Abstract
The national and state governments require crop production forecasts to make a variety of policy decisions on import-export, storage, distribution, price, and other factors. This article presents a pre-harvest forecasting method specially developed for crops grown in the western region of Haryana (India). The western region includes Hisar, Sirsa, and Bhiwani districts. For crop forecasting in the Hisar, Sirsa, and Bhiwani regions ARIMA and ARIMAX models have been framed. For the development of the ARIMAX model, climate data during the growing season of the crop were used as input along with the crop yield. The percentage difference between the root mean square error and the wheat yield estimations determined by the real-time yield(s) indicates how well-competing models performed in terms of forecasting. The ARIMAX model performs well at all time points with a lower measurement error compared to the ARIMA model.
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Download PDF- The national and state governments require crop production forecasts to make a variety of policy decisions on import-export, storage, distribution, price, and other factors. This article presents a pre-harvest forecasting method specially developed for crops grown in the western region of Haryana (India). The western region includes Hisar, Sirsa, and Bhiwani districts. For crop forecasting in the Hisar, Sirsa, and Bhiwani regions ARIMA and ARIMAX models have been framed. For the development of the ARIMAX model, climate data during the growing season of the crop were used as input along with the crop yield. The percentage difference between the root mean square error and the wheat yield estimations determined by the real-time yield(s) indicates how well-competing models performed in terms of forecasting. The ARIMAX model performs well at all time points with a lower measurement error compared to the ARIMA model.
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