| Title |
Modeling and Forecasting of Sugarcane Production in India |
| Authors |
Mishra, P., College of Agriculture, J.N.K.V.V., Powarkheda, MP, India; Al Khatib, A.M.G., Department of Banking and Insurance, Faculty of Economics, Damascus University, Damascus, Syrian Arab Republic; Sardar, I., Department of Mathematics & Statistics, Riphah International University, Islamabad, Pakistan; Mohammed, J., Department of General/Liberal Studies, Faculty of Business and Management Studies, Koforidua Technical University, Koforidua, Ghana; Karakaya, K., Faculty of Science, Department of Statistics, Selçuk University, Konya, Turkey; Dash, A., College of Agriculture, OUAT, Bhubaneswar, India; Ray, M., College of Agriculture, OUAT, Bhubaneswar, India; Narsimhaiah, L., Department of Agril. Statistics, B.C.K.V.V., Kalyani, West Bengal, India; Dubey, A., Departments of Mechanical and Automation Engineering, Amity University Noida, Noida, Uttar Pradesh, India |
| Source title |
Sugar Tech |
| ISSN |
9721525 |
| Q |
Q2 |
| Link |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107470266&doi=10.1007%2fs12355-021-01004-3&partnerID=40&md5=7a24e007ee0031cf17a66be82d01749e |
| Abstract |
Sugarcane plays an essential role in the economy of the India. During 2018, 79.9% of total sugarcane production of India was used in the manufacture of white sugar, 11.29% was used for jaggery production, and 8.80% was used as seed and feed materials. 840.16 Mt sugarcane was exported in the year 2019. Prediction of production level is basic to effective decision-making for policymakers. The objective of this study is thus to find the suitable models of forecasting for sugarcane production. India and major sugarcane producing states, namely Andhra Pradesh, Karnataka, Maharashtra, Tamil Nadu and Uttar Pradesh were selected. Sugarcane production data from 1950 to 2015 were used for training and 2016 to 2018 was used to test the model. ARIMA method was used to model the production process. Order selection was done using AIC. RMSE, MAPE and Theils’ U statistic were used to test the accuracy of the models fitted to the data. ARCH process was found for Karnataka, Tamil Nadu and Uttar Pradesh. Autocorrelation was not present in all the data series analyzed. Forecast accuracy on MAPE criteria ranged from 0.046 to 0.197 percent. |
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