Time Series Analysis of Cattle Population and Its Effect on Some Greenhouse Gases in Brazil

In this study, the number of cattle for the period 1961–2020 in Brazil was modeled with time series. The series is not stationary at the level, but becomes stationary after the first difference is taken. According to the autocorrelation (ACF) and partial autocorrelation (PACF) graphs of the first difference series, it is seen that the series has a first-order integrated moving average model (ARIMA (0,1,1)). According to the ARIMA (0,1,1) model, the forecast for the years 2021–2030 has been made. According to these model, there will be an increase of 12.72% in the number of cattle at the end of the next 10 years. The relationship between the cattle population and methane (CH4) and nitrous oxide (N2O) values, which play an important role in climate change, was analyzed by regression analysis. The inverse regression model is the most suitable regression model for the cattle population with both methane (CH4) and nitrous oxide (N2O) values. According to the inverse regression model, the R2 values for the bovine population-CH4 gas and cattle population-N2O relationship were found to be 0.904 and 0.936, respectively.