Establishment and Discriminate of Fatty Acid Fingerprint from Waste Cooking Oil
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Abstract:
GC-MS was applied to analyze the contents of 37 fatty acids in vegetable oils (peanut oil, colza oil, palm oil and edible blend oil), animal oils (butter, mutton fat, duck grease) and catering waste oils respectively to establish a characteristic fingerprint data base for different types of vegetable oils．Meanwhile, discrimination (distance discriminant method) and cluster (Flexible-Beta Method) analysis were conducted to determine fatty acid compositions of the abovementioned oils l. The results showed that normal oils were well classified through the function except for a small amount of adulteration and oils with high saturated fatty acid content. Twenty-three blind samples were investigated and the accuracy was as high as 91.3%. Therefore, the established model could distinguish different kinds of oil correctly based on changes in content or proportion of fatty acids.
