Identification Of Vegetable Oils And Fats By Fatty Acid Analysis And Chemometric Techniques

In this work, the composition and content of fatty acid in the vegetable oils and fats were analyzed and investigated. Qualitative and quantitative analysis of fatty acid in nine kinds of vegetable oils, sixteen kinds of binary mixts, seven kinds of vegetable oils in the position of Sn-2, and soybean oils and peanut oils after freezing and fractionation were achieved respectively by gas chromatography. Different kinds of pretreatment methods for discrimination of different vegetable oils and fats were employed, coupling with the methods of Cluster Analysis- Principal Components Analysis (CLU-PCA) and Soft Independent Modeling of Class Analogy(SIMCA) with a variable of various fatty acid contents.The composition and content of fatty acid in the vegetable oils, including soybean oils, peanut oils, rice bran oils, cottonseed oils, sesame oils, palm oils, sunflower oils, corn oils and rapeseed oils were analyzed by gas chromatography. the CLU-PCA method was conducted by considering the relative content of nine kinds of fatty acid in these vegetable oils as a variable. The result of the cluster analysis showed that nine kinds of vegetable oils were entirely accurate cluster, and all of cottonseed oils, sesame oils and corn oils could be completely recognized at the possibility of 100 %; combined with SIMCA method of analysis nine kinds of vegetable oil, and showed that eight kinds of oils were identified absolutely ,and the recognition accuracy(RA) of the palm oil was 92 %. Comparison of the two methods for cluster recognition analysis of these vegetable oils, it was proved that the SIMCA method is better than the CLU-PCA method.The methods of CLU and SIMCA were applied to recognition analysis of binary and ternary mixts. From the result of CLU-PCA, it was seen that the data points of fatty acid information were distributed between the pure oils and had some overlapped with pure oils at the edge of the small and large blend proportion in the binary blend oils, except for the ternary mixts, which were differentiated from pure oils. Meanwhile, the result of the SIMCA method was indicated that sixteen kinds of binary mixts and two kinds of binary mixts could be 100 % completely recognized, and the minimum ratio recognited is 1 % based on the data of experimental.The analysis of Sn-2 position fatty acid of triglyceride in seven kinds of vegetable oils was developed by CLU-PCA. From the result, it was obviously showed that seven kinds of vegetable oils were clustered exactly, and the RA of six kinds of vegetable oils was obtained 100 %,except for the RA of cottonseed oil with 75 %. But when the SIMCA method was applied to the same vegetable oils with same factors mentioned above, the cluster precision and the recognition accuracy were of 100 %, and the clustering result was better than that of CLU-PCA .The peanut oil and soybean oil was partly crystallized with the assistant of freezing method. After crystallization, it was found that recognition rate was very low by the method of CLU-PCA, but 100 % recognition accuracy for SIMCA technology. Therefore, not only it was feasible for SIMCA technology to recognize the peanut oils and the soybean oils Whether or not crystallized, but also received perfect result which was relative to the method of CLU-PCA.