This study investigated the possibility of using near-infrared spectroscopy (NIRS) for the authentication of Asiago d'allevo, a protected designation of origin cheese from northern Italy. Latent variable models applied on spectral data were developed and used to estimate several chemical properties and to classify the available dataset according to the location and management of the cheesemaking factory (lowland and alpine), the ripening age (6, 12, 18 and 36 months), the altitude of milk production (low, medium, medium-high and high), and the period of the year of the cheese production (May, July and September). The variable importance in projection index was used to identify the most informative spectral regions for discrimination. Results showed that NIR spectra can be used both to accurately estimate several chemical properties and to classify the samples according to the different experimental conditions under investigation with the same discrimination capacity provided by traditional chemical analysis. (c) 2012 Elsevier Ltd. All rights reserved.