›› 2017, Vol. 44 ›› Issue (1): 131-140.doi: 10.16431/j.cnki.1671-7236.2017.01.018

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Predicting the Dairy Cow Somatic Cell Number of Ningxia Area Based on ARIMA Model

LI Xin1, SHAO Huai-feng2, WEN Wan2, TUO Zheng-jun2, ZHANG Wei-xin2, GU Ya-ling1   

  1. 1. Laboratory of Animal Production, Agricultural College, Ningxia University, Yinchuan 750105, China;
    2. Laboratory of Dairy Herd Improvement, Ningxia Animal Husbandry and Veterinary Station, Yinchuan 750105, China
  • Received:2016-04-18 Online:2017-01-20 Published:2017-01-19

Abstract:

Through dairy herd improvement (DHI) data analysis to predict somatic cell count (SCC) of Ningxia area in time, which providing a reference for the prevention and treatment of mastitis in dairy cows, making the DHI data more effective and timely in guiding the dairy industry production. Using the difference method to make the average cow somatic cell data form September 2011 to February 2016 stabled, then used the seasonal ARIMA model to analysis, fitting and forecasting data. The auto.arima function of R software had been used to calculate the optimal time series that finally confirmed the model was ARIMA (1,1,0)(1,1,0)[12], AIC was -3.67. The Acf test showed that the residual had no significant autocorrelation; Ljung-Box test showed that all P-value>0.5, indicating that the residual was white noise, and this model could be used to make predication for the next 24 months. The forecast function of the R software was used to predict the dairy cows SCC from March 2016 to February 2017, and the forecast map was drawn. The predicted results showed that the SCC of the entire Ningxia area were showing a downward trend. The SCC would be the least in January 2017,and the predictive value was about 253 100 per mL. It would be the largest in March 2016, was about 439 600 per mL. The results also showed that the dairy cows SCC in Ningxia was higher than the critical value of 20 million of subclinical mastitis. It suggested that the prevention and treatment of dairy cow mastitis need to be strengthened in Ningxia area. At the same time, if the data of the dairy cows SCC was added in timely, the data model should be updated to make it more close to the true value, which would be more meaningful to the actual instruction.

Key words: time series; dairy cow; somatic cell count; seasonal ARIMA model; forecast

CLC Number: