Abstract

Monthly test-day milk yields of 1200 dairy Sarda ewes were analyzed by time-series methods. Autocorrelation functions were calculated for lactations within parity classes and altitude of location of flocks. Spectral analysis of the successions of data was developed by Fourier transformation, and different Box-Jenkins autoregressive integrated moving average models were fitted. The separation of deterministic and stochastic components highlighted the autoregressive feature of milk production pattern. The forecasting power of autoregressive integrated moving average models was tested by predicting total milk production for a standardized lactation length of 225 d from only a few testday records. Results indicated a greater forecasting capacity in comparison with standard methods and suggested further development of time-series analysis for studying lactation curves with more sophisticated methods, such as wavelet decomposition and neural network models.

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