Food Fraud as a Global Problem: Advanced Analytical Tools to Detect Species, Country of Origin and Adulterations

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 2024) | Viewed by 18896

Special Issue Editors


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Guest Editor
Research Center for Plants and Human Health, Institute of Urban Agriculture, Chinese Academy of Agricultural Sciences, National Agricultural Science and Technology Center, Chengdu 610213, China
Interests: food authentication; polyphenol; MS-based metabolomics; functional food; chemometrics
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Guangdong Province Key Laboratory of Food Quality and Safety/National-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
Interests: food authenticity; biosensor; chemometrics; food safety; food analysis; immunoassay; antibody engineering; hapten design
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Institute of Agro-Products Processing Science and Technology, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-Products Processing, Ministry of Agriculture, Beijing, China
Interests: cereal storage; cereal processing; quality control; cereal geographical traceability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the development of a globalized food market, food fraud has become a crucial issue over the world. Adulteration, substitution, and the deliberately incorrect labeling of species and geographical origins of food are considered the main cases of food fraud. Some unscrupulous traders replace special local products with inferior or counterfeit products, substitute labeled food species with others, or extend the shelf life of food by using banned chemicals for economic profit, which can pose a great threat to human health.

Therefore, advanced analytical tools are needed as scientific support against food fraud. Food authentication involves procedures to determine whether the product complies with its labeling, and whether it conforms to the legal standards and regulations that govern its consumption. The combination of appropriate techniques and statistic methods are considered to be powerful tools for identifying cases of food fraud.

This Special Issue aims to bring together the most recent research advances associated with the latest techniques and methods for identifying food fraud. We encourage the submissions of original research articles, perspectives, opinion articles, and reviews that focus on, but are not limited to, the following potential topics: Food fraud, stable isotopic ratios/elements, targeted and untargeted omics (LC-MS, GC-MS, etc.), spectroscopy (NIR, MIR, etc.), genetic analyses, and chemometrics/statistic methods.

Dr. Hongyan Liu
Prof. Dr. Hongtao Lei
Prof. Dr. Boli Guo
Dr. Ren-You Gan 
Guest Editors

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Keywords

  • geographical origin
  • food fraud
  • food adulteration
  • fingerprints
  • stable isotopic ratios
  • spectroscopy
  • omics

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Published Papers (10 papers)

