Alignment and Proficiency of Virgin Olive Oil Sensory Panels: The OLEUM Approach

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.

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A survey on geographic classification of virgin olive oil with using T-operators in Fuzzy Decision Tree Approach

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2016.04.004 ◽

2016 ◽

Vol 155 ◽

pp. 86-96 ◽

Cited By ~ 5

Author(s):

Efendi Nasibov ◽

Suzan Kantarcı Savaş ◽

Alper Vahaplar ◽

Ayşe Övgü Kınay

Keyword(s):

Decision Tree ◽

Olive Oil ◽

Virgin Olive Oil ◽

Fuzzy Decision ◽

Fuzzy Decision Tree ◽

Tree Approach

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Quantification of Lard in the Mixture with Olive Oil in Cream Cosmetics Based on FTIR Spectra and Chemometrics for Halal Authentication

Jurnal Teknologi ◽

10.11113/jt.v69.2062 ◽

2014 ◽

Vol 69 (1) ◽

Cited By ~ 5

Author(s):

Abdul Rohman ◽

Intan Gupitasari ◽

Purwanto Purwanto ◽

Kuwat Triyana ◽

Arieff Salleh Rosman ◽

...

Keyword(s):

Olive Oil ◽

Ftir Spectroscopy ◽

Multivariate Calibration ◽

Virgin Olive Oil ◽

Sampling Technique ◽

Extra Virgin Olive Oil ◽

Ftir Spectra ◽

Halal Authentication ◽

Extracting Solvent

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.

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Classification of extra virgin olive oil and verification of adulteration using digital images and discriminant analysis

Analytical Methods ◽

10.1039/c5ay01765c ◽

2015 ◽

Vol 7 (20) ◽

pp. 8839-8846 ◽

Cited By ~ 13

Author(s):

Karla Danielle Tavares de Melo Milanez ◽

Márcio José Coelho Pontes

Keyword(s):

Pattern Recognition ◽

Discriminant Analysis ◽

Soybean Oil ◽

Olive Oil ◽

Digital Images ◽

Virgin Olive Oil ◽

Extra Virgin Olive Oil ◽

Pattern Recognition Methods

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.

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Physico-chemical and sensory evaluation of virgin olive oils from several Algerian olive-growing regions

OCL ◽

10.1051/ocl/2021044 ◽

2021 ◽

Vol 28 ◽

pp. 55

Author(s):

Malika Douzane ◽

Mohamed-Seghir Daas ◽

Amel Meribai ◽

Ahmed-Hani Guezil ◽

Abdelkrim Abdi ◽

...

Keyword(s):

Olive Oil ◽

Virgin Olive Oil ◽

Principal Component ◽

Great Variability ◽

Olive Cultivar ◽

Virgin Olive Oils ◽

Olive Oils ◽

Physical Chemical ◽

Physico Chemical

Olive cultivar diversity is rich in Algeria but most remain unexplored in terms of quality traits. This work aimed to evaluate the physicochemical and organoleptic quality of twenty olive oil samples belonging to four Algerian cultivars (Chemlal, Sigoise, Ronde de Miliana and Rougette de Mitidja) collected throughout the national territory. Physical-chemical and sensory results showed that 60% of the oils belong to the extra virgin category, while 40% were classified as “virgin olive oil”. The results of the principal component analysis (PCA) revealed a great variability in fatty acids composition between the samples depending on the cultivar and origin. Oleic acid was the most abundant and varied between 64.84 and 80.14%. Extra virgin olive oils with quality attributes are eligible for a label. Rougette de Mitidja, Ronde de Miliana and Sigoise from Oran showed great potential.

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Monitoring Virgin Olive Oil Shelf-Life by Fluorescence Spectroscopy and Sensory Characteristics: A Multidimensional Study Carried Out under Simulated Market Conditions

Foods ◽

10.3390/foods9121846 ◽

2020 ◽

Vol 9 (12) ◽

pp. 1846

Author(s):

Ana Lobo-Prieto ◽

Noelia Tena ◽

Ramón Aparicio-Ruiz ◽

Diego L. García-González ◽

Ewa Sikorska

Keyword(s):

Fluorescence Spectroscopy ◽

Shelf Life ◽

Olive Oil ◽

Fluorescence Spectra ◽

Virgin Olive Oil ◽

Sensory Characteristics ◽

Oxidation Products ◽

Chlorophyll Pigments ◽

Multiple Parameters ◽

Physical Chemical

The control of virgin olive oil (VOO) freshness requires new tools that reflect the diverse chemical changes that take place during the market period. Fluorescence spectroscopy is one of the techniques that has been suggested for controlling virgin olive oil (VOO) freshness during its shelf-life. However, a complete interpretation of fluorescence spectra requires analyzing multiple parameters (chemical, physical–chemical, and sensory) to evaluate the pace of fluorescence spectral changes under moderate conditions with respect to other changes impacting on VOO quality. In this work, four VOOs were analyzed every month with excitation–emission fluorescence spectra. The same samples were characterized with the concentration of fluorophores (phenols, tocopherols, chlorophyll pigments), physical–chemical parameters (peroxide value, K232, K270, free acidity), and sensory attributes (medians of defects and of the fruity attribute). From the six components extracted with parallel factor analysis (PARAFAC), two components were assigned to chlorophyll pigments and those assigned to tocopherols, phenols, and oxidation products were selected for their ability to discriminate between fresh and aged oils. Thus, the component assigned to oxidation products correlated with K270 in the range 0.80–0.93, while the component assigned to tocopherols–phenols correlated with the fruity attribute in the range 0.52–0.90. The sensory analysis of the samples revealed that the changes of these PARAFAC components occurred at the same time as, or even before, the changes of the sensory characteristics.

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