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Detection of Food Fraud Using Analytical Methods

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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 (10 June 2021) | Viewed by 43557

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Special Issue Editors

Prof. Dr. Rosalee S. Hellberg

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Guest Editor

Chapman University, Schmid College of Science and Technology, Food Science Program, One University Drive, Orange, CA, 92866, USA
Interests: food safety; food microbiology; food mislabeling; DNA barcoding; real-time PCR; species identification

Prof. Dr. Robert Hanner

E-Mail Website
Guest Editor

Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
Interests: biodiversity; DNA barcoding; evolution; ichthyology; molecular authentication of foods; molecular biosurveillance; molecular diagnostics

Special Issue Information

Dear Colleagues,

Food fraud refers to the intentional misrepresentation of food or food ingredients for the purpose of economic gain. This includes the partial or complete substitution of ingredients; the addition of unapproved enhancements; dilution; and mislabeling. Food commodities that are considered especially vulnerable to food fraud include dairy products, seafood, meat and poultry, herbs and spices, oils, honey, and alcoholic or non-alcoholic beverages. Analytical methods are extensively used for the detection of food fraud, and are recognized as essential components of most food fraud mitigation plans. There is a wide range of analytical methods available for the detection of fraud in various food commodities. Often, multiple techniques are used in a complementary manner to authenticate food ingredients. The purpose of this Special Issue is to highlight current research on the development and/or application of analytical methods for the detection of food fraud.

Prof. Dr. Rosalee S. Hellberg
Prof. Dr. Robert Hanner
Guest Editors

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Keywords

food fraud
analytical methods
food authentication
food integrity
food mislabeling

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Published Papers (10 papers)

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Research

12 pages, 1619 KiB

Open AccessArticle

Development of Hydrolysis Probe-Based qPCR Assays for Panax ginseng and Panax quinquefolius for Detection of Adulteration in Ginseng Herbal Products

by Prasad Kesanakurti, Subramanyam Ragupathy, Adam C. Faller, Dhivya Shanmughanandhan, Francesco Buongiorno, Isabella Della Noce, Zhengfei Lu, Yanjun Zhang and Steven G. Newmaster

Foods 2021, 10(11), 2705; https://doi.org/10.3390/foods10112705 - 5 Nov 2021

Cited by 4 | Viewed by 2383

Abstract

Authentication of Panax ginseng and Panax quinquefolius products is important to be able to mitigate instances of adulteration and substitution that exist within the international supply chain of ginseng. To address this issue, species-specific hydrolysis probe qPCR assays were developed and validated for both P. ginseng and P. quinquefolius herbal dietary supplements. Performance of the probe-based assays was evaluated using analytical validation criteria, which included evaluation of: (1) specificity, in selectively identifying the target species; (2) sensitivity, in detecting the lowest amount of the target material; and (3) repeatability and reproducibility of the method in detecting the target species in raw materials on a real-time PCR platform (reliability). The species-specific probes were developed and successfully passed the validation criteria with 100% specificity, 80–120% efficiency and 100% reliability. The methods developed in this study are fit for purpose, rapid, and easy to implement in quality assurance programs; authentication of ginseng herbal supplements is possible, even with extracts where DNA is fragmented and of low quality and quantity. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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14 pages, 1372 KiB

