Optimum Sowing Window And Yield Forecasting For Maize In Northern And Western Bangladesh Using Ceres Maize Model

AGRONOMY-BASEL(2021)

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Abstract
Determination of the optimum sowing window not only can improve maize yield significantly but also can fit maize in the existing cropping pattern. To get the advantages of sowing maize at the optimum time, a study was designed and carried out at the research field of Bangladesh Agricultural Research Institute, Rangpur, Bangladesh during 2015-2017. Another aim of the study was to forecast the yield of maize for the northern and western regions of Bangladesh using the CERES-Maize model. The study considered 5 November, 20 November, 5 December, 20 December, and 5 January as sowing dates for maize to identify the optimum sowing window. Three hybrid maize varieties, viz., BARI Hybrid Maize-9 (BHM-9), NK-40, and Pioneer30V92 were used. The study was laid out in a split-plot design, assigning the sowing dates in the main plot and the varieties in the sub-plot. To forecast the yield, the daily weather data of 2017 were subjected to run the model along with thirty years (1986-2015) of weather data. The genetic coefficients of the tested maize varieties were obtained through calibration of the model by using the observed field data of 2015-2016 and through validation by using the data of 2016-2017. The seasonal analysis was done using the DSSAT CERES-Maize model to confirm the experimental findings for optimizing the sowing window for maize at the northern region (Rangpur) of the country and subsequently adjusted the model for the western region (Jashore). The model performances were satisfactory for crop phenology, biomass, and grain yield. The NRMSE for anthesis was 0.66% to 1.39%, 0.67% to 0.89% for maturity date, 1.78% to 3.89% for grain yield, and 1.73% to 3.17% for biomass yield. The optimum sowing window for maize at the Rangpur region was 5 November to 5 December and 5 to 20 November for the Jashore region. The CERES-Maize model was promising for yield forecasting of the tested maize varieties. It gave a realistic yield forecast at approximately 45 days prior to the harvest of all the tested varieties. The study results are expected to be useful for both the farmers and the policy planners to meet up the future maize demands.
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Key words
climate change, crop model, grain yield, maize, sowing window, yield forecast
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