Characterizing Variances of Adulterated Extra Virgin Olive Oils by UV-Vis Spectroscopy Combined with Analysis of Variance-Projected Difference Resolution (ANOVA-PDR) and Multivariate Classification

Abstract

The analysis of variance-projected difference resolution (ANOVA-PDR) was proposed and compared with multivariate classification for its potential in detecting possible food adulteration in extra virgin olive oils (EVOOs) by UV-Vis spectra. Three factors including origin, adulteration level, and adulteration type were systematically examined by the ANOVA-derived methods. The ANOVA-PDR quantitatively presented the separation of the internal classes according to the three main factors. Specifically, the average ANOVA-derived PDRs of the EVOO origination and adulteration level, respectively, is 4.01 and 1.78, while the conventional PDRs of the three factors are all less than 1.5. Furthermore, the partial least-squares-discriminant analysis (PLS-DA) and the PLS regression (PLSR) modeling with the selected sub-datasets from different origins were used to verify the results. The resulting models suggested that the three main factors and their interactions were all important sources of spectral variations.

Screening Method for the Visual Discrimination of Olive Oil from Other Vegetable Oils by a Multispecies DNA Sensor

“…A commonly followed strategy for the development of analytical methods aims to investigate and exploit changes in the profile of small molecules and metabolites that occur when olive oil is mixed with other vegetable oils. Methods based on NMR, , chromatographic techniques combined with mass spectrometry, , FTIR and Raman spectroscopy, , UV–vis and fluorescence spectroscopy, , and methods based on the differences on the refractive index, differential scanning calorimetry, and hyperspectral imaging combined with chemometrics − were developed for monitoring the changes of metabolites such as fatty acids, triacylglycerols, phospholipids, tocopherols, pigments, flavonoids, triterpenes etc., or other parameters, in olive oil blends. Table S1 (Supporting Information, SI) presents an extensive list of the reported methods, which have been categorized based on the techniques used.…”

Identification of the Beverage Sotol Adulterated with Ethylene Glycol Using UV-Vis Spectroscopy and Artificial Neural Networks

“…However, sometimes, it is difficult to relate the absorbance bands to the concentration of a specific analyte, especially in cases in which the concentration of the analyte is very low or is found within another substance that has similar absorption bands. In this complicated scenario, the use of computational algorithms has proven to be an alternative solution [22,23].…”

Engraved Split-Ring Resonators as Potential Microwave Sensors for Olive Oil Quality Control

“…Currently, there are many processes related to the quality control of olive oil. Apart from conventional physicochemical analyses, these procedures include the use of various spectroscopic methods, such as Fourier transform infrared spectroscopy (FT-IR), ultraviolet–visible spectroscopy (UV–vis), fluorescence spectroscopy, Raman spectroscopy, gas chromatography–mass spectroscopy, to name but a few. With the use of these optical techniques, detailed quality control can be achieved, such as a gentle classification of edible oils, olive oil adulteration, oil contamination, and differentiation among oil types, as well as olive oil grades .…”