Classification of edible and lampante virgin olive oil based on synchronous fluorescence and total luminescence spectroscopy

2005 ◽  
Vol 542 (2) ◽  
pp. 151-156 ◽  
Author(s):  
Konstantina I. Poulli ◽  
George A. Mousdis ◽  
Constantinos A. Georgiou
2011 ◽  
Vol 59 (4) ◽  
pp. 1051-1057 ◽  
Author(s):  
Matthew Ross Kunz ◽  
Joshua Ottaway ◽  
John H. Kalivas ◽  
Constantinos A. Georgiou ◽  
George A. Mousdis

2014 ◽  
Vol 69 (1) ◽  
Author(s):  
Abdul Rohman ◽  
Intan Gupitasari ◽  
Purwanto Purwanto ◽  
Kuwat Triyana ◽  
Arieff Salleh Rosman ◽  
...  

The presence of lard (LD) in cosmetics products is a serious matter for certain religion, like Islam. The Muslim community is not allowed to use cosmetics products containing pig derivatives such as LD. Therefore, analysis of LD in cosmetics products is highly needed. The present study highlighted the employment of Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and principle component analysis (PCA) for quantitative analysis and classification of LD in the binary mixture with extra virgin olive oil (EVOO) as oil base in cream formulations for halal authentication. The lipid component in cream was extracted using liquid-liquid extraction using hexane as extracting solvent, and the lipid obtained was subjected to FTIR spectra measurement, using horizontal attenuated total reflectance as sampling technique. The result showed that FTIR spectroscopy in combination with partial least squares can be used to quantify the levels of LD in the mixture with EVOO in cosmetics creams using the combined frequency regions of 1785-702 cm-1 and 3020-2808 cm-1. PCA using absorbance intensities at 1200 – 1000 cm-1 as variables has been successfully used for the classification of cream with and without LD in the formulation. The developed method is rapid and not involving the excessive sample preparation.


Foods ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 355 ◽  
Author(s):  
Sara Barbieri ◽  
Karolina Brkić Bubola ◽  
Alessandra Bendini ◽  
Milena Bučar-Miklavčič ◽  
Florence Lacoste ◽  
...  

A set of 334 commercial virgin olive oil (VOO) samples were evaluated by six sensory panels during the H2020 OLEUM project. Sensory data were elaborated with two main objectives: (i) to classify and characterize samples in order to use them for possible correlations with physical–chemical data and (ii) to monitor and improve the performance of panels. After revision of the IOC guidelines in 2018, this work represents the first published attempt to verify some of the recommended quality control tools to increase harmonization among panels. Specifically, a new “decision tree” scheme was developed, and some IOC quality control procedures were applied. The adoption of these tools allowed for reliable classification of 289 of 334 VOOs; for the remaining 45, misalignments between panels of first (on the category, 21 cases) or second type (on the main perceived defect, 24 cases) occurred. In these cases, a “formative reassessment” was necessary. At the end, 329 of 334 VOOs (98.5%) were classified, thus confirming the effectiveness of this approach to achieve a better proficiency. The panels showed good performance, but the need to adopt new reference materials that are stable and reproducible to improve the panel’s skills and agreement also emerged.


2015 ◽  
Vol 7 (20) ◽  
pp. 8839-8846 ◽  
Author(s):  
Karla Danielle Tavares de Melo Milanez ◽  
Márcio José Coelho Pontes

This work proposes a new methodology based on digital images and supervised pattern recognition methods for the classification of extra virgin olive oil (EVOO) samples with respect to brand (A, B and C) and verification of adulteration with soybean oil.


2020 ◽  
Vol 159 ◽  
pp. 105544
Author(s):  
Flavia T. Borghi ◽  
Priscilla C. Santos ◽  
Francine D. Santos ◽  
Márcia H.C. Nascimento ◽  
Thayná Corrêa ◽  
...  

1984 ◽  
Vol 67 (4) ◽  
pp. 721-727 ◽  
Author(s):  
Derde Marie-Paule ◽  
Coomans Danny ◽  
Massart Désiré L

Abstract The multivariate technique SIMCA (soft independent modeling of class analogy) has been applied to the classification of foodstuffs on the basis of gas chromatographic profiles of some of their constituents. The data set used in this investigation consists of the percentage distribution of 7 fatty acids (7 variables) in 100 samples of virgin olive oil from 2 different regions (2 classes) of Italy, East and West Liguria. The SIMCA method can be used to compute whether an olive oil sample from Liguria originated in the western or eastern part of this region, while 98.8% of samples that do not originate in Liguria are correctly classified as outliers. The developed classification rules are adequate for identifying oils according to their origin. Standard decision diagrams (SDD) are very attractive tools for classification of new samples; the similarity between a new sample and each of the classes is easily computed. Consequently, the SDD visualizes any similarity toward each of the classes, and enables a decision on whether the new sample originates in one of the regions under study.


2016 ◽  
Vol 93 (6) ◽  
pp. 837-848 ◽  
Author(s):  
Ioanna Kosma ◽  
Maria Vavoura ◽  
Stavros Kontakos ◽  
Ioannis Karabagias ◽  
Michael Kontominas ◽  
...  

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