This work aims to discriminate milk samples according to their geographical origin, heat treatment, and season of production. This was achieved by combining different techniques, such as isotope ratio mass spectrometry (IRMS), mid- (MIRS) and near-infrared spectroscopies (NIRS), and gas chromatography with flame ionization detector (GC-FID). Milk samples were from North Tyrol (raw milk), South Tyrol (raw milk and high-temperature short time (HTST)), both collected in different seasons. Ultra-high-temperature (UHT) milk samples were from other European regions. These techniques, when used alone, showed limited discrimination capacity. Instead, when such techniques were combined in a multi-variate classification method (PLS-DA), then, milk samples were discriminated according to their geographical origin with an error lower than 5 %. The type of processing and the season were also discriminated. The combination of different techniques compensated their inherent limits and provided a good potential for determining the geographic origin of milk.
Scampicchio, M., Eisenstecken, D., de Benedictis, L., Capici, C., Ballabio, D., Mimmo, T., et al. (2016). Multi-method Approach to Trace the Geographical Origin of Alpine Milk: a Case Study of Tyrol Region. FOOD ANALYTICAL METHODS, 9(5), 1262-1273 [10.1007/s12161-015-0308-2].
Multi-method Approach to Trace the Geographical Origin of Alpine Milk: a Case Study of Tyrol Region
BALLABIO, DAVIDE;
2016
Abstract
This work aims to discriminate milk samples according to their geographical origin, heat treatment, and season of production. This was achieved by combining different techniques, such as isotope ratio mass spectrometry (IRMS), mid- (MIRS) and near-infrared spectroscopies (NIRS), and gas chromatography with flame ionization detector (GC-FID). Milk samples were from North Tyrol (raw milk), South Tyrol (raw milk and high-temperature short time (HTST)), both collected in different seasons. Ultra-high-temperature (UHT) milk samples were from other European regions. These techniques, when used alone, showed limited discrimination capacity. Instead, when such techniques were combined in a multi-variate classification method (PLS-DA), then, milk samples were discriminated according to their geographical origin with an error lower than 5 %. The type of processing and the season were also discriminated. The combination of different techniques compensated their inherent limits and provided a good potential for determining the geographic origin of milk.
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