Detection and quantification of extra virgin olive oil adulteration with edible oils by FT-IR spectroscopy and chemometrics

2015 ◽  
Vol 7 (9) ◽  
pp. 3939-3945 ◽  
Author(s):  
Xiaodan Sun ◽  
Weiqi Lin ◽  
Xinhui Li ◽  
Qi Shen ◽  
Hongyuan Luo
Keyword(s):  
Ir Spectroscopy ◽  
Olive Oil ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Ft Ir ◽  
Detection And Quantification ◽  
Ft Ir Spectroscopy

The adulterated oils, including the type of adulterants and levels of adulteration, are identified from extra virgin olive oil using FT-IR spectroscopy coupled with chemometrics.

EXPRESS: Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils

2020 ◽  
pp. 000370282097470
Author(s):  
Joshua M. Ottaway ◽  
J. Chance Carter ◽  
Kristl L Adams ◽  
Joseph Camancho ◽  
Barry Lavine ◽  
...  
Keyword(s):  
Olive Oil ◽  
Peroxide Value ◽  
Near Infrared ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Spectroscopic Techniques ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Calibration Models

The peroxide value (PV) of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine PVs using field portable and process instrumentation; those efforts presented ‘best-case’ scenarios with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique, or combination thereof, is best for predicting PVs. Following PV assays of each oil class using an established titration-based method, global and global-subset calibration models were constructed from spectroscopic data collected on the 19 oil classes used in this study. Spectra from each optical technique were used to create partial least squares regression (PLSR) calibration models to predict the PV of unknown oil samples. A global PV model based on near-infrared (8 mm optical path length – OPL) oil measurements produced the lowest RMSEP (4.9), followed by 24 mm OPL near infrared (5.1), Raman (6.9) and 50 μm OPL mid-infrared (7.3). However, it was determined that the Raman RMSEP resulted from chance correlations. Global PV models based on low-level fusion of the NIR (8 and 24 mm OPL) data and all infrared data produced the same RMSEP of 5.1. Global subset models, based on any of the spectroscopies and olive oil training sets from any class (pure, extra light, extra virgin), all failed to extrapolate to the non-olive oils. However, the near-infrared global subset model built on extra virgin olive oil could extrapolate to test samples from other olive oil classes.

scholarly journals Evaluation of Extra Virgin Olive Oil Adulteration with Edible Oils using ATR-FTIR Spectroscopy

2020 ◽  
Vol 5 (1) ◽  
pp. 35-44
Author(s):  
Nuraznee Mashodi ◽  
Nurul Yani Rahim ◽  
Norhayati Muhammad ◽  
Saliza Asman
Keyword(s):  
Linear Regression ◽  
Olive Oil ◽  
Ftir Spectroscopy ◽  
Corn Oil ◽  
Edible Oils ◽  
Limit Of Detection ◽  
Linear Regression Analysis ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Regression Graph

Extra virgin olive oil (EVOO) is categorized as expensive oil due to high-quality nutritional value. Unfortunately, EVOO is easily adulterated with other low-quality edible oils. Therefore, this study was done to differentiate and analyze the adulteration of EVOO with other edible oils using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The study was used several edible oils included canola oil, corn oil, sunflower oil, and soybean oil as an adulterant for EVOO. The adulterant EVOO samples were prepared by mixing with dissimilar concentrations of the solely edible oils (20 %, 40 %, 60 % and 80 % (v/v)). The main functional groups of EVOO and other edible oils are O-H, C-H, C=C and C=O groups were assigned around 3500 cm-1, 2925 cm-1, 3006 cm-1 and 1745 cm-1 wavenumbers, respectively. From the comparison of EVOO and other adulterant edibles oil spectra, it showed that the EVOO has the lowest absorbance intensity at around 3006 cm-1 represented double bond which is closely related to the composition of oil sample. The adulteration of EVOO was evaluated by analysing the changes in the absorbance based on the linear regression analysis graph of the bands at 3006 and 2925 cm-1 and the limit of detection (LOD) was measured. The graph of A3008/A2925 with good relative coefficients (R2) and lower LOD is more favourable than the linear regression graph of A3006 versus percentage of edible oils added in EVOO. This study showed that ATR-FTIR spectroscopy is a convenient tool for analysing the adulteration of EVOO.