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Research

Jump to: Review

13 pages, 6020 KiB  
Article
DNA Barcoding Unveils Novel Discoveries in Authenticating High-Value Snow Lotus Seed Food Products
by Gang Zhao, Lingyu Li, Xing Shen, Ruimin Zhong, Qingping Zhong and Hongtao Lei
Foods 2024, 13(16), 2580; https://doi.org/10.3390/foods13162580 - 18 Aug 2024
Viewed by 704
Abstract
Snow Lotus Seed (SLS), esteemed for its nutritional and market value, faces challenges of authentication due to the absence of appropriate testing standards and methods. This results in frequent adulteration of SLS sourced from Gleditsia sinensis (G. sinensis) with other plant [...] Read more.
Snow Lotus Seed (SLS), esteemed for its nutritional and market value, faces challenges of authentication due to the absence of appropriate testing standards and methods. This results in frequent adulteration of SLS sourced from Gleditsia sinensis (G. sinensis) with other plant seeds endosperm. Traditional chloroplast DNA barcoding methods are inadequate for species identification due to the absence of chloroplasts in G. sinensis seeds endosperm. In this study, the homology of 11 ITS genes among 6 common Gleditsia species was analyzed. Universal primers suitable for these species were designed and screened. A DNA barcoding method for distinguishing SLS species was developed using Sanger sequencing technology, leveraging existing GenBank and Barcode of Life Data System (BOLD) databases. Optimized sample pretreatment facilitated effective DNA extraction from phytopolysaccharide-rich SLS. Through testing of commercial SLS products, the species origin has been successfully identified. Additionally, a novel instance of food fraud was uncovered, where the Caesalpinia spinosa endosperm was used to counterfeit SLS for the first time. The study established that the developed DNA barcoding method is effective for authenticating SLS species. It is of great significance for combating food fraud related to SLS, ensuring food safety, and promoting the healthy development of the SLS industry. Full article
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14 pages, 3519 KiB  
Article
Laser-Induced Breakdown Spectroscopy–Visible and Near-Infrared Spectroscopy Fusion Based on Deep Learning Network for Identification of Adulterated Polygonati Rhizoma
by Feng Chen, Mengsheng Zhang, Weihua Huang, Harse Sattar and Lianbo Guo
Foods 2024, 13(14), 2306; https://doi.org/10.3390/foods13142306 - 22 Jul 2024
Viewed by 1049
Abstract
The geographical origin of foods greatly influences their quality and price, leading to adulteration between high-priced and low-priced regions in the market. The rapid detection of such adulteration is crucial for food safety and fair competition. To detect the adulteration of Polygonati Rhizoma [...] Read more.
The geographical origin of foods greatly influences their quality and price, leading to adulteration between high-priced and low-priced regions in the market. The rapid detection of such adulteration is crucial for food safety and fair competition. To detect the adulteration of Polygonati Rhizoma from different regions, we proposed LIBS-VNIR fusion based on the deep learning network (LVDLNet), which combines laser-induced breakdown spectroscopy (LIBS) containing element information with visible and near-infrared spectroscopy (VNIR) containing molecular information. The LVDLNet model achieved accuracy of 98.75%, macro-F measure of 98.50%, macro-precision of 98.78%, and macro-recall of 98.75%. The model, which increased these metrics from about 87% for LIBS and about 93% for VNIR to more than 98%, significantly improved the identification ability. Furthermore, tests on different adulterated source samples confirmed the model’s robustness, with all metrics improving from about 87% for LIBS and 86% for VNIR to above 96%. Compared to conventional machine learning algorithms, LVDLNet also demonstrated its superior performance. The results indicated that the LVDLNet model can effectively integrate element information and molecular information to identify the adulterated Polygonati Rhizoma. This work shows that the scheme is a potent tool for food identification applications. Full article
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12 pages, 299 KiB  
Article
Exploring the Influence of Soil Types on the Mineral Profile of Honey: Implications for Geographical Origin Prediction
by Simona Schmidlová, Zdeňka Javůrková, Bohuslava Tremlová, Józef Hernik, Barbara Prus, Slavomír Marcinčák, Dana Marcinčáková, Pavel Štarha, Helena Čížková, Vojtěch Kružík, Zsanett Bodor, Csilla Benedek, Dalibor Titěra, Jana Boržíková and Matej Pospiech
Foods 2024, 13(13), 2006; https://doi.org/10.3390/foods13132006 - 25 Jun 2024
Viewed by 1223
Abstract
Honey contains a wide range of inorganic substances. Their content can be influenced, i.e., by the type of soil on which the bee pasture is located. As part of this study, the mineral profile of 32 samples of honey from hobby beekeepers from [...] Read more.
Honey contains a wide range of inorganic substances. Their content can be influenced, i.e., by the type of soil on which the bee pasture is located. As part of this study, the mineral profile of 32 samples of honey from hobby beekeepers from the Czech Republic wasevaluated and then compared with soil types in the vicinity of the beehive location. Pearson’s correlation coefficient was used to express the relationship between mineral substances and soil type. There was a high correlation between antroposol and Zn (R = 0.98), Pb (R = 0.96), then between ranker and Mn (0.95), then regosol and Al (R = 0.97) (p < 0.05). A high negative correlation was found between regosol and Mg (R = −0.97), Cr (R = −0.98) and between redzinas and Al (R = −0.97) (p < 0.05). Both positive and negative high correlations were confirmed for phaeozem. The CART method subsequently proved that the characteristic elements for individual soil types are B, Ca, Mg, Ni, and Mn. The soil types of cambisol, fluvisol, gleysol, anthrosol, and kastanozem had the closest relationship with the elements mentioned, and it can therefore be assumed that their occurrence indicates the presence of these soil types within the range of beehive location. Full article
15 pages, 1559 KiB  
Article
