A predictive model to evaluate the impact of the cooling profile on growth of psychrotrophic bacteria in raw milk from conventional and robotic milking.

Abstract

This Research Communication explores the usefulness of predictive modelling to explain bacterial behaviour during cooling. A simple dynamic lag phase model was developed and validated. The model takes into account the effect of the cooling profile on the lag phase and growth in bulk tank milk. The time before the start of cooling was the most critical and should not exceed 1 h. The cooling rate between 30 and approximately 10 °C was the second most critical period. Cooling from 30 to 10 °C within 2 h ensured minimal growth of psychrotrophic bacteria in the milk. The cooling rate between 10 and 4 °C (the slowest phase of cooling) was of surprisingly little importance. Given a normal cooling profile to 10 °C, several hours of prolonged cooling time made practically no difference in psychrotrophic counts. This behaviour can be explained by the time/temperature dependence of the work needed by the bacteria to complete the lag phase at low temperature. For milk quality advisors, it is important to know that slow cooling below 10 °C does not result in high total counts of bacteria. In practice, slow cooling is occasionally found at farms with robotic milking. However, when comparing psychrotrophic growth in bulk milk tanks designed for robotic milking or conventional milking, the model predicted less growth for robotic milking for identical cooling profiles. It is proposed that due to the different rates of milk entering the tank, fewer bacteria will exit the lag phase during robotic milking and they will be more diluted than in conventional milking systems. At present, there is no international standard that specifies the cooling profile in robotic systems. The information on the insignificant effect of the cooling rate below 10 °C may be useful in the development of a standard.