In the present study, a total of 116 tank milk samples were collected from 30 farms located in The Netherlands and analysed by Fourier-transform infrared (FTIR) spectroscopy. Samples were collected in April, May and June 2011 and in February 2012. The samples differed in the time spent by the cows on pasture, presence/absence of fresh grass in the daily ration and the farming system (organic/biodynamic or conventional). Classification models based on partial least square discriminant analysis (PLS-DA) of FTIR spectra were developed for the prediction of fresh grass feeding, pasture grazing and organic farming. The PLS-DA model discriminated between milk from cows that had fresh grass in the daily ration and milk from cows that had not fresh grass with sensitivity and specificity values of 88% and 83% in external validation and all the samples from cows that had no fresh grass collected in spring were correctly classified. The PLS-DA model developed for the authentication of pasture grazing showed comparable accuracy when the whole sample set is considered but was less accurate on the spring samples (75% of samples from cows indoors in spring correctly classified). Discrimination of organic and conventional milk was also accomplished with acceptable accuracy with % correct classification of 80% and 94% respectively in external validation. The results suggest that milk FTIR spectra contain valuable information on cows' diet that can be used for authentication purposes.