NMR Spectroscopy For Component Analysis And Quality Identification Of Edible Oils

NMR spectroscopy in combination with multivariate statistical analysis provides the promising feasibility for origin characterization and quality control of food.In this study,this technique was successfully employed to analyze various edible oils from seven plant-origins including sunflower seed,rapeseed,sesame,soybean,peanut,corn and olive oils.The fatty acids in edible oils including oleic acid,linoleic acid,linolenic acid,saturated fatty acid and the corresponding iodine values were quantified by NMR techniques,and principal component analysis was used to distinguish their plant origins.The compositional differences were derived from the pair-wise orthogonal partialleast squares discriminant analysis models between other edible oils and olive oil with highest nutritional value and favorable flavor.The results indicated that olive oil and rapeseed oil seem to be good choices as cooking oils in the daily food preparation,and sesame oil and olive oil could induce health benefits by reducing the risk of heart disease and antineoplastic effects due to their rich polyphenol contents.The further analysis of different-producing-region sesame oils indicated that the altitude gives the great contribution to the compositional differences of sesame oils,and the climatic conditions also cause the compositional variations.On the basis of research results from eligible edible oils,we carried out an in-depth research on the substandard edible oils including waste cooking oils(hogwash oils)and fried old oils.The results show that waste cooking oils and fried old oils demonstrate some unqualified parameters in water content,aldehydes compounds,some phenolic compounds,acid value and iodine value(IV)compared with the eligible ones.In order to functionalize the classification and authentication of edible oils,an expert system was developed based on NMR database of purebred edible oils,mixed cooking oils,waste cooking oils and fried oils conjugation with the multivariate analysis.The results show that it is possible to automatically identify the nature of edible oils and quantify the main components of edible oils.