Growth dynamics and forecasting of minor millets in India: A time series analysis R. Prabhu* School of Post Graduate Studies, Tamil Nadu Agricultural University, Coimbatore - 641003 (Tamil Nadu), India M. Uma Gowri Department of Agricultural Economics, Centre for Agricultural and Rural Development Studies, Tamil Nadu Agricultural University, Coimbatore - 641003 (Tamil Nadu), India R. Gayathri Department of Agricultural Economics, Centre for Agricultural and Rural Development Studies, Tamil Nadu Agricultural University, Coimbatore - 641003 (Tamil Nadu), India M. Govindaraj Department of Seed Science and Technology, Tamil Nadu Agricultural University, Coimbatore - 641003 (Tamil Nadu), India G. Manikandan Central Institute of Agricultural Engineering, Regional Centre, Coimbatore - 641007 (Tamil Nadu), India *Corresponding author Email: drrprabhuphd@gmail.com Article Info https://doi.org/10.31018/ jans.v14iSI.3600 Received: March 10, 2022 Revised: May 9, 2022 Accepted: June 4, 2022 This work is licensed under Attribution-Non Commercial 4.0 International (CC BY-NC 4.0). © : Author (s). Publishing rights @ ANSF. ISSN : 0974-9411 (Print), 2231-5209 (Online) journals.ansfoundation.org Research Article INTRODUCTION Millet is an important grain crop in India, especially in areas where deficient water is widespread. Despite its economic consequence, this millet crop has received diminutive consideration (Gowri and Sivakumar, 2020a) compared with other cereal grains, such as rice and wheat (Rimi et al., 2011). These crops are very re- sistant to water stress and drought conditions and tailored to various ecological circumstances (Gowri and Prabhu, 2017). Minor millets are loaded sources of vitamins, minerals and nutrients. All these attrib- utes of small millet cultivation systems lead to cli- mate amends that portend less water and rain, lower malnutrition and high heat (Gowri and Sivakumar, 2020b). Abstract The forecasting behaviour of millet plays a critical role in production planning at the Indian farm level. This study made an effort to forecast the area and production of small millets in India with time series analysis. The performance of the forecasting models was appraised and collated by the Mean Absolute Percentage Error (MAPE), Partial Autocorrelation Function (PACF) and Auto Correlation Function (ACF) criteria. For this analysis, the yearly data of the area and production of small millet from 1950 to 2021 were calculated. Among all Autoregressive Integrated Moving Average (ARIMA) models, ARIMA (0,1,0) was found to be the best fitted for forecasting the area and production of minor millets in India since, principally, this model relies on historical ideals of the sequences in addition to earlier error relations for forecasting minor millets and it does not adopt information of any fundamental model or associations as in some other approaches. The predicted values of minor millet area showed decreased trend from 422.4 thousand hectares in the year 2022 to 409.2 thousand hectares in the year 2026. Likewise, the production under small millets declined from 393.5 thousand tons to 159.5 thousand tons for the corresponding period. Hence, production of these crops can be enhanced by suitable use of inputs and timely application of inputs, high yielding varieties, government interventions like policy support, subsidising through the Public Distribution System and awareness by the way of propaganda and demonstration. Keywords: Area, Forecasting, Minor millets, Production, Time series analysis How to Cite Prabhu, R. et al. (2022). Growth dynamics and forecasting of minor millets in India: A time series analysis. Journal of Applied and Natural Science, 14 (SI), 145 - 150. https://doi.org/10.31018/jans.v14iSI.3600