Percorrer por autor "Ferro, Miguel Duarte"
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- Chromatographic analysis and comparison of chemical composition of the samples between olive oils in Europe and some chinese oilsPublication . Ferro, Miguel Duarte; Cavaco, Isabel Maria Palma Antunes; Liang, YizengOlive oil is a well known vegetable oil due to its beneficial effects on human’s health and its strong economic importance in the Mediterranean area, being this region alone responsible for more than 90% of the olive oil’s world production. In other regions such as the Chinese one, olive oil is not that commonly used, and other vegetable oils such as tea seed oil, rapeseed oil, sesame oil, corn oil, sunflower oil and peanut oil are rather used to prepare the daily meals. The unique characteristics of each type of vegetable oil is directly related to their fatty acid distribution, being this way the study of the fatty acid composition a good way to characterize them. So, GC-MS fingerprinting technique was applied for the characterization of the different oils, being able to identify a total of 22 fatty acids among the seven tested oils in the CSU’s laboratory. Then, chemometrics were applied for data analysis, which included Principal Component Analysis (PCA) and Partial Least Squares – Linear Discriminant Analysis (PLS-LDA), in order to see if (1) it was possible to group the olive oils according to their region of production in the Iberian Peninsula, and (2) this fingerprinting method could be validated for the analyses of vegetable oils through its both inter- and intra-laboratorial comparison. With PLS-LDA we were able to group the olive oil samples according to their region of production, and also a clear distinction could be made between olive oil and tea seed oil by means of a PCA model. In terms of repeatability and intermediate precision, good results were also obtained from the analyses performed both in CSU and HAPPI. The same analyses were then performed resorting to a group of 12 fatty acids, and similar results could be observed as when using all the fatty acids, meaning that these 12 fatty acids posses sufficient information to characterize the different types of oil. The use of Palmitic acid as a reference peak instead an internal standard was also tested, proving to be a good way to perform these analyses.
- Detection and Identification of extra virgin olive oil adulteration by GC-MS combined with chemometricsPublication . Yang, Yang; Ferro, Miguel Duarte; Cavaco, Isabel Maria Palma Antunes; Liang, YizengIn this study, an analytical method for the detection and identification of extra virgin olive oil adulteration with four types of oils (corn, peanut, rapeseed, and sunflower oils) was proposed. The variables under evaluation included 22 fatty acids and 6 other significant parameters (the ratio of linoleic/linolenic acid, oleic/linoleic acid, total saturated fatty acids (SFAs), polyunsaturated fatty acids (PUFAs), monounsaturated fatty acids (MUFAs), MUFAs/PUFAs). Univariate analyses followed by multivariate analyses were applied to the adulteration investigation. As a result, the univariate analyses demonstrated that higher contents of eicosanoic acid, docosanoic acid, tetracosanoic acid, and SFAs were the peculiarities of peanut adulteration and higher levels of linolenic acid, 11-eicosenoic acid, erucic acid, and nervonic acid the characteristics of rapeseed adulteration. Then, PLSLDA made the detection of adulteration effective with a 1% detection limit and 90% prediction ability; a Monte Carlo tree identified the type of adulteration with 85% prediction ability.