Open AccessArticle

Utilizing Big Data to Identify Tiny Toxic Components: Digitalis

by Elizabeth Sage Hunter, Robert Literman and Sara M. Handy

Foods 2021, 10(8), 1794; https://doi.org/10.3390/foods10081794 - 3 Aug 2021

Cited by 3 | Viewed by 2787

Abstract

The botanical genus Digitalis is equal parts colorful, toxic, and medicinal, and its bioactive compounds have a long history of therapeutic use. However, with an extremely narrow therapeutic range, even trace amounts of Digitalis can cause adverse effects. Using chemical methods, the United States Food and Drug Administration traced a 1997 case of Digitalis toxicity to a shipment of Plantago (a common ingredient in dietary supplements marketed to improve digestion) contaminated with Digitalis lanata. With increased accessibility to next generation sequencing technology, here we ask whether this case could have been cracked rapidly using shallow genome sequencing strategies (e.g., genome skims). Using a modified implementation of the Site Identification from Short Read Sequences (SISRS) bioinformatics pipeline with whole-genome sequence data, we generated over 2 M genus-level single nucleotide polymorphisms in addition to species-informative single nucleotide polymorphisms. We simulated dietary supplement contamination by spiking low quantities (0–10%) of Digitalis whole-genome sequence data into a background of commonly used ingredients in products marketed for “digestive cleansing” and reliably detected Digitalis at the genus level while also discriminating between Digitalis species. This work serves as a roadmap for the development of novel DNA-based assays to quickly and reliably detect the presence of toxic species such as Digitalis in food products or dietary supplements using genomic methods and highlights the power of harnessing the entire genome to identify botanical species. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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17 pages, 22422 KiB

Open AccessArticle

Non-Specific Binding and Cross-Reaction of ELISA: A Case Study of Porcine Hemoglobin Detection

by Xingyi Jiang, Meng Wu, Jonathan Albo and Qinchun Rao

Foods 2021, 10(8), 1708; https://doi.org/10.3390/foods10081708 - 23 Jul 2021

Cited by 22 | Viewed by 9430

Abstract

Different types of enzyme-linked immunosorbent assays (ELISA) have been widely used to control food safety and quality. To develop an accurate and reproducible ELISA, false immunodetection results caused by non-specific binding (NSB) and cross-reaction must be prevented. During the case study of sandwich ELISA development for the detection of porcine hemoglobin (P_Hb), several critical factors leading to NSB and cross-reaction were found. First, to reduce the NSB of the target analyte, the selection of microplate and blocker was discussed. Second, cross-reactions between enzyme-labeled secondary antibodies and sample proteins were demonstrated. In addition, the function of (3-aminopropyl)triethoxysilane (APTES) was evaluated. Overall, this study highlights the essence of both antibody and assay validation to minimize any false-positive/negative immunodetection results. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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15 pages, 926 KiB

Open AccessArticle

DNA Analysis Detects Different Mislabeling Trend by Country in European Cod Fillets

by Frederik Feldmann, Alba Ardura, Carmen Blanco-Fernandez and Eva Garcia-Vazquez

Foods 2021, 10(7), 1515; https://doi.org/10.3390/foods10071515 - 30 Jun 2021

Cited by 12 | Viewed by 3044

Abstract

Atlantic cod, Gadus morhua, is a highly appreciated fish in European seafood markets and is one of the most substituted fish species in the world. Fraud have been detected in European markets in the last decade, finding different substitute species sold as G. morhua or Atlantic cod on the label. In this study, we analyzed 252 samples of fresh and frozen cod fillets sold in Germany, the Netherlands, and France using DNA barcoding. Different trends were found in different countries: while the level of mislabeling found in Germany and the Netherlands remained at zero in the last years, a significant increase was found in the French markets comparing the current results with previous studies on fillets in France. On the one hand, this mislabeling proves the need to encourage European efforts to control seafood authenticity; on the other, zero mislabeling in two countries shows the success of current European regulations. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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12 pages, 1053 KiB

Open AccessArticle

Characterizing Industrial and Artisanal Fishing Vessel Catch Composition Using Environmental DNA and Satellite-Based Tracking Data

by Demian A. Willette, Gabriela Navarrete-Forero, Zachary Gold, Apollo Marco D. Lizano, Leonardo Gonzalez-Smith and Giovanna Sotil

Foods 2021, 10(6), 1425; https://doi.org/10.3390/foods10061425 - 19 Jun 2021

Cited by 10 | Viewed by 4250

Abstract

The decline in wild-caught fisheries paired with increasing global seafood demand is pushing the need for seafood sustainability to the forefront of national and regional priorities. Validation of species identity is a crucial early step, yet conventional monitoring and surveillance tools are limited in their effectiveness because they are extremely time-consuming and require expertise in fish identification. DNA barcoding methods are a versatile tool for the genetic monitoring of wildlife products; however, they are also limited by requiring individual tissue samples from target specimens which may not always be possible given the speed and scale of seafood operations. To circumvent the need to individually sample organisms, we pilot an approach that uses forensic environmental DNA (eDNA) metabarcoding to profile fish species composition from the meltwater in fish holds on industrial and artisanal fishing vessels in Ecuador. Fish identified genetically as present were compared to target species reported by each vessel’s crew. Additionally, we contrasted the geographic range of identified species against the satellite-based fishing route data of industrial vessels to determine if identified species could be reasonably expected in the catch. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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20 pages, 1865 KiB

