Editorial

6 pages, 216 KiB

Open AccessEditorial

Target and Non-Target Approaches for Food Authenticity and Traceability

by Joana S. Amaral

Foods 2021, 10(1), 172; https://doi.org/10.3390/foods10010172 - 16 Jan 2021

Cited by 16 | Viewed by 3676

In the last decade, consumers have become increasingly aware of and concerned about the quality and safety of food, in part due to several scandals that were widely disseminated by the media [...] Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

Research

Jump to: Editorial, Review

15 pages, 1509 KiB

Open AccessArticle

Machine Learning Approaches Applied to GC-FID Fatty Acid Profiles to Discriminate Wild from Farmed Salmon

by Liliana Grazina, P. J. Rodrigues, Getúlio Igrejas, Maria A. Nunes, Isabel Mafra, Marco Arlorio, M. Beatriz P. P. Oliveira and Joana S. Amaral

Foods 2020, 9(11), 1622; https://doi.org/10.3390/foods9111622 - 07 Nov 2020

Cited by 10 | Viewed by 2739

Abstract

In the last decade, there has been an increasing demand for wild-captured fish, which attains higher prices compared to farmed species, thus being prone to mislabeling practices. In this work, fatty acid composition coupled to advanced chemometrics was used to discriminate wild from [...] Read more.

In the last decade, there has been an increasing demand for wild-captured fish, which attains higher prices compared to farmed species, thus being prone to mislabeling practices. In this work, fatty acid composition coupled to advanced chemometrics was used to discriminate wild from farmed salmon. The lipids extracted from salmon muscles of different production methods and origins (26 wild from Canada, 25 farmed from Canada, 24 farmed from Chile and 25 farmed from Norway) were analyzed by gas chromatography with flame ionization detector (GC-FID). All the tested chemometric approaches, namely principal components analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and seven machine learning classifiers, namely k-nearest neighbors (kNN), decision tree, support vector machine (SVM), random forest, artificial neural networks (ANN), naïve Bayes and AdaBoost, allowed for differentiation between farmed and wild salmons using the 17 features obtained from chemical analysis. PCA did not allow clear distinguishing between salmon geographical origin since farmed samples from Canada and Chile overlapped. Nevertheless, using the 17 features in the models, six out of the seven tested machine learning classifiers allowed a classification accuracy of ≥99%, with ANN, naïve Bayes, random forest, SVM and kNN presenting 100% accuracy on the test dataset. The classification models were also assayed using only the best features selected by a reduction algorithm and the best input features mapped by t-SNE. The classifier kNN provided the best discrimination results because it correctly classified all samples according to production method and origin, ultimately using only the three most important features (16:0, 18:2n6c and 20:3n3 + 20:4n6). In general, the classifiers presented good generalization with the herein proposed approach being simple and presenting the advantage of requiring only common equipment existing in most labs. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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15 pages, 1929 KiB

Open AccessArticle

Procedures for DNA Extraction from Opium Poppy (Papaver somniferum L.) and Poppy Seed-Containing Products

by Šarlota Kaňuková, Michaela Mrkvová, Daniel Mihálik and Ján Kraic

Foods 2020, 9(10), 1429; https://doi.org/10.3390/foods9101429 - 09 Oct 2020

Cited by 3 | Viewed by 3782

Abstract

Several commonly used extraction procedures and commercial kits were compared for extraction of DNA from opium poppy (Papaver somniferum L.) seeds, ground seeds, pollen grains, poppy seed filling from a bakery product, and poppy oil. The newly developed extraction protocol was much [...] Read more.