Effects of Geographical Origin and Tree Age on the Stable Isotopes and Multi-Elements of Pu-erh Tea
by Ming-Ming Chen, Qiu-Hong Liao, Li-Li Qian, Hai-Dan Zou, Yan-Long Li, Yan Song, Yu Xia, Yi Liu, Hong-Yan Liu and Ze-Long Liu
Foods 2024, 13(3), 473; https://doi.org/10.3390/foods13030473 - 2 Feb 2024
Cited by 1 | Viewed by 1195
Abstract
Pu-erh tea is a famous tea worldwide, and identification of the geographical origin of Pu-erh tea can not only protect manufacture’s interests, but also boost consumers’ confidence. However, tree age may also influence the fingerprints of Pu-erh tea. In order to study the [...] Read more.
Pu-erh tea is a famous tea worldwide, and identification of the geographical origin of Pu-erh tea can not only protect manufacture’s interests, but also boost consumers’ confidence. However, tree age may also influence the fingerprints of Pu-erh tea. In order to study the effects of the geographical origin and tree age on the interactions of stable isotopes and multi-elements of Pu-erh tea, 53 Pu-erh tea leaves with three different age stages from three different areas in Yunnan were collected in 2023. The δ13C, δ15N values and 25 elements were determined and analyzed. The results showed that δ13C, δ15N, Mg, Mn, Fe, Cu, Zn, Rb, Sr, Y, La, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu had significant differences among different geographical origins (p < 0.05). Mn content was significantly influenced by region and tree age interaction. Based on multi-way analysis of variance, principal component analysis and step-wised discriminant analysis, 24 parameters were found to be closely related to the geographical origin rather than tree age, and the geographical origin of Pu-erh tea can be 100.0% discriminated in cross-validation with six parameters (δ13C, δ15N, Mn, Mg, La, and Tb). The study could provide references for the establishment of a database for the traceability of Pu-erh tea, and even the identification of tea sample regions with different tree ages. Full article
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17 pages, 7905 KiB  
Communication
Traceability Research on Dendrobium devonianum Based on SWATHtoMRM
by Tao Lin, Xinglian Chen, Lijuan Du, Jing Wang, Zhengxu Hu, Long Cheng, Zhenhuan Liu and Hongcheng Liu
Foods 2023, 12(19), 3608; https://doi.org/10.3390/foods12193608 - 28 Sep 2023
Cited by 1 | Viewed by 1266
Abstract
SWATHtoMRM technology was used in this experiment to further identify and trace the sources of Dendrobium devonianum and Dendrobium officinale produced in the same area using TOF and MS-MRM. After the conversion of the R package of SWATHtoMRM, 191 MRM pairs of positive [...] Read more.
SWATHtoMRM technology was used in this experiment to further identify and trace the sources of Dendrobium devonianum and Dendrobium officinale produced in the same area using TOF and MS-MRM. After the conversion of the R package of SWATHtoMRM, 191 MRM pairs of positive ions and 96 pairs of negative ions were obtained. Dendrobium devonianum and Dendrobium officinale can be separated very well using the PCA and PLS-DA analysis of MRM ion pairs; this shows that there are obvious differences in chemical composition between Dendrobium devonianum and Dendrobium officinale, which clearly proves that the pseudotargeted metabolomics method based on SWATHtoMRM can be used for traceability identification research. A total of 146 characteristic compounds were obtained, with 20 characteristic compounds in Dendrobium devonianum. The enrichment pathways of the characteristic compounds were mainly concentrated in lipids and atherosclerosis, chagas disease, fluid shear stress and atherosclerosis, proteoglycans in cancer, the IL-17 signaling pathway, the sphingolipid signaling pathway, diabetic cardiomyopathy, arginine and proline metabolism, etc., among which the lipid and atherosclerosis pathways were more enriched, and 11 characteristic compounds affected the expression levels of IL-1, TNFα, CD36, IL-1β, etc. These can be used as a reference for research on variety improvement and active substance accumulation in Dendrobium devonianum and Dendrobium officinale. Full article
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8 pages, 756 KiB  
Communication
Cuttlefish Species Authentication: Advancing Label Control through Near-Infrared Spectroscopy as Rapid, Eco-Friendly, and Robust Approach
by Sarah Currò, Stefania Balzan, Enrico Novelli and Luca Fasolato
Foods 2023, 12(15), 2973; https://doi.org/10.3390/foods12152973 - 7 Aug 2023
Cited by 2 | Viewed by 1371
Abstract
Accurate species identification, especially in the fishery sector, is critical for ensuring food safety, consumer protection and to prevent economic losses. In this study, a total of 93 individual frozen–thawed cuttlefish samples from four different species (S. officinalis, S. bertheloti, [...] Read more.
Accurate species identification, especially in the fishery sector, is critical for ensuring food safety, consumer protection and to prevent economic losses. In this study, a total of 93 individual frozen–thawed cuttlefish samples from four different species (S. officinalis, S. bertheloti, S. aculeata, and Sepiella inermis) were collected from two wholesale fish plants in Chioggia, Italy. Species identification was carried out by inspection through morphological features using dichotomic keys and then through near-infrared spectroscopy (NIRS) measurements. The NIRS data were collected using a handled-portable spectrophotometer, and the spectral range scanned was from 900–1680 nm. The collected spectra were processed using principal component analysis for unsupervised analysis and a support vector machine for supervised analysis to evaluate the species identification capability. The results showed that NIRS classification had a high overall accuracy of 93% in identifying the cuttlefish species. This finding highlights the robustness and effectiveness of spectral analysis as a tool for species identification, even in complex spatial contexts. The findings emphasize the potential of NIRS as a valuable tool in the field of fishery product authentication, offering a rapid and eco-friendly approach to species identification in the post-processing stages. Full article
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15 pages, 5225 KiB  
Article
