Reliability of Peanut Oil Authenticity Identification Based on Fatty Acids and Establishment of Adulteration Analysis Model

Abstract

Abstract In order to establish a highly reliable, fast and effective method for identification of adulterated peanut oil, this paper studies authenticity identification based on fatty acids. A comparison of the credibility using three different methods was conducted, namely the method of GB/T 1534 Peanut Oil, Principal Component Analysis (PCA) and Partial Least Squares analysis (PLS). Firstly, 120 samples were prepared by mixing peanut oil with corn oil, soybean oil or palm oil in different proportions. Afterwards, adulteration models were developed respectively using Principal Component Analysis (PCA) and Partial Least Squares analysis (PLS). The results show that according to the quality standard, the adulteration could be identified only when there was more than 50% soybean oil, 45% corn oil or 15% palm oil; the reliability was low. Both PCA and PLS models were more credible than the quality standards; furthermore, PLS model was more effective than PCA model, it could not only identify the adulteration by 100% when palm oil, soybean oil or corn oil was solely mixed, but also distinguish well the type of oil adulterated. The results also indicate that when peanut oil adulterated with palm oil, the content of palmitic acid and myristic acid had highly positive correlation; when that mixed with soybean oil, the content of linoleic acid and linolenic acid were highly positively correlated; when that mixed with corn oil, the content of heptachenoic acid was positively correlated, but negatively correlated with the content of behenic acid, arachidonic acid and arachidonic acid.