Rapid detection of peanut oil adulteration using low-field nuclear magnetic resonance and chemometrics.
(1)H low-field nuclear magnetic resonance (LF-NMR) and chemometrics were employed to screen the quality changes of peanut oil (PEO) adulterated with soybean oil (SO), rapeseed oil (RO), or palm oil (PAO) in ratios ranging from 0% to 100%. Significant differences in the LF-NMR parameters, single component relaxation time (T2W), and peak area proportion (S21 and S22), were detected between pure and adulterated peanut oil samples. As the ratio of adulteration increased, the T2W, S21, and S22 changed linearly; however, the multicomponent relaxation times (T21 and T22) changed slightly. The established principal component analysis or discriminant analysis models can correctly differentiate authentic PEO from fake and adulterated samples with at least 10% of SO, RO, or PAO. The binary blends of oils can be clearly classified by discriminant analysis when the adulteration ratio is above 30%, illustrating possible applications in screening the oil species in peanut oil blends.
Institute of Food Safety and Quality, University of Shanghai for Science and Technology, Shanghai 200093, China.
Wenran
W
Zhu
Institute of Food Safety and Quality, University of Shanghai for Science and Technology, Shanghai 200093, China. Electronic address: 18918629281@126.com.
Xin
X
Wang
Institute of Food Safety and Quality, University of Shanghai for Science and Technology, Shanghai 200093, China.
Lihua
L
Chen
D016002:Discriminant Analysis; D005506:Food Contamination / Q000032:analysis*; D008279:Magnetic Resonance Imaging / Q000379:methods; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D000073878:Palm Oil; D000074241:Peanut Oil; D010938:Plant Oils / Q000032:analysis*; D025341:Principal Component Analysis / Q000379:methods; D013024:Soybean Oil / Q000032:analysis; D013997:Time Factors
D000074241:Peanut Oil; D010938:Plant Oils; D000073878:Palm Oil; D013024:Soybean Oil
Discriminant analysis; LF-NMR parameters; Peanut oil adulteration; Principal component analysis