Effects of Light Shading, Fertilization, and Cultivar Type on the Stable Isotope Distribution of Hybrid Rice
by Syed Abdul Wadood, Yunzhu Jiang, Jing Nie, Chunlin Li, Karyne M. Rogers, Hongyan Liu, Yongzhi Zhang, Weixing Zhang and Yuwei Yuan
Foods 2023, 12(9), 1832; https://doi.org/10.3390/foods12091832 - 28 Apr 2023
Cited by 3 | Viewed by 1416
Abstract
The effect of fertilizer supply and light intensity on the distribution of elemental contents (%C and %N) and light stable isotopes (C, N, H, and O) in different rice fractions (rice husk, brown rice, and polished rice) of two hybrid rice cultivars (maintainer [...] Read more.
The effect of fertilizer supply and light intensity on the distribution of elemental contents (%C and %N) and light stable isotopes (C, N, H, and O) in different rice fractions (rice husk, brown rice, and polished rice) of two hybrid rice cultivars (maintainer lines You-1B and Zhong-9B) were investigated. Significant variations were observed for δ13C (−31.3 to −28.3‰), δ15N (2.4 to 2.7‰), δ2H (−125.7 to −84.7‰), and δ18O (15.1‰ to 23.7‰) values in different rice fractions among different cultivars. Fertilizer treatments showed a strong association with %N, δ15N, δ2H, and δ18O values while it did not impart any significant variation for the %C and δ13C values. Light intensity levels also showed a significant influence on the isotopic values of different rice fractions. The δ13C values showed a positive correlation with irradiance. The δ2H and δ15N values decreased with an increase in the irradiance. The light intensity levels did not show any significant change for δ18O values in rice fractions. Multivariate ANOVA showed a significant interaction effect of different factors (light intensity, fertilizer concentration, and rice variety) on the isotopic composition of rice fractions. It is concluded that all environmental and cultivation factors mentioned above significantly influenced the isotopic values and should be considered when addressing the authenticity and origin of rice. Furthermore, care should be taken when selecting rice fractions for traceability and authenticity studies since isotopic signatures vary considerably among different rice fractions. Full article
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19 pages, 2516 KiB  
Article
Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding
by Grégoire Denay, Laura Preckel, Henning Petersen, Klaus Pietsch, Anne Wöhlke and Claudia Brünen-Nieweler
Foods 2023, 12(5), 968; https://doi.org/10.3390/foods12050968 - 24 Feb 2023
Cited by 1 | Viewed by 2147
Abstract
DNA-metabarcoding is becoming more widely used for routine authentication of meat-based food and feed products. Several methods validating species identification methods through amplicon sequencing have already been published. These use a variety of barcodes and analysis workflows, however, no methodical comparison of available [...] Read more.
DNA-metabarcoding is becoming more widely used for routine authentication of meat-based food and feed products. Several methods validating species identification methods through amplicon sequencing have already been published. These use a variety of barcodes and analysis workflows, however, no methodical comparison of available algorithms and parameter optimization are published hitherto for meat-based products’ authenticity. Additionally, many published methods use very small subsets of the available reference sequences, thereby limiting the potential of the analysis and leading to over-optimistic performance estimates. We here predict and compare the ability of published barcodes to distinguish taxa in the BLAST NT database. We then use a dataset of 79 reference samples, spanning 32 taxa, to benchmark and optimize a metabarcoding analysis workflow for 16S rDNA Illumina sequencing. Furthermore, we provide recommendations as to the parameter choices, sequencing depth, and thresholds that should be used to analyze meat metabarcoding sequencing experiments. The analysis workflow is publicly available, and includes ready-to-use tools for validation and benchmarking. Full article
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17 pages, 2546 KiB  
Communication
Development of Non-Targeted Mass Spectrometry Method for Distinguishing Spelt and Wheat
by Kapil Nichani, Steffen Uhlig, Bertrand Colson, Karina Hettwer, Kirsten Simon, Josephine Bönick, Carsten Uhlig, Sabine Kemmlein, Manfred Stoyke, Petra Gowik, Gerd Huschek and Harshadrai M. Rawel
Foods 2023, 12(1), 141; https://doi.org/10.3390/foods12010141 - 27 Dec 2022
Cited by 2 | Viewed by 1978
Abstract
Food fraud, even when not in the news, is ubiquitous and demands the development of innovative strategies to combat it. A new non-targeted method (NTM) for distinguishing spelt and wheat is described, which aids in food fraud detection and authenticity testing. A highly [...] Read more.
Food fraud, even when not in the news, is ubiquitous and demands the development of innovative strategies to combat it. A new non-targeted method (NTM) for distinguishing spelt and wheat is described, which aids in food fraud detection and authenticity testing. A highly resolved fingerprint in the form of spectra is obtained for several cultivars of spelt and wheat using liquid chromatography coupled high-resolution mass spectrometry (LC-HRMS). Convolutional neural network (CNN) models are built using a nested cross validation (NCV) approach by appropriately training them using a calibration set comprising duplicate measurements of eleven cultivars of wheat and spelt, each. The results reveal that the CNNs automatically learn patterns and representations to best discriminate tested samples into spelt or wheat. This is further investigated using an external validation set comprising artificially mixed spectra, samples for processed goods (spelt bread and flour), eleven untypical spelt, and six old wheat cultivars. These cultivars were not part of model building. We introduce a metric called the D score to quantitatively evaluate and compare the classification decisions. Our results demonstrate that NTMs based on NCV and CNNs trained using appropriately chosen spectral data can be reliable enough to be used on a wider range of cultivars and their mixes. Full article
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Review

