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Rapid Detection Methods for Food Fraud and Food Contaminants Series II

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A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Analytical Methods".

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 19684

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Special Issue Editor

Dr. Giorgia Purcaro

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Guest Editor

Gembloux Agri-Bio Tech, University of Liege, Liege, Belgium
Interests: analytical chemistry; chromatography; multidimensional and comprehensive chromatography; mass spectrometry; sample preparation; metabolomics; lipid analysis; food quality and authenticity; food contaminants
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This is the second in a series of Special Issues devoted to detection methods for food frauds and contaminants, for which I serve as Guest Editor. This is an evergreen topic that deserve continuous effort to keep pace with the detection of emerging contaminants, to improve the available methods, and to develop novel rapid and advanced techniques for an accurate and sensititve determination of frauds and contaminants. This field of application benefits from the application of advanced, highly sensitive, and informative techniques, such as comprehensive chroimatography and powerful mass spectrometer analyzers, but at the same time the fundamental step of sample preparation cannot be overlooked and deserves a special emphasis in maximizing results, both with advanced analytical techniques and also with more traditional instrumentation.

The target of this Special Issue is to present recent developments in the field of food frauds and contaminants detection. Papers dealing with the optimization of sample preparation, analytical approaches, and data handling will be welcomed.

Prof. Giorgia Purcaro
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Food frauds
Food contaminants
Sample preparation
Analytical methods
Rapid methods
Fingerprinting
Profiling
Chemometrics

Published Papers (7 papers)

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Research

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15 pages, 1560 KiB

Open AccessArticle

Monitoring and Occurrence of Heavy PAHs in Pomace Oil Supply Chain Using a Double-Step Solid-Phase Purification and HPLC-FLD Determination

by Laura Barp, Sabrina Moret and Giorgia Purcaro

Foods 2022, 11(18), 2737; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11182737 - 06 Sep 2022

Cited by 6 | Viewed by 1590

Abstract

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental and processing contaminants generated by both spontaneous and anthropogenic incomplete combustion processes of organic matter. Contamination of PAHs in vegetable oils can result from several factors and processes, including environmental contamination, oil processing, and migration from food contact materials. The determination of PAHs in edible oil presents a challenge because of the complexity of the matrix. Since PAHs are present at lower levels than triglycerides, it is necessary to isolate the compounds of interest from the rest of the matrix. To this purpose, a new purification approach based on a double solid-phase extraction (SPE) step followed by high performance liquid chromatography–fluorometric detector (HPLC-FLD) analysis was developed. The method involves a first purification step by using a 5 g silica SPE cartridge, previously washed with dichloromethane (20 mL), dried completely, and then conditioned with n-hexane (20 mL). The triglycerides are retained by the silica, while the PAH-containing fraction is eluted with a mixture of n-hexane/dichloromethane (70/30, v/v). After evaporation, the residue is loaded on a 5 g amino SPE cartridge and eluted with n-hexane/toluene (70/30, v/v) before HPLC-FLD analysis. The focus was the evaluation of the contribution of the various phases of the pomace oil supply chain in terms of the heavy PAHs (PAH8) concentration. Data collected showed that pomace contamination increased (by 15 times) as storage time increased. In addition, the process of pomace drying, which is necessary to reduce its moisture content before solvent extraction of the residual oil, appeared to significantly contribute to the total heavy PAHs content, with increases in value by up to 75 times. Full article

(This article belongs to the Special Issue Rapid Detection Methods for Food Fraud and Food Contaminants Series II)

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15 pages, 4883 KiB

Open AccessArticle

High-Throughput Flow Injection Analysis–Mass Spectrometry (FIA-MS) Fingerprinting for the Authentication of Tea Application to the Detection of Teas Adulterated with Chicory

by Mònica Vilà, Àlex Bedmar, Javier Saurina, Oscar Núñez and Sònia Sentellas

Foods 2022, 11(14), 2153; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11142153 - 20 Jul 2022

