Determining optimum sowing date of wheat using CSM-CERES-Wheat model

By B. Andarzian, Gerrit Hoogenboom, M. Bannayan, M. Shirali, B. Andarzian. 2015

78 citations recorded by the source corpus.

Wheat production in the south of Khuzestan, Iran is constrained by heat stress for late sowing dates. For optimization of yield, sowing at the appropriate time to fit the cultivar maturity length and growing season is critical. Crop models could be used to determine optimum sowing win- dow for a locality. The objectives of this study were to evaluate the Cropping System Model (CSM)- CERES-Wheat for its ability to simulate growth, development, grain yield of wheat in the tropical regions of Iran, and to study the impact of different sowing dates on wheat performance. The genetic coefficients of cultivar Chamran were calibrated for the CSM-CERES-Wheat model and crop model performance was evaluated with experimental data. Wheat cultivar Chamran was sown on different dates, ranging from 5 November to 9 January during 5 years of field experiments that were conducted in the Khuzestan province, Iran, under full and deficit irrigation conditions. The model was run for 8 sowing dates starting on 25 October and repeated every 10 days until 5 January using long-term historical weather data from the Ahvaz, Behbehan, Dezful and Izeh locations. The seasonal analysis program of DSSAT was used to determine the optimum sowing window for different locations as well. Evaluation with the experimental data showed that performance of the model was reasonable as indicated by fairly accurate simulation of crop phenology, biomass accumulation and grain yield against measured data. The normalized RMSE were 3%, 2%, 11.8%, and 3.4% for anthesis date, maturity date, grain yield and biomass, respectively. Optimum sowing window was different among locations. It was opened and closed on 5 November and 5 December for Ahvaz; 5 November and 15 December for Behbehan and Dezful;and 1 November

Subfields: Agronomy and Crop Science, Ecology, Evolution, Behavior and Systematics, Plant Science

View Paper: https://www.semanticscholar.org/paper/7a937af3a767f70f8c2186641fb4bb25e78bc670

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Citations in the corpus

How well do crop modeling groups predict wheat phenology, given calibration data from the target population? (2019, background): “In many evaluation studies, this independence of calibration and evaluation data is not strictly satisfied, for example because the same sites appear in both data sets (Andarzian et al., 2015; Hussain et al., 2018; Yuan et al., 2017).”
Consequences and Mitigation Strategies of Abiotic Stresses in Wheat (Triticum aestivum L.) under the Changing Climate (2021, background): “Crop simulation models that assess the complex phenomena amongst the plantsoil-atmosphere continuum and farmers’ management practices, might be a very useful tool for determining the suitable cropping window for achieving the maximum yield vis-àvis alleviating the abiotic stress in wheat [273,274].”