Several commonly used extraction procedures and commercial kits were compared for extraction of DNA from opium poppy (Papaver somniferum L.) seeds, ground seeds, pollen grains, poppy seed filling from a bakery product, and poppy oil. The newly developed extraction protocol was much simpler, reduced the cost and time required for DNA extraction from the native and ground seeds, and pollen grains. The quality of extracted DNA by newly developed protocol was better or comparable to the most efficient ones. After being extended by a simple purification step on a silica membrane column, the newly developed protocol was also very effective in extracting of poppy DNA from poppy seed filling. DNA extracted from this poppy matrix was amplifiable by PCR analysis. DNA extracted from cold-pressed poppy oil and suitable for amplifications was obtained only by methods developed previously for olive oil. Extracted poppy DNA from all tested matrices was analysed by PCR using primers flanking a microsatellite locus (156 bp) and two different fragments of the reference tubulin gene (553 bp and 96 bp). The long fragment of the reference gene was amplified in DNA extracted from native seeds, ground seeds, and pollen grains. Poppy DNA extracted from the filling of bakery product was confirmed only by amplification of short fragments (96 bp and 156 bp). DNA extracted from cold-pressed poppy oil was determined also only by amplification of these two short fragments. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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12 pages, 635 KiB

Open AccessFeature PaperArticle

Authentication of Ginkgo biloba Herbal Products by a Novel Quantitative Real-Time PCR Approach

by Liliana Grazina, Joana S. Amaral, Joana Costa and Isabel Mafra

Foods 2020, 9(9), 1233; https://doi.org/10.3390/foods9091233 - 04 Sep 2020

Cited by 9 | Viewed by 2776

Abstract

Ginkgo biloba is a widely used medicinal plant. Due to its potential therapeutic effects, it is an ingredient in several herbal products, such as plant infusions and plant food supplements (PFS). Currently, ginkgo is one of the most popular botanicals used in PFS. [...] Read more.

Ginkgo biloba is a widely used medicinal plant. Due to its potential therapeutic effects, it is an ingredient in several herbal products, such as plant infusions and plant food supplements (PFS). Currently, ginkgo is one of the most popular botanicals used in PFS. Due to their popularity and high cost, ginkgo-containing products are prone to be fraudulently substituted by other plant species. Therefore, this work aimed at developing a method for G. biloba detection and quantification. A new internal transcribe spacer (ITS) marker was identified, allowing the development of a ginkgo-specific real-time polymerase chain reaction (PCR) assay targeting the ITS region, with high specificity and sensitivity, down to 0.02 pg of DNA. Additionally, a normalized real-time PCR approach using the delta cycle quantification (ΔCq) method was proposed for the effective quantification of ginkgo in plant mixtures. The method exhibited high performance parameters, namely PCR efficiency, coefficient of correlation and covered dynamic range (50–0.01%), achieving limits of detection and quantification of 0.01% (w/w) of ginkgo in tea plant (Camellia sinensis). The quantitative approach was successfully validated with blind mixtures and further applied to commercial ginkgo-containing herbal infusions. The estimated ginkgo contents of plant mixture samples suggest adulterations due to reduction or almost elimination of ginkgo. In this work, useful and robust tools were proposed to detect/quantify ginkgo in herbal products, which suggests the need for a more effective and stricter control of such products. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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11 pages, 1169 KiB

Open AccessArticle

Geographical Origin Discrimination of Monofloral Honeys by Direct Analysis in Real Time Ionization-High Resolution Mass Spectrometry (DART-HRMS)

by Vincenzo Lippolis, Elisabetta De Angelis, Giuseppina Maria Fiorino, Annalisa Di Gioia, Marco Arlorio, Antonio Francesco Logrieco and Linda Monaci

Foods 2020, 9(9), 1205; https://doi.org/10.3390/foods9091205 - 01 Sep 2020

Cited by 8 | Viewed by 3136

Abstract

An untargeted method using direct analysis in real time and high resolution mass spectrometry (DART-HRMS) combined to multivariate statistical analysis was developed for the discrimination of two monofloral (chestnut and acacia) honeys for their geographical origins—i.e., Italy and Portugal for chestnut honey and [...] Read more.