Cited by 4 | Viewed by 2370

Abstract

Tea is a broadly consumed beverage worldwide that is susceptible to fraudulent practices, including its adulteration with other plants such as chicory extracts. In the present work, a non-targeted high-throughput flow injection analysis-mass spectrometry (FIA-MS) fingerprinting methodology was employed to characterize and classify different varieties of tea (black, green, red, oolong, and white) and chicory extracts by principal component analysis (PCA) and partial least squares–discriminant analysis (PLS-DA). Detection and quantitation of frauds in black and green tea extracts adulterated with chicory were also evaluated as proofs of concept using partial least squares (PLS) regression. Overall, PLS-DA showed that FIA-MS fingerprints in both negative and positive ionization modes were excellent sample chemical descriptors to discriminate tea samples from chicory independently of the tea product variety as well as to classify and discriminate among some of the analyzed tea groups. The classification rate was 100% in all the paired cases—i.e., each tea product variety versus chicory—by PLS-DA calibration and prediction models showing their capability to assess tea authentication. The results obtained for chicory adulteration detection and quantitation using PLS were satisfactory in the two adulteration cases evaluated (green and black teas adulterated with chicory), with calibration, cross-validation, and prediction errors below 5.8%, 8.5%, and 16.4%, respectively. Thus, the non-targeted FIA-MS fingerprinting methodology demonstrated to be a high-throughput, cost-effective, simple, and reliable approach to assess tea authentication issues. Full article

(This article belongs to the Special Issue Rapid Detection Methods for Food Fraud and Food Contaminants Series II)

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13 pages, 1973 KiB

Open AccessArticle

Handheld Spectral Sensing Devices Should Not Mislead Consumers as Far as Non-Authentic Food Is Concerned: A Case Study with Adulteration of Milk Powder

by Thierry Delatour, Florian Becker, Julius Krause, Roman Romero, Robin Gruna, Thomas Längle and Alexandre Panchaud

Foods 2022, 11(1), 75; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11010075 - 29 Dec 2021

Cited by 1 | Viewed by 1659

Abstract

With the rising trend of consumers being offered by start-up companies portable devices and applications for checking quality of purchased products, it appears of paramount importance to assess the reliability of miniaturized sensors embedded in such devices. Here, eight sensors were assessed for food fraud applications in skimmed milk powder. The performance was evaluated with dry- and wet-blended powders mimicking adulterated materials by addition of either ammonium sulfate, semicarbazide, or cornstarch in the range 0.5–10% of profit. The quality of the spectra was assessed for an adequate identification of the outliers prior to a deep assessment of performance for both non-targeted (soft independent modelling of class analogy, SIMCA) and targeted analyses (partial least square regression with orthogonal signal correction, OPLS). Here, we show that the sensors have generally difficulties in detecting adulterants at ca. 5% supplementation, and often fail in achieving adequate specificity and detection capability. This is a concern as they may mislead future users, particularly consumers, if they are intended to be developed for handheld devices available publicly in smartphone-based applications. Full article

(This article belongs to the Special Issue Rapid Detection Methods for Food Fraud and Food Contaminants Series II)

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9 pages, 685 KiB

Open AccessArticle

Occurrence of Mineral Oil Hydrocarbons in Omega-3 Fatty Acid Dietary Supplements

by Alessia Arena, Mariosimone Zoccali, Alessandra Trozzi, Peter Q. Tranchida and Luigi Mondello

Foods 2021, 10(10), 2424; https://0-doi-org.brum.beds.ac.uk/10.3390/foods10102424 - 13 Oct 2021

Cited by 3 | Viewed by 1991

Abstract

Omega-3 fatty acid dietary supplements have become increasingly popular with consumers due to their multiple health benefits. In this study, the presence of mineral oil hydrocarbons (MOH) was investigated in seventeen commercial samples of such supplements, characterized by different formulations. The analyses were performed using on-line liquid chromatography–gas chromatography (with flame ionization detection), which is considered the most efficient method for the determination of MOH in foodstuffs. Analyte transfer was performed by using the retention gap technique, with partially concurrent solvent evaporation. Various degrees of mineral oil saturated hydrocarbon contamination (from 2.4 ppm to 375.7 ppm) were found, with an average value of 49.9 ppm. Different C-number range contaminations were determined, with the >C₂₅–≤C₃₅ range always found with an average value of 26.9 ppm. All samples resulted free of mineral oil aromatic hydrocarbons, except for two samples in which a contamination was found at the 9.9 and 6.6 ppm levels, respectively. Full article

(This article belongs to the Special Issue Rapid Detection Methods for Food Fraud and Food Contaminants Series II)

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16 pages, 2141 KiB

Open AccessArticle

HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents

by Natasa P. Kalogiouri and Victoria F. Samanidou

Foods 2021, 10(9), 2145; https://0-doi-org.brum.beds.ac.uk/10.3390/foods10092145 - 10 Sep 2021

