The composition of the volatile fraction of milk from cows was investigated in a survey of milk samples using a headspace sampling technique and gas chromatography coupled to mass spectrometry analysis (GC-MS). Milk samples were collected from 12 farms, selected for similar management, breed and level of production. Farms were also grouped according to the type of forage in the ration: (1) hay; (2) hay and maize silage; (3) hay, maize silage and grass silages. Forty-one compounds in milk were isolated and identified from GC-MS headspace analysis. Quantitatively, the most representative chemical class was ketones (eight compounds, 170 μg/kg), followed by aldehydes (nine compounds, 63 μg/kg), alcohols (eight compounds, 36 μg/kg), and lower amounts of hydrocarbons (six compounds), sulphur compounds (three compounds), esters (four compounds) and terpenes (three compounds). The novel headspace sampling technique, and the consequent reduction of sample pre-treatment, allowed the identification of low-molecular weight volatile compounds, and reduced the risk of producing artefacts during analysis.

Discriminant analysis was used to identify a classification criterion for milk samples, using type of forage in the ration as a grouping variable. Posterior probability error rate indicated that aldehydes provided one of the best discriminant criteria for grouping milks according to ration composition. When all 41 identified volatile compounds were included, discriminant analysis selected nine compounds (acetone, 2,3-butanedione, 2-butanone, ethanol, acetaldehyde, ethylacetate, ethylisovalerate, dimethylsulphone) that did not fail the tolerance test and which correctly classified 100% of the original cases.