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

被引:2
|
作者
Sullivan, Roisin O. ' [1 ]
Cama-Moncunill, Raquel [1 ]
Salter-Townshend, Michael [2 ]
Schmidt, Olaf [1 ]
Monahan, Frank J. [1 ]
机构
[1] Univ Coll Dublin, UCD Sch Agr & Food Sci, Dublin D04 V1W8, Ireland
[2] Univ Coll Dublin, UCD Sch Math & Stat, Dublin D04 V1W8, Ireland
关键词
Authenticity; IRMS; Geographic; Milk; Butter; Cheese; MILK; OXYGEN; NITROGEN; AUTHENTICITY; ABUNDANCES; HYDROGEN; CARBON;
D O I
10.1016/j.fochx.2023.100858
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
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 delta 13C, delta 2H, delta 15N, delta 18O and delta 34S 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.
引用
收藏
页数:7
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