An untargeted method using direct analysis in real time and high resolution mass spectrometry (DART-HRMS) combined to multivariate statistical analysis was developed for the discrimination of two monofloral (chestnut and acacia) honeys for their geographical origins—i.e., Italy and Portugal for chestnut honey and Italy and China for acacia honey. Principal Component Analysis, used as an unsupervised approach, showed samples of clusterization for chestnut honey samples, while overlapping regions were observed for acacia honeys. Three supervised statistical approaches, such as Principal Components—Linear Discriminant Analysis, Partial Least Squares—Discriminant Analysis and k-nearest neighbors, were tested on the dataset gathered and relevant performances were compared. All tested statistical approaches provided comparable prediction abilities in cross-validation and external validation with mean values falling between 89.2–98.4% for chestnut and between 85.8–95.0% for acacia honey. The results obtained herein indicate the feasibility of the DART-HRMS approach in combination with chemometrics for the rapid authentication of honey’s geographical origin. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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16 pages, 2825 KiB

Open AccessArticle

Comparison of Targeted (HPLC) and Nontargeted (GC-MS and NMR) Approaches for the Detection of Undeclared Addition of Protein Hydrolysates in Turkey Breast Muscle

by Liane Wagner, Manuela Peukert, Bertolt Kranz, Natalie Gerhardt, Sabine Andrée, Ulrich Busch and Dagmar Adeline Brüggemann

Foods 2020, 9(8), 1084; https://doi.org/10.3390/foods9081084 - 08 Aug 2020

Cited by 6 | Viewed by 3376

Abstract

The adulteration of fresh turkey meat by the undeclared addition of protein hydrolysates is of interest for fraudsters due to the increase of the economic gain by substituting meat with low cost ingredients. The aim of this study was to compare the suitability [...] Read more.

The adulteration of fresh turkey meat by the undeclared addition of protein hydrolysates is of interest for fraudsters due to the increase of the economic gain by substituting meat with low cost ingredients. The aim of this study was to compare the suitability of three different analytical techniques such as GC-MS and ¹H-NMR with HPLC-UV/VIS as a targeted method, for the detection of with protein hydrolysates adulterated turkey meat. For this, turkey breast muscles were treated with different plant- (e.g., wheat) and animal-based (e.g., gelatin, casein) protein hydrolysates with different hydrolyzation degrees (15–53%: partial; 100%: total), which were produced by enzymatic and acidic hydrolysis. A water- and a nontreated sample (REF) served as controls. The data analyses revealed that the hydrolysate-treated samples had significantly higher levels of amino acids (e.g., leucine, phenylalanine, lysine) compared with REF observed with all three techniques concordantly. Furthermore, the nontargeted metabolic profiling (GC-MS and NMR) showed that sugars (glucose, maltose) and/or by-products (build and released during acidic hydrolyses, e.g., levulinic acid) could be used for the differentiation between control and hydrolysates (type, degrees). The combination of amino acid profiling and additional compounds gives stronger evidence for the detection and classification of adulteration in turkey breast meat. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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18 pages, 1361 KiB

Open AccessArticle

Comparison of Real-Time PCR Quantification Methods in the Identification of Poultry Species in Meat Products

by Kerstin Dolch, Sabine Andrée and Fredi Schwägele

Foods 2020, 9(8), 1049; https://doi.org/10.3390/foods9081049 - 03 Aug 2020

Cited by 12 | Viewed by 2890

Abstract

Poultry meat is consumed worldwide and is prone to food fraud because of large price differences among meat from different poultry species. Precise and sensitive analytical methods are necessary to control poultry meat products. We chose species–specific sequences of the cytochrome b gene [...] Read more.

