Forecasting of milk production of crossbred dairy cattle by Autoregressive Integrated Moving Average (ARIMA) model
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Authors
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Rohit Sharma
Lala Lajpat Rai University of Veterinary & Animal Sciences, Hisar, Haryana
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JK Chaudhary
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Sanjeev Kumar
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Ranjit Rewar
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Sandeep Kumar
Keywords:
Forecasting, Milk production, ARIMA, ACF, PACFAbstract
The objective of this study was to forecast the milk production in crossbred dairy cattle. In this study secondary data was used, collected from Livestock Farm of CVSc. & A.H., CAU, Aizawl, Mizoram, from year 2010 to 2019. The main focus of our study was based on forecasting through ARIMA model. To perform exploratory information examination, box-plot was used while stationarity of data was checked with Augmented Dicker-fuller test, Autocorrelation Function (ACF) and Partial autocorrelation function (PACF). Model fit checking and forecasting of milk was done through software package R. The results indicated that ARIMA (1, 0, 0) was the most suitable model for forecasting of milk for our dataset. Milk production is expected to be 1910.20 litres by 2022 with 95% confidence interval.
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