Implementation of Chemometrics and Other Techniques as Means of Authenticity and Traceability to Detect Adulteration in Foods for the Protection of Human Health

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

Deadline for manuscript submissions: closed (10 September 2022) | Viewed by 31701

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Special Issue Editor

Department of Food Science and Technology, University of Peloponnese, 24100 Antikalamos, Greece
Interests: food technology; food engineering; food safety; food quality; extra virgin olive oil; mycotoxins; fermented foods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Authenticity and traceability are crucial in order to overcome frauds in the international food trade.

Classification of foods such as olive oils according to their variety and /or geographical origin is of great importance for producers, importers, and consumers. Toward this target of food classification, different multivariate statistical procedures are employed, such as cluster analysis, factor analysis, multidimensional scaling, discriminant analysis, correspondence analysis, canonical analysis, and Procrustes analysis.

Recently, artificial intelligence has also been applied to solve food characterization problems.

Different analytical approaches have been employed for the adulteration of foods such as gas chromatography–mass spectrometry (GC/MS), compound-specific isotope analysis (CSIA), isotope ratio mass spectrometry (IRMS), NMR spectroscopy, Fourier transform mid-infrared (FTIR), near-infrared (FT-NIR), and Raman (FT-Raman) spectroscopy.

Moreover, chemometric methods have been used to process experimental data, such as linear discriminant analysis (LDA) and artificial neural networks (ANN).

Finally, stable isotope ratio analysis (SIRA) offers one of the most promising tools for establishing the authenticity of premium products.

The aim of this Special Issue is to bring advances in the area of authentication of foods of plant and animal origin to prevent adulteration for the protection of consumers’ health.

Control measures are perceived as the greatest vulnerability in the food supply chain. In order to decrease contribution to the overall perceived fraud vulnerability, the fraud factors that should be taken into account to control food security are the following: technical opportunities, managerial controls, technical controls, economic drivers, cultural and behavioral drivers, and opportunities in time and place.

Prof. Dr. Theodoros Varzakas
Guest Editor

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Keywords

  • foods
  • security
  • quality
  • safety
  • authenticity
  • traceability
  • adulteration
  • chemometrics
  • multivariate statistics
  • GC/MS
  • IRMS
  • NMR
  • FTIR
  • Raman spectroscopy
  • nutrition
  • health
  • fraud vulnerability
  • control measures

Published Papers (12 papers)

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Editorial

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3 pages, 182 KiB  
Editorial
Implementation of Chemometrics and Other Techniques as Means of Authenticity and Traceability to Detect Adulteration in Foods for the Protection of Human Health
by Theodoros Varzakas
Foods 2023, 12(3), 652; https://doi.org/10.3390/foods12030652 - 02 Feb 2023
Cited by 1 | Viewed by 1099
Abstract
The authenticity of foods of plant and animal origin is key to safeguarding both quality and safety aspects without jeopardizing consumers’ health [...] Full article

Research

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10 pages, 2494 KiB  
Article
Investigating the Tocopherol Contents of Walnut Seed Oils Produced in Different European Countries Analyzed by HPLC-UV: A Comparative Study on the Basis of Geographical Origin
by Petros D. Mitsikaris, Lambros Kokokiris, Agathi Pritsa, Athanasios N. Papadopoulos and Natasa P. Kalogiouri
Foods 2022, 11(22), 3719; https://doi.org/10.3390/foods11223719 - 19 Nov 2022
Cited by 4 | Viewed by 2022
Abstract