scholarly journals Authenticity and Concentration Analysis of Extra Virgin Olive Oil Using Spontaneous Raman Spectroscopy and Multivariate Data Analysis

2019 ◽  
Vol 9 (12) ◽  
pp. 2433 ◽  
Author(s):  
Shiyamala Duraipandian ◽  
Jan C. Petersen ◽  
Mikael Lassen
Keyword(s):  
Raman Spectroscopy ◽  
Olive Oil ◽  
Rapeseed Oil ◽  
Corn Oil ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Ternary Mixtures ◽  
Calibration Models ◽  
Oil Mixtures

Adulteration of extra virgin olive oil (EVOO) with cheaper edible oils is of considerable concern in the olive oil industry. The potential of Raman spectroscopy combined with multivariate statistics has been investigated for evaluating the authenticity (or purity) and concentration of EVOO irrespective of it being adulterated with one or more adulterants. The adulterated oil samples were prepared by blending different concentrations of EVOO (10–100% v/v) randomly with cheaper edible oils such as corn, soybean and rapeseed oil. As a result, a Raman spectral database of oil samples (n = 214 spectra) was obtained from 11 binary mixtures (EVOO and rapeseed oil), 16 ternary mixtures (EVOO, rapeseed and corn oil) and 44 quaternary mixtures (EVOO, rapeseed, corn and soybean oil). Partial least squares (PLS) calibration models with 10-fold cross validation were constructed for binary, ternary and quaternary oil mixtures to determine the purity of spiked EVOO. The PLS model on the complex dataset (binary + ternary + quaternary) where the spectra obtained with different measurement parameters and sample conditions can able to determine the purity of spiked EVOO inspite of being blended with one or more cheaper oils. As a proof of concept, in this study, we used single batch of commercial oil bottles for estimating the purity of EVOO. The developed method is not only limited to EVOO, but can be applied to clean EVOO obtained from the production site and other types of food.

FT-IR extra virgin olive oil classification based on ethyl ester content

Food Control ◽  
2019 ◽  
Vol 102 ◽  
pp. 149-156 ◽  
Author(s):  
Giacomo Squeo ◽  
Silvia Grassi ◽  
Vito Michele Paradiso ◽  
Cristina Alamprese ◽  
Francesco Caponio
Keyword(s):  
Olive Oil ◽  
Ethyl Ester ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Ester Content ◽  
Ft Ir

scholarly journals Detecting Food Fraud in Extra Virgin Olive Oil Using a Prototype Portable Hyphenated Photonics Sensor

2020 ◽  
Author(s):  
Yannick Weesepoel ◽  
Martin Alewijn ◽  
Michiel Wijtten ◽  
Judith Müller-Maatsch
Keyword(s):  
Data Fusion ◽  
Olive Oil ◽  
Near Infrared ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Food Fraud ◽  
Olive Oils ◽  
Level Data ◽  
High Level

Abstract Background Current developments in portable photonic devices for fast authentication of extra virgin olive oil (EVOO) or EVOO with non-EVOO additions steer towards hyphenation of different optic technologies. The multiple spectra or so-called “fingerprints” of samples are then analyzed with multivariate statistics. For EVOO authentication, one-class classification (OCC) to identify “out-of-class” EVOO samples in combination with data-fusion is applicable. Objective Prospecting the application of a prototype photonic device (“PhasmaFood”) which hyphenates visible, fluorescence, and near-infrared spectroscopy in combination with OCC modelling to classify EVOOs and discriminate them from other edible oils and adulterated EVOOs. Method EVOOs were adulterated by mixing in 10–50% (v/v) of refined and virgin olive oils, olive-pomace olive oils, and other common edible oils. Samples were analyzed by the hyphenated sensor. OCC, data-fusion, and decision thresholds were applied and optimized for two different scenarios. Results: By high-level data-fusion of the classification results from the three spectral databases and several multivariate model vectors, a 100% correct classification of all pure edible oils using OCC in the first scenario was found. Reducing samples being falsely classified as EVOOs in a second scenario, 97% of EVOOs adulterated with non-EVOO olive oils were correctly identified and ones with other edible oils correctly classified at score of 91%. Conclusions Photonic sensor hyphenation in combination with high-level data fusion, OCC, and tuned decision thresholds delivers significantly better screening results for EVOO compared to individual sensor results. Highlights Hyphenated photonics and its data handling solutions applied to extra virgin olive oil authenticity testing was found to be promising.

