Factors associated with market weight on three New Zealand pig farms

The aim of this observational study was to identify performance parameters, which can be used to predict market weight of a batch of pigs on commercial farms. Weekly retro- and prospective production records were obtained from three New Zealand pig farms. Observation periods on farms A, B, and C were 140, 127 and 90 weeks. Two modelling approaches were used for multivariable analysis to account for autocorrelation: An autoregressive (AR) and an ordinary least squares (OLS) regression model ( naive approach ). Each farm was analysed separately. Using an AR-model, four production parameters (weaning age, two sample weights and days to market) were identified across all farms that were effective in predicting market weight with accuracies greater than 70%. All AR-models yielded stationary and normally distributed residuals. In contrast, residuals of the OLS-models showed remaining autocorrelation on two farms indicating biased model estimates. Using an AR-model also has the advantage that immediate future observations can be forecasted. This is particularly useful as predictor variables (apart from 'Days to market') could be obtained a month prior to marketing.

Autorentext

Dr Birgit Schauer, studied veterinary medicine at Ludwig-Maximilian-Univ (LMU). Specialized in epidemiology. German doctorate (joint project betw. LMU and EpiCentre, Massey, NZ). MVSt at the EpiCentre. Since 2008, technical manager of an avian influenza research project in Vietnam (NZAID; Dep. of Animal Health, Vietnam; EpiCentre).