Cited by 8 | Viewed by 2476

Abstract

A high-pressure liquid chromatographic method coupled to diode array detector (HPLC-DAD) was developed for the determination of phenolic compounds that could be used as markers in authentication studies of walnuts belonging to the Chandler variety, originating from Bulgaria, Greece, and France. An ultrasound-assisted extraction (UAE) protocol applied in the extraction of phenolic compounds was optimized. The method was validated and the relative standard deviations (RSD%) of the within-day, and between-day assays was lower than 6.3 and 11.1, respectively, showing adequate precision, and good accuracy ranging from 86.4 (sinapic acid) to 98.4% (caffeic acid) for within-day assay, and from 90.1 (gallocatechin gallate) to 100.6% (gallic acid) for between-day assay. Eighteen phenolic compounds were determined belonging to the classes of phenolic acids and flavonoids. The quantification results were further processed with chemometrics, and a robust partial least square–discriminant analysis (PLS-DA) model was developed for the classification of the samples according to their geographical origin, proposing markers that could be used for the control of walnuts authenticity and the detection of fraudulent incidents. Full article

(This article belongs to the Special Issue Rapid Detection Methods for Food Fraud and Food Contaminants Series II)

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Review

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18 pages, 348 KiB

Open AccessReview

A Review on Recent Sensing Methods for Determining Formaldehyde in Agri-Food Chain: A Comparison with the Conventional Analytical Approaches

by Luigi Fappiano, Fabiana Carriera, Alessia Iannone, Ivan Notardonato and Pasquale Avino

Foods 2022, 11(9), 1351; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11091351 - 06 May 2022

Cited by 9 | Viewed by 3037

Abstract

Formaldehyde, the simplest molecule of the aldehyde group, is a gaseous compound at room temperature and pressure, is colorless, and has a strong, pungent odor. It is soluble in water, ethanol, and diethyl ether and is used in solution or polymerized form. Its maximum daily dosage established by the EPA is 0.2 μg g⁻¹ of body weight whereas that established by the WHO is between 1.5 and 14 mg g⁻¹: it is in category 1A of carcinogens by IARC. From an analytical point of view, formaldehyde is traditionally analyzed by HPLC with UV-Vis detection. Nowadays, the need to analyze this compound quickly and in situ is increasing. This work proposes a critical review of methods for analyzing formaldehyde in food using sensing methods. A search carried out on the Scopus database documented more than 50 papers published in the last 5 years. The increase in interest in the recognition of the presence of formaldehyde in food has occurred in recent years, above all due to an awareness of the damage it can cause to human health. This paper focuses on some new sensors by analyzing their performance and comparing them with various no-sensing methods but focusing on the determination of formaldehyde in food products. The sensors reported are of various types, but they all share a good LOD, good accuracy, and a reduced analysis time. Some of them are also biodegradable and others have a very low cost, many are portable and easy to use, therefore usable for the recognition of food adulterations on site. Full article

(This article belongs to the Special Issue Rapid Detection Methods for Food Fraud and Food Contaminants Series II)

24 pages, 10339 KiB

Open AccessReview

Non-Destructive Spectroscopic and Imaging Techniques for the Detection of Processed Meat Fraud

by Kiah Edwards, Marena Manley, Louwrens C. Hoffman and Paul J. Williams

Foods 2021, 10(2), 448; https://0-doi-org.brum.beds.ac.uk/10.3390/foods10020448 - 18 Feb 2021

Cited by 15 | Viewed by 4634

Abstract

In recent years, meat authenticity awareness has increased and, in the fight to combat meat fraud, various analytical methods have been proposed and subsequently evaluated. Although these methods have shown the potential to detect low levels of adulteration with high reliability, they are destructive, time-consuming, labour-intensive, and expensive. Therefore, rendering them inappropriate for rapid analysis and early detection, particularly under the fast-paced production and processing environment of the meat industry. However, modern analytical methods could improve this process as the food industry moves towards methods that are non-destructive, non-invasive, simple, and on-line. This review investigates the feasibility of different non-destructive techniques used for processed meat authentication which could provide the meat industry with reliable and accurate real-time monitoring, in the near future. Full article

(This article belongs to the Special Issue Rapid Detection Methods for Food Fraud and Food Contaminants Series II)

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