Quality control of raw cows’ milk by headspace analysis

This study investigated whether headspace analysis of volatile components can be used for monitoring the quality of raw cows’ milk. The detection of different quality defects caused by cows’ feed, microbiological and chemical contamination, as well as enzymatic deterioration was studied. Fresh raw milk without quality defects was shown to always contain the same seven volatile components. It was also shown that treatments like heating and homogenization of raw milk may drastically change this basic pattern resulting in as much as a 10-fold increase in the number of volatile compounds. The growth of Pseudomonas could not be detected in an early stage using headspace analysis. Feed was shown to have an effect on the volatile composition if specific vegetable byproducts were fed to the cow. Chloroform contamination was quantified using the method. Also, the extent of lipolysis could be quantified by measuring the free fatty acids. For quantification of both chloroform and lipolysis, the sensitivity and reproducibility of the method were sufficient for quality control purposes. The method was thus able to detect several quality defects with a single analysis and may therefore be a useful supplementary method for raw milk quality control.