Open AccessArticle

Building of an Internal Transcribed Spacer (ITS) Gene Dataset to Support the Italian Health Service in Mushroom Identification

by Alice Giusti, Enrica Ricci, Laura Gasperetti, Marta Galgani, Luca Polidori, Francesco Verdigi, Roberto Narducci and Andrea Armani

Foods 2021, 10(6), 1193; https://doi.org/10.3390/foods10061193 - 25 May 2021

Cited by 12 | Viewed by 2736

Abstract

This study aims at building an ITS gene dataset to support the Italian Health Service in mushroom identification. The target species were selected among those mostly involved in regional (Tuscany) poisoning cases. For each target species, all the ITS sequences already deposited in GenBank and BOLD databases were retrieved and accurately assessed for quality and reliability by a systematic filtering process. Wild specimens of target species were also collected to produce reference ITS sequences. These were used partly to set up and partly to validate the dataset by BLAST analysis. Overall, 7270 sequences were found in the two databases. After filtering, 1293 sequences (17.8%) were discarded, with a final retrieval of 5977 sequences. Ninety-seven ITS reference sequences were obtained from 76 collected mushroom specimens: 15 of them, obtained from 10 species with no sequences available after the filtering, were used to build the dataset, with a final taxonomic coverage of 96.7%. The other 82 sequences (66 species) were used for the dataset validation. In most of the cases (n = 71; 86.6%) they matched with identity values ≥ 97–100% with the corresponding species. The dataset was able to identify the species involved in regional poisoning incidents. As some of these species are also involved in poisonings at the national level, the dataset may be used for supporting the National Health Service throughout the Italian territory. Moreover, it can support the official control activities aimed at detecting frauds in commercial mushroom-based products and safeguarding consumers. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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16 pages, 888 KiB

Open AccessArticle

Assessment of the Analytical Performance of Three Near-Infrared Spectroscopy Instruments (Benchtop, Handheld and Portable) through the Investigation of Coriander Seed Authenticity

by Claire McVey, Una Gordon, Simon A. Haughey and Christopher T. Elliott

Foods 2021, 10(5), 956; https://doi.org/10.3390/foods10050956 - 27 Apr 2021

Cited by 27 | Viewed by 3569

Abstract

The performance of three near-infrared spectroscopy (NIRS) instruments was compared through the investigation of coriander seed authenticity. The Thermo Fisher iS50 NIRS benchtop instrument, the portable Ocean Insights Flame-NIR and the Consumer Physics handheld SCiO device were assessed in conjunction with chemometric modelling in order to determine their predictive capabilities and use as quantitative tools through regression analysis. Two hundred authentic coriander seed samples and ninety adulterated samples were analysed on each device. Prediction models were developed and validated using SIMCA 15 chemometric software. All instruments correctly predicted 100% of the adulterated samples. The best models resulted in correct predictions of 100%, 98.5% and 95.6% for authentic coriander samples using spectra from the iS50, Flame-NIR and SCiO, respectively. The development of regression models highlighted the limitations of the Flame-NIR and SCiO for quantitative analysis, compared to the iS50. However, the results indicate their use as screening tools for on-site analysis of food, at various stages of the food supply chain. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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13 pages, 680 KiB

Open AccessArticle

Detection of Meat Adulteration Using Spectroscopy-Based Sensors

by Lemonia-Christina Fengou, Alexandra Lianou, Panagiοtis Tsakanikas, Fady Mohareb and George-John E. Nychas

