Common components and specific weights analysis for the discrimination and evaluation of vegetable oil quality

Abstract

Summary The aim of this study was to assess the quality of different vegetable oils by applying common components and specific weights analysis as a tool for the evaluation and discrimination of chromatography, spectral and physicochemical data. This multiblock method of data analysis divided the data into three common components, corresponding to 56.44%, 34.74% and 8.77% of variance, and it was influenced mostly by chromatography, physicochemical and spectral data, respectively. Gas chromatography, which was used for discrimination of the botanical origin of oil and the groups of saturated, monounsaturated and polyunsaturated fatty acids, was situated in the first common dimension; physicochemical analysis, which was applied to evaluate quality parameters such as acid and saponification value and determine the stability of the product, was situated in the second common dimension. FTIR analysis, by exerting a minor influence on the common dimensions, was considered dispensable in evaluating the quality of vegetable oils by common components and specific weights analysis. Therefore, multiblock analysis could efficiently discriminate vegetable oils.

Multi‐block analysis for the correlation of physico‐chemical and rheological data of 42 fruit pulps

“…Common dimensions (ComDim) was first developed by Qannari, Wakeling, Courcoux, and Macfie (2000), for data treatment of sensorial tests. However, this method has been used to correlate analytical techniques for quality evaluation and classification of samples in food science and technology (Ferreira et al, 2017;Rampazzo et al, 2018).…”