin, Kyle R. & Han, Ming & Trout, Thomas J., 2021. "Modeling maize production under growth stage-based deficit irrigation management with RZWQM2," Agricultural Water Management, Elsevier, vol. 248(C).
    6. Araya, A. & Kisekka, Isaya & Gowda, Prasanna H. & Prasad, P.V. Vara, 2017. "Evaluation of water-limited cropping systems in a semi-arid climate using DSSAT-CSM," Agricultural Systems, Elsevier, vol. 150(C), pages 86-98.
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