The Quality Assessment of Edible Oils and Fats by LF-NMR Coupled with PCA
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Abstract:
Principal component analysis (PCA) was used to analyze the low field nuclear magnetic resonance (LF-NMR) relaxation characteristics (T21, T22, T23, S21, S22, S23) of a variety of different oil samples. The results indicated that application of PCA to the LF-NMR data allowed a good differentiation between edible soybean oil and cottonseed oil; while palm oil and lard could not be obviously distinguished. Different kinds of fried oil samples could be properly differentiated, regardless of the frying degree. As the frying process prolonged, the distribution of the fried oil samples moved to upper right based on the principal component scores. And the fried oil samples could be obviously divided into two groups: palm oil and lard, soybean oil and cottonseed oil. In addition, it was easy to distinguish adulterated lard from edible lard according to their corresponding principal component scores. With adulteration ratio of fried lard increased, higher distinguish ability was found and experimentally verified correctly. Therefore, LF-NMR combined with PCA is feasible to analyze the variety of edible oil, the degree of fried oil, and the quality of adulterated lard.