Foods 2021, 10(4), 861; https://doi.org/10.3390/foods10040861 - 15 Apr 2021

Cited by 37 | Viewed by 6729

Abstract

Minced meat is a vulnerable to adulteration food commodity because species- and/or tissue-specific morphological characteristics cannot be easily identified. Hence, the economically motivated adulteration of minced meat is rather likely to be practiced. The objective of this work was to assess the potential of spectroscopy-based sensors in detecting fraudulent minced meat substitution, specifically of (i) beef with bovine offal and (ii) pork with chicken (and vice versa) both in fresh and frozen-thawed samples. For each case, meat pieces were minced and mixed so that different levels of adulteration with a 25% increment were achieved while two categories of pure meat also were considered. From each level of adulteration, six different samples were prepared. In total, 120 samples were subjected to visible (Vis) and fluorescence (Fluo) spectra and multispectral image (MSI) acquisition. Support Vector Machine classification models were developed and evaluated. The MSI-based models outperformed the ones based on the other sensors with accuracy scores varying from 87% to 100%. The Vis-based models followed in terms of accuracy with attained scores varying from 57% to 97% while the lowest performance was demonstrated by the Fluo-based models. Overall, spectroscopic data hold a considerable potential for the detection and quantification of minced meat adulteration, which, however, appears to be sensor-specific. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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26 pages, 8792 KiB

Open AccessArticle

Spatial Fingerprinting: Horizontal Fusion of Multi-Dimensional Bio-Tracers as Solution to Global Food Provenance Problems

by Kevin Cazelles, Tyler Stephen Zemlak, Marie Gutgesell, Emelia Myles-Gonzalez, Robert Hanner and Kevin Shear McCann

Foods 2021, 10(4), 717; https://doi.org/10.3390/foods10040717 - 28 Mar 2021

Cited by 5 | Viewed by 2772

Abstract

Building the capacity of efficiently determining the provenance of food products represents a crucial step towards the sustainability of the global food system. Despite species specific empirical examples of multi-tracer approaches to provenance, the precise benefit and efficacy of multi-tracers remains poorly understood. Here we show why, and when, data fusion of bio-tracers is an extremely powerful technique for geographical provenance discrimination. Specifically, we show using extensive simulations how, and under what conditions, geographical relationships between bio-tracers (e.g., spatial covariance) can act like a spatial fingerprint, in many naturally occurring applications likely allowing rapid identification with limited data. To highlight the theory, we outline several statistic methodologies, including artificial intelligence, and apply these methodologies as a proof of concept to a limited data set of 90 individuals of highly mobile Sockeye salmon that originate from 3 different areas. Using 17 measured bio-tracers, we demonstrate that increasing combined bio-tracers results in stronger discriminatory power. We argue such applications likely even work for such highly mobile and critical fisheries as tuna. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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9 pages, 635 KiB

Open AccessFeature PaperArticle

Use of DNA Barcoding Combined with PCR-SFLP to Authenticate Species in Bison Meat Products

by Zerika M. Scales, Elif Narbay and Rosalee S. Hellberg

Foods 2021, 10(2), 347; https://doi.org/10.3390/foods10020347 - 6 Feb 2021

Cited by 5 | Viewed by 3516

Abstract

American bison (Bison bison) meat is susceptible to species mislabeling due to its high value and similar appearance to meat from domestic cattle (Bos taurus). DNA barcoding is commonly used to identify animal species. However, as a result of the historical hybridization of American bison and domestic cattle, additional genetic testing is required for species confirmation. The objective of this study was to perform a market survey of bison meat products and verify the species using DNA barcoding combined with polymerase chain reaction-satellite fragment length polymorphism (PCR-SFLP). Bison products (n = 45) were purchased from a variety of retailers. Samples that were positive for domestic cattle with DNA barcoding were further analyzed with PCR-SFLP. DNA barcoding identified bison in 41 products, red deer (Cervus elaphus) in one product, and domestic cattle in three products. PCR-SFLP confirmed the identification of domestic cattle in two samples, while the third sample was identified as bison with ancestral cattle DNA. Overall, mislabeling was detected in 3 of the 45 samples (6.7%). This study revealed that additional DNA testing of species that have undergone historical hybridization provides improved identification results compared to DNA barcoding alone. Full article

(This article belongs to the Special Issue Detection of Food Fraud Using Analytical Methods)

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