Poultry meat is consumed worldwide and is prone to food fraud because of large price differences among meat from different poultry species. Precise and sensitive analytical methods are necessary to control poultry meat products. We chose species–specific sequences of the cytochrome b gene to develop two multiplex real-time polymerase chain reaction (real-time PCR) systems: one for chicken (Gallus gallus), guinea fowl (Numida meleagris), and pheasant (Phasianus colchicus), and one for quail (Coturnix japonica) and turkey (Meleagris gallopavo). For each species, added meat could be detected down to 0.5 % w/w. No cross reactions were seen. For these two real-time PCR systems, we applied three different quantification methods: (A) with relative standard curves, (B) with matrix-specific multiplication factors, and (C) with an internal DNA reference sequence to normalize and to control inhibition. All three quantification methods had reasonable recovery rates from 43% to 173%. Method B had more accepted recovery rates, i.e., in the range 70–130%, namely 83% compared to 75% for method A or C. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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16 pages, 3818 KiB

Open AccessArticle

Metabolite Profiling and Chemometric Study for the Discrimination Analyses of Geographic Origin of Perilla (Perilla frutescens) and Sesame (Sesamum indicum) Seeds

by Tae Jin Kim, Jeong Gon Park, Hyun Young Kim, Sun-Hwa Ha, Bumkyu Lee, Sang Un Park, Woo Duck Seo and Jae Kwang Kim

Foods 2020, 9(8), 989; https://doi.org/10.3390/foods9080989 - 24 Jul 2020

Cited by 17 | Viewed by 3190

Abstract

Perilla and sesame are traditional sources of edible oils in Asian and African countries. In addition, perilla and sesame seeds are rich sources of health-promoting compounds, such as fatty acids, tocopherols, phytosterols and policosanols. Thus, developing a method to determine the geographic origin [...] Read more.

Perilla and sesame are traditional sources of edible oils in Asian and African countries. In addition, perilla and sesame seeds are rich sources of health-promoting compounds, such as fatty acids, tocopherols, phytosterols and policosanols. Thus, developing a method to determine the geographic origin of these seeds is important for ensuring authenticity, safety and traceability and to prevent cheating. We aimed to develop a discriminatory predictive model for determining the geographic origin of perilla and sesame seeds using comprehensive metabolite profiling coupled with chemometrics. The orthogonal partial least squares-discriminant analysis models were well established with good validation values (Q² = 0.761 to 0.799). Perilla and sesame seed samples used in this study showed a clear separation between Korea and China as geographic origins in our predictive models. We found that glycolic acid could be a potential biomarker for perilla seeds and proline and glycine for sesame seeds. Our findings provide a comprehensive quality assessment of perilla and sesame seeds. We believe that our models can be used for regional authentication of perilla and sesame seeds cultivated in diverse geographic regions. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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9 pages, 3041 KiB

Open AccessCommunication

Species Identification of Red Deer (Cervus elaphus), Roe Deer (Capreolus capreolus), and Water Deer (Hydropotes inermis) Using Capillary Electrophoresis-Based Multiplex PCR

by Mi-Ju Kim, Yu-Min Lee, Seung-Man Suh and Hae-Yeong Kim

Foods 2020, 9(8), 982; https://doi.org/10.3390/foods9080982 - 23 Jul 2020

Cited by 14 | Viewed by 2715

Abstract

To provide consumers correct information on meat species, specific and sensitive detection methods are needed. Thus, we developed a capillary electrophoresis-based multiplex PCR assay to simultaneously detect red deer (Cervus elaphus), roe deer (Capreolus capreolus), and water deer ( [...] Read more.

To provide consumers correct information on meat species, specific and sensitive detection methods are needed. Thus, we developed a capillary electrophoresis-based multiplex PCR assay to simultaneously detect red deer (Cervus elaphus), roe deer (Capreolus capreolus), and water deer (Hydropotes inermis). Specific primer sets for these three species were newly designed. Each primer set only amplified target species without any reactivity against non-target species. To identify multiple targets in a single reaction, multiplex PCR was optimized and combined with capillary electrophoresis to increase resolution and accuracy for the detection of multiple targets. The detection levels of this assay were 0.1 pg for red deer and roe deer and 1 pg for water deer. In addition, its applicability was demonstrated using various concentrations of meat DNA mixtures. Consequently, as low as 0.1% of the target species was detectable using the developed method. This capillary electrophoresis-based multiplex PCR assay for simultaneous detection of three types of deer meat could authenticate deer species labeled on products, thus protecting consumers from meat adulteration. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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16 pages, 2613 KiB

