TIME SERIES MODELLING AND FORECASTING OF PRICES OF CATTLE FEED IN TAMIL NADU

S. Gokulakrishnan; G. Senthil Kumar; A. Serma Saravana Pandian; J. Ramesh; P. Thilakar; L. Radhakrishnan; A. Ruba Nanthini

doi:10.56093/ijvasr.v53i2.152716

Authors

S. Gokulakrishnan Ph.D. Scholar, Department of Animal Husbandry Economics, Madras Veterinary College, TANUVAS, Chennai - 7
G. Senthil Kumar Associate Professor, Department of Dairy Business Management, College of Food and Dairy Technology, Koduveli, Chennai - 52
A. Serma Saravana Pandian Professor and Head, Department of Animal Husbandry Economics, Veterinary College and Research Institute, Namakka
J. Ramesh Professor and Head, Veterinary University Training and Research Centre, Melmaruvathur
P. Thilakar Professor and Head, Department of Veterinary and Animal Husbandry Extension Education, Veterinary College and Research Institute, Tirunelveli
L. Radhakrishnan Professor and Head, Department of Animal Nutrition, Madras Veterinary College, Chennai - 7
A. Ruba Nanthini Assistant Professor, Central Feed Technology Unit, Kattupakkam - 603 203

https://doi.org/10.56093/ijvasr.v53i2.152716

Keywords:

ARIMA, Cattle, Feed prices, Forecasting, Time series model

Abstract

The quantum of inclusion of concentrates in cattle feeding depends solely on availability and its price. An attempt was made to model and forecast the feed prices of dairy cattle feed in Tamil Nadu using time series data collected from Central Feed Technology Unit, Kattupakkam for the period from January 2012 to December 2022. Various time series models viz., Mean, Naïve, Random drift, Seasonal naive, Simple Exponential Smoothing, Holt linear, Holt-winter, Autoregressive Integrated Moving Average - ARIMA and Seasonal Autoregressive Integrated Moving Average models were fitted. The error measures, parameter estimates, forecast estimates and plots were assessed to ascertain the best fit model. Random drift model and ARIMA (0,1,0) model were found to be the best fit models for dairy cattle feed. Further, Holt-winter multiplicative model and SARIMA (1,1,0)(1,0,1) model were identified as the best fit models for the dry cattle feed price forecasting. Thus, these models could be utilized by the various stakeholders to predict the short term price forecasts of cattle feed for efficient planning and making right decisions.

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