Verifying origin claims on dairy products using stable isotope ratio analysis and random forest classification

Autor: Roisin O' Sullivan, Raquel Cama-Moncunill, Michael Salter-Townshend, Olaf Schmidt, Frank J. Monahan
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Food Chemistry: X, Vol 19, Iss , Pp 100858- (2023)
Druh dokumentu: article
ISSN: 2590-1575
DOI: 10.1016/j.fochx.2023.100858
Popis: Scientifically underpinning geographic origin claims will improve consumer trust in food labels. Stable isotope ratio analysis (SIRA) is an analytical technique that supports origin verification of food products based on naturally occurring differences in isotopic compositions. SIRA of five relevant elements (C, H, N, O, S) was conducted on casein isolated from butter (n = 60), cheese (n = 96), and whole milk powder (WMP) (n = 41). Samples were divided into four geographic regions based on their commercial origin: Ireland (n = 79), Europe (n = 67), Australasia (n = 29) and USA (n = 22). A random forest machine learning model built using δ13C, δ2H, δ15N, δ18O and δ34S values of all products (n = 197) accurately (88% model accuracy rate) predicted the region of origin with class accuracy of 95% for Irish, 84% for European, 71% for Australasia, and 94% for US products.
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