| Literature DB >> 31522125 |
Matteo Bergamaschi1, Claudio Cipolat-Gotet2, Alessio Cecchinato3, Stefano Schiavon1, Giovanni Bittante1.
Abstract
Milk samples from 1264 cows in 85 farms were authenticated for different farming-systems using a 10-fold cross-validated linear-discriminant-analysis using Fourier-transform infrared spectra (FTIRS) and gas-chromatographic fatty-acid (FA) profiles. FTIRS gave correct classification greater than FAs (97.4% vs. 81.1%) during calibration, but slightly worse in validation (73.5% vs 77.3%) and their combination improved the results. All milk samples were processed into ripened model-cheeses, and analyzed by near-infrared-spectrometry (NIRS), by proton-transfer-reaction time-of-flight mass-spectrometry for their volatile organic compound (VOCs) fingerprint and by panel sensory profiling (SENS). Farming-system authentication on cheese samples was less efficient than on milk, but still possible. The instrumental methods yielded similar validation results, better than SENS, and their combination improved the correct classification rate. The efficiency of the different technics was affected by specific farming systems. In conclusion, dairy products could be discriminated for farming-systems with acceptable accuracy, but the methods tested differ in sampling procedure, rapidity and costs.Entities:
Keywords: Food authentication; Food origin discrimination; Food quality monitoring, volatile organic compound; Silage feeding
Year: 2019 PMID: 31522125 DOI: 10.1016/j.foodchem.2019.125480
Source DB: PubMed Journal: Food Chem ISSN: 0308-8146 Impact factor: 7.514