Open AccessArticle

Food Authentication: Truffle (Tuber spp.) Species Differentiation by FT-NIR and Chemometrics

by Torben Segelke, Stefanie Schelm, Christian Ahlers and Markus Fischer

Foods 2020, 9(7), 922; https://doi.org/10.3390/foods9070922 - 13 Jul 2020

Cited by 21 | Viewed by 3946

Abstract

Truffles are certainly the most expensive mushrooms; the price depends primarily on the species and secondly on the origin. Because of the price differences for the truffle species, food fraud is likely to occur, and the visual differentiation is difficult within the group [...] Read more.

Truffles are certainly the most expensive mushrooms; the price depends primarily on the species and secondly on the origin. Because of the price differences for the truffle species, food fraud is likely to occur, and the visual differentiation is difficult within the group of white and within the group of black truffles. Thus, the aim of this study was to develop a reliable method for the authentication of five commercially relevant truffle species via Fourier transform near-infrared (FT-NIR) spectroscopy as an easy to handle approach combined with chemometrics. NIR-data from 75 freeze-dried fruiting bodies were recorded. Various spectra pre-processing techniques and classification methods were compared and validated using nested cross-validation. For the white truffle species, the most expensive Tuber magnatum could be differentiated with an accuracy of 100% from Tuber borchii. Regarding the black truffle species, the relatively expensive Tuber melanosporum could be distinguished from Tuber aestivum and the Chinese truffles with an accuracy of 99%. Since the most expensive Italian Tuber magnatum is highly prone to fraud, the origin was investigated and Italian T. magnatum truffles could be differentiated from non-Italian T. magnatum truffles by 83%. Our results demonstrate the potential of FT-NIR spectroscopy for the authentication of truffle species. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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11 pages, 1557 KiB

Open AccessArticle

A Chip Digital PCR Assay for Quantification of Common Wheat Contamination in Pasta Production Chain

by Caterina Morcia, Raffaella Bergami, Sonia Scaramagli, Roberta Ghizzoni, Paola Carnevali and Valeria Terzi

Foods 2020, 9(7), 911; https://doi.org/10.3390/foods9070911 - 10 Jul 2020

Cited by 17 | Viewed by 2562

Abstract

Pasta, the Italian product par excellence, is made of pure durum wheat. The use of Triticum durum derived semolina is in fact mandatory for Italian pasta, in which Triticum aestivum species is considered a contamination that must not exceed the 3% maximum level. [...] Read more.

Pasta, the Italian product par excellence, is made of pure durum wheat. The use of Triticum durum derived semolina is in fact mandatory for Italian pasta, in which Triticum aestivum species is considered a contamination that must not exceed the 3% maximum level. Over the last 50 years, various electrophoretic, chemical, and immuno-chemical methods have been proposed aimed to track the possible presence of common wheat in semolina and pasta. More recently, a new generation of methods, based on DNA (DeoxyriboNucleic Acid) analysis, has been developed to this aim. Species traceability can be now enforced by a new technology, namely digital Polymerase Chain Reaction (dPCR) which quantify the number of target sequence present in a sample, using limiting dilutions, PCR, and Poisson statistics. In our work we have developed a duplex chip digital PCR (cdPCR) assay able to quantify common wheat presence along pasta production chain, from raw materials to final products. The assay was verified on reference samples at known level of common wheat contamination and applied to commercial pastas sampled in the Italian market. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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12 pages, 1187 KiB

Open AccessArticle

Development and Validation of a Real-Time PCR Based Assay to Detect Adulteration with Corn in Commercial Turmeric Powder Products

by Su Hong Oh and Cheol Seong Jang

Foods 2020, 9(7), 882; https://doi.org/10.3390/foods9070882 - 05 Jul 2020

Cited by 18 | Viewed by 3344

Abstract

Turmeric, or Curcuma longa, is commonly consumed in the South East Asian countries as a medical product and as food due to its therapeutic properties. However, with increasing demand for turmeric powder, adulterated turmeric powders mixed with other cheap starch powders, such [...] Read more.

