LAUSR

Abstract The volatiles of three typical Italian Pecorino cheeses were analysed by headspace solid-phase microextraction (HS-SPME) coupled with gas-chromatography with mass spectrometry detection (GC-MS) evaluating its potentiality to discriminate Protected Designation of Origin (PDO) Pecorino Romano (PR), PDO Pecorino Sardo (PS) and Pecorino di Farindola (PF). A Design of Experiments (DOE) was employed to optimize the extraction conditions in terms of sample temperature and exposure time in the HS-SPME/GC-MS procedure. Linear Discriminant Analysis (LDA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were applied to the volatile composition data to classify samples. Both methods showed high calibration accuracy (100% of non-error rate in cross-validation) and good predictions (87.5% of correct classification, on the external validation set) providing a powerful tool for discriminating Pecorino cheeses, despite their production occurs in different production cycles, in nearby geographical areas and, in the case of PS/PR origins, the raw materials come from common sources.