Application of transmission FT-IR spectroscopy for the trans fat determination in the industrially processed edible oils

2009 ◽  
Vol 114 (1) ◽  
pp. 323-327 ◽  
Author(s):  
S.T.H. Sherazi ◽  
Aftab Kandhro ◽  
S.A. Mahesar ◽  
M.I. Bhanger ◽  
M. Younis Talpur ◽  
...  
Keyword(s):  
Ir Spectroscopy ◽  
Edible Oils ◽  
Trans Fat ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

Self-organizing maps based on chaotic parameters to detect adulterations of extra virgin olive oil with inferior edible oils

2013 ◽  
Vol 118 (4) ◽  
pp. 400-405 ◽  
Author(s):  
José S. Torrecilla ◽  
John C. Cancilla ◽  
Gemma Matute ◽  
Pablo Díaz-Rodríguez ◽  
Ana I. Flores
Keyword(s):  
Olive Oil ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Self Organizing Maps ◽  
Self Organizing

FT-NIR the method of choice to verify the authenticity of extra virgin olive oils

NIR news ◽  
2017 ◽  
Vol 28 (4) ◽  
pp. 6-9 ◽  
Author(s):  
John KG Kramer ◽  
Hormoz Azizian
Keyword(s):  
Fourier Transform ◽  
Olive Oil ◽  
Near Infrared ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Volatile Fraction ◽  
Olive Oils ◽  
Calibration Models ◽  
A Minor

Fourier transform near infrared spectroscopy was recently demonstrated to be an excellent method to evaluate the authenticity and adulteration of extra virgin olive oil. Since this method is matrix dependent, it takes a chemical fingerprint of all the components which sets it apart from the targeted methods. Careful examinations of the Fourier transform near infrared spectra lead to the identification of a minor carbonyl overtone absorption at 5269 cm−1 associated with the volatile fraction in extra virgin olive oil that appears to be a reliable indicator of authenticity. The same spectra were used to identify the fatty acids present in the oil using models based on comparison to accurate GC data. Gravimetric mixtures of extra virgin olive oil with refined edible oils were then prepared to develop PLS1 calibration models to identify possible adulterants and by how much. The great varietal difference in olive oils made it necessary to develop four unique sets of PLS1 calibration models for each extra virgin olive oil variety. As a result, an extra virgin olive oil acceptance specification was established.

Hue Parameter Fluorescence Identification of Edible Oils with a Smartphone

2018 ◽  
Author(s):  
Aron Hakonen ◽  
Jonathon E. Beves
Keyword(s):  
Olive Oil ◽  
Edible Oils ◽  
Low Cost ◽  
Virgin Olive Oil ◽  
Field Testing ◽  
Extra Virgin Olive Oil ◽  
High Price ◽  
Food Fraud ◽  
Simple Method ◽  
Fluorescent Compounds

Food-fraud can be highly lucrative and high accuracy authentication of various foodstuffs is becoming essential. Olive oil is one of the most investigated food matrices, due to its high price and low production globally, with recent food-fraud examples showing little or no high quality olive oil in the tested oils. Here a simple method using a 405 nm-LED flashlight and a smartphone is developed for edible oil authentication. Identification is fingerprinted by intrinsic fluorescent compounds in the oils, such as chlorophylls and poly-phenols. This study uses the hue parameter of HSV-colorspace to authenticate 24 different edible oils of nine different types and 15 different brands. For extra virgin olive oil all the nine samples are well separated from the other oil samples. The rest of the samples were also well type-distinguished by the hue parameter, which is complemented by hue-histogram analysis. This opens up opportunities for low-cost and high-throughput smartphone field-testing of edible oils on all levels of the production and supply chain.

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