Turmeric, or Curcuma longa, is commonly consumed in the South East Asian countries as a medical product and as food due to its therapeutic properties. However, with increasing demand for turmeric powder, adulterated turmeric powders mixed with other cheap starch powders, such as from corn or cassava, are being distributed by food suppliers for economic benefit. Here, we developed molecular markers using quantitative real-time PCR to identify adulteration in commercial turmeric powder products. Chloroplast genes, such as matK, atpF, and ycf2, were used to design species-specific primers for C. longa and Zea mays. Of the six primer pairs designed and tested, the correlation coefficients (R²) were higher than 0.99 and slopes were −3.136 to −3.498. The efficiency of the primers was between 93.14 and 108.4%. The specificity of the primers was confirmed with ten other species, which could be intentionally added to C. longa powders or used as ingredients in complex turmeric foods. In total, 20 blind samples and 10 commercial C. longa food products were tested with the designed primer sets to demonstrate the effectiveness of this approach to detect the addition of Z. mays products in turmeric powders. Taken together, the real-time PCR assay developed here has the potential to contribute to food safety and the protection of consumer’s rights. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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11 pages, 695 KiB

Open AccessArticle

Flash Gas Chromatography in Tandem with Chemometrics: A Rapid Screening Tool for Quality Grades of Virgin Olive Oils

by Sara Barbieri, Chiara Cevoli, Alessandra Bendini, Beatriz Quintanilla-Casas, Diego Luis García-González and Tullia Gallina Toschi

Foods 2020, 9(7), 862; https://doi.org/10.3390/foods9070862 - 02 Jul 2020

Cited by 22 | Viewed by 2869

Abstract

This research aims to develop a classification model based on untargeted elaboration of volatile fraction fingerprints of virgin olive oils (n = 331) analyzed by flash gas chromatography to predict the commercial category of samples (extra virgin olive oil, EVOO; virgin olive [...] Read more.

This research aims to develop a classification model based on untargeted elaboration of volatile fraction fingerprints of virgin olive oils (n = 331) analyzed by flash gas chromatography to predict the commercial category of samples (extra virgin olive oil, EVOO; virgin olive oil, VOO; lampante olive oil, LOO). The raw data related to volatile profiles were considered as independent variables, while the quality grades provided by sensory assessment were defined as a reference parameter. This data matrix was elaborated using the linear technique partial least squares-discriminant analysis (PLS-DA), applying, in sequence, two sequential classification models with two categories (EVOO vs. no-EVOO followed by VOO vs. LOO and LOO vs. no-LOO followed by VOO vs. EVOO). The results from this large set of samples provide satisfactory percentages of correctly classified samples, ranging from 72% to 85%, in external validation. This confirms the reliability of this approach in rapid screening of quality grades and that it represents a valid solution for supporting sensory panels, increasing the efficiency of the controls, and also applicable to the industrial sector. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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8 pages, 1248 KiB

Open AccessArticle

Genetic Identification of the Wild Form of Olive (Olea europaea var. sylvestris) Using Allele-Specific Real-Time PCR

by Christina I. Kyriakopoulou and Despina P. Kalogianni

Foods 2020, 9(4), 467; https://doi.org/10.3390/foods9040467 - 09 Apr 2020

Cited by 9 | Viewed by 3179

Abstract

The wild-type of olive tree, Olea europaea var Sylvestris or oleaster, is the ancestor of the cultivated olive tree. Wild-type olive oil is considered to be more nutritious with increased antioxidant activity compared to the common cultivated type (Olea europaea L. var [...] Read more.

