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Journal of Pharmacognosy and Phytochemistry

Journal of Pharmacognosy and Phytochemistry

Vol. 9, Special Issue 2 (2020)

Statistical model for forecasting production of ginger in India

Author(s):

B Ramana Murthy, S Govinda Rao and SK Nafeez Umar

Abstract:
The present research study was carried out to fit different Linear, Non – Linear and ARIMA models on production of Ginger (Zingiber officinale) in India for the period 1970-71 to 2018-19. Statistically the best fitted model was chosen on the basis of goodness of fit criteria’s like R2, Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). Among all the models, ARIMA (4, 1, 2) was found to be the best fitted model for future forecasting. The results were shown, there is an increasing trend for certain long time of period and then fluctuating for short time of period and again it was increasing for a certain long time of period. It means that for a certain long time of period, the production of Ginger in India has been increasing. Based on this trend to forecast production of Ginger crop for next four years. The forecasted production of Ginger in India for the years 2019-20 to 2020-23 to be 2212.3, 2114.9, 2211.8, 2506.3 in thousand metric tonnes respectively.

Pages: 317-320  |  942 Views  300 Downloads

How to cite this article:
B Ramana Murthy, S Govinda Rao and SK Nafeez Umar. Statistical model for forecasting production of ginger in India. J Pharmacogn Phytochem 2020;9(2S):317-320.

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