Oil and fat classification by FT-Raman spectroscopy

One hundred and thirty-eight edible oil and fat samples from 21 different sources, either vegetable (Brazil nut, coconut, corn, high oleic sunflower, alive oil, peanut, palm, palm kernel, rapeseed, soybean, sunflower, etc.) or animal (butter, hydrogenated fish, and tallow) have been analyzed. The spectral features of the most noteworthy bands are studied, and their correlations with the amount of fatty acids quantified by gas chromatography are presented. Principal component analysis is applied to classify the set of samples by their level of unsaturation [saturated (SFA), monounsaturated (MUFA), and polyunsaturated fatty acids (PUFA)]. The most remarkable MUFA and PUFA oil sources are independently classified by applying stepwise linear discriminant analysis to the Raman shifts selected by their correlation with fatty acids or structural assignments. The results show that FT-Raman spectra not only have information of the degree of unsaturation but also of the balance among the amounts of SFA, MUFA, and PUFA. The scattering intensities near different Raman shies (3013, 1663, and 1264 cm(-1)) show high correlations with the fatty acid profile determined by gas chromatography

Oil and fat classification by selected bands of near-infrared spectroscopy

One hundred and four edible oil and fat samples from 18 different sources, either vegetable (Brazil nut, coconut, corn, sunflower, walnut, virgin olive, peanut, palm, canola, soybean, sunflower) or animal (tallow and hydrogenated fish), have been analyzed by highperformance gas chromatography (HPGC) and near-infrared spectroscopy (NIRS). Fatty acids were quantified by HPGC. The near-infrared spectral features of the most noteworthy bands were studied and discussed to design a filter-type NIR instrument. An arborescent structure, based on stepwise linear discriminant analysis (SLDA), was built to classify the samples according to their sources. Seven discriminant functions permitted a successive discrimination of saturated fats, corn, soybean, sunflower, canola, peanut, high oleic sunflower, and virgin olive oils. The discriminant functions were based on the absorbance values, between three and five, from the 1700-1800 and 2100-2400 nm regions. Chemical explanations are given in support of the selected wavelengths. The arborescent structure was then checked with a test set, and 90% of the samples were correctly classified