The wild-type of olive tree, Olea europaea var Sylvestris or oleaster, is the ancestor of the cultivated olive tree. Wild-type olive oil is considered to be more nutritious with increased antioxidant activity compared to the common cultivated type (Olea europaea L. var Europaea). This has led to the wild-type of olive oil having a much higher financial value. Thus, wild olive oil is one of the most susceptible agricultural food products to adulteration with other olive oils of lower nutritional and economical value. As cultivated and wild-type olives have similar phenotypes, there is a need to establish analytical methods to distinguish the two plant species. In this work, a new method has been developed which is able to distinguish Olea europaea var Sylvestris (wild-type olive) from Olea europaea L. var Europaea (cultivated olive). The method is based, for the first time, on the genotyping, by allele-specific, real-time PCR, of a single nucleotide polymorphism (SNP) present in the two olives’ chloroplastic genomes. With the proposed method, we were able to detect as little as 1% content of the wild-type olive in binary DNA mixtures of the two olive species. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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9 pages, 3682 KiB

Open AccessArticle

A Real-Time PCR Method for the Authentication of Common Cuttlefish (Sepia officinalis) in Food Products

by Amaya Velasco, Graciela Ramilo-Fernández and Carmen G. Sotelo

Foods 2020, 9(3), 286; https://doi.org/10.3390/foods9030286 - 04 Mar 2020

Cited by 16 | Viewed by 3862

Abstract

Cephalopods are very relevant food resources. The common cuttlefish (Sepia officinalis) is highly appreciated by consumers and there is a lack of rapid methods for its authentication in food products. We introduce a new minor groove binding (MGB) TaqMan real-time PCR [...] Read more.

Cephalopods are very relevant food resources. The common cuttlefish (Sepia officinalis) is highly appreciated by consumers and there is a lack of rapid methods for its authentication in food products. We introduce a new minor groove binding (MGB) TaqMan real-time PCR (Polymerase Chain Reaction) method for the authentication of S. officinalis in food products to amplify a 122 base pairs (bp) fragment of the mitochondrial COI (Cytochrome Oxidase I) region. Reference and commercial samples of S. officinalis showed a threshold cycle (Ct) mean of 14.40, while the rest of the species examined did not amplify, or showed a significantly different Ct (p < 0.001). The calculated efficiency of the system was 101%, and the minimum DNA quantity detected was 10⁻⁴ ng. No cross-reactivity was detected with any other species, thus, the designed method differentiates S. officinalis from other species of the genus Sepia and other cephalopod species and works for fresh, frozen, grilled, cooked and canned samples of Sepia spp. The method has proved to be reliable and rapid, and it may prove to be a useful tool for the control of fraud in cuttlefish products. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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9 pages, 971 KiB

Open AccessArticle

Using Chemometric Analyses for Tracing the Regional Origin of Multifloral Honeys of Montenegro

by Vesna Vukašinović-Pešić, Nada Blagojević, Snežana Brašanac-Vukanović, Ana Savić and Vladimir Pešić

Foods 2020, 9(2), 210; https://doi.org/10.3390/foods9020210 - 18 Feb 2020

Cited by 8 | Viewed by 2616

Abstract

This is the first study of mineral content and basic physicochemical parameters of honeys of Montenegro. We examined honey samples from eight different micro-regions of Montenegro, and the results confirm that, with the exception of cadmium in samples from two regions exposed to [...] Read more.

This is the first study of mineral content and basic physicochemical parameters of honeys of Montenegro. We examined honey samples from eight different micro-regions of Montenegro, and the results confirm that, with the exception of cadmium in samples from two regions exposed to industrial pollution, none of the 12 elements analyzed exceeded the maximum allowable level. The samples from areas exposed to industrial pollution were clearly distinguished from samples from other regions of Montenegro in the detectable contents of Pb, Cd, and Sr. This study showed that chemometric techniques might enhance the classification of Montenegrin honeys according to their micro-regional origin using the mineral content. Linear discriminant analysis revealed that the classification rate was 79.2% using the cross-validation method. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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8 pages, 500 KiB