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25 pages, 666 KiB  
Review
Molecular Barcoding: A Tool to Guarantee Correct Seafood Labelling and Quality and Preserve the Conservation of Endangered Species
by Laura Filonzi, Alessia Ardenghi, Pietro Maria Rontani, Andrea Voccia, Claudio Ferrari, Riccardo Papa, Nicolò Bellin and Francesco Nonnis Marzano
Foods 2023, 12(12), 2420; https://doi.org/10.3390/foods12122420 - 20 Jun 2023
Cited by 4 | Viewed by 4133
Abstract
The recent increase in international fish trade leads to the need for improving the traceability of fishery products. In relation to this, consistent monitoring of the production chain focusing on technological developments, handling, processing and distribution via global networks is necessary. Molecular barcoding [...] Read more.
The recent increase in international fish trade leads to the need for improving the traceability of fishery products. In relation to this, consistent monitoring of the production chain focusing on technological developments, handling, processing and distribution via global networks is necessary. Molecular barcoding has therefore been suggested as the gold standard in seafood species traceability and labelling. This review describes the DNA barcoding methodology for preventing food fraud and adulteration in fish. In particular, attention has been focused on the application of molecular techniques to determine the identity and authenticity of fish products, to discriminate the presence of different species in processed seafood and to characterize raw materials undergoing food industry processes. In this regard, we herein present a large number of studies performed in different countries, showing the most reliable DNA barcodes for species identification based on both mitochondrial (COI, cytb, 16S rDNA and 12S rDNA) and nuclear genes. Results are discussed considering the advantages and disadvantages of the different techniques in relation to different scientific issues. Special regard has been dedicated to a dual approach referring to both the consumer’s health and the conservation of threatened species, with a special focus on the feasibility of the different genetic and genomic approaches in relation to both scientific objectives and permissible costs to obtain reliable traceability. Full article
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