Open AccessArticle

Development of a Real-Time PCR Assay for the Detection of Donkey (Equus asinus) Meat in Meat Mixtures Treated under Different Processing Conditions

by Mi-Ju Kim, Seung-Man Suh, Sung-Yeon Kim, Pei Qin, Hong-Rae Kim and Hae-Yeong Kim

Foods 2020, 9(2), 130; https://doi.org/10.3390/foods9020130 - 26 Jan 2020

Cited by 18 | Viewed by 3163

Abstract

In this study, a donkey-specific primer pair and probe were designed from mitochondrial cytochrome b gene for the detection of raw donkey meat and different processed meat mixtures. The PCR product size for donkey DNA was 99 bp, and primer specificity was verified [...] Read more.

In this study, a donkey-specific primer pair and probe were designed from mitochondrial cytochrome b gene for the detection of raw donkey meat and different processed meat mixtures. The PCR product size for donkey DNA was 99 bp, and primer specificity was verified using 20 animal species. The limit of detection (LOD) was examined by serially diluting donkey DNA. Using real-time PCR, 0.001 ng of donkey DNA could be detected. In addition, binary meat mixtures with various percentages of donkey meat (0.001%, 0.01%, 0.1%, 1%, 10%, and 100%) in beef were analyzed to determine the sensitivity of this real-time PCR assay. At least 0.001% of donkey meat was detected in raw, boiled, roasted, dried, grinded, fried, and autoclaved meat mixtures. The developed real-time PCR method showed sufficient specificity and sensitivity in identification of donkey meat and could be a useful tool for the identification of donkey meat in processed products. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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15 pages, 2719 KiB

Open AccessArticle

Swordfish or Shark Slice? A Rapid Response by COIBar–RFLP

by Venera Ferrito, Alessandra Raffa, Luana Rossitto, Concetta Federico, Salvatore Saccone and Anna Maria Pappalardo

Foods 2019, 8(11), 537; https://doi.org/10.3390/foods8110537 - 01 Nov 2019

Cited by 21 | Viewed by 6359

Abstract

Market transparency is in strong demand by consumers, and the authentication of species is an important step for seafood traceability. In this study, a simple molecular strategy, COIBar–RFLP (cytochrome oxidase I barcode–restriction fragment length polymorphism), is proposed to unveil commercial fraud based on [...] Read more.

Market transparency is in strong demand by consumers, and the authentication of species is an important step for seafood traceability. In this study, a simple molecular strategy, COIBar–RFLP (cytochrome oxidase I barcode–restriction fragment length polymorphism), is proposed to unveil commercial fraud based on the practice of species substitution in the swordfish trade. In particular, COI barcoding allowed the identification of the species Prionace glauca, Mustelus mustelus, and Oxynotus centrina in slices labeled as Xiphias gladius. Furthermore, the enzymatic digestion of COI amplicons using the MboI restriction endonuclease allowed the simultaneous discrimination of the four species. Interestingly, an intraspecific differential MboI pattern was obtained for the swordfish samples. This pattern was useful to differentiate the two different clades revealed in this species by phylogenetic analyses using several molecular markers. These results indicate the need to strengthen regulations and define molecular tools for combating the occurrence of fraud along the seafood supply chain and show that COIBar–RFLP could become a standardized molecular tool to assess seafood authenticity. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

by Abdo Hassoun, Ingrid Måge, Walter F. Schmidt, Havva Tümay Temiz, Li Li, Hae-Yeong Kim, Heidi Nilsen, Alessandra Biancolillo, Abderrahmane Aït-Kaddour, Marek Sikorski, Ewa Sikorska, Silvia Grassi and Daniel Cozzolino

Foods 2020, 9(8), 1069; https://doi.org/10.3390/foods9081069 - 06 Aug 2020

Cited by 82 | Viewed by 12424

Abstract

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks [...] Read more.

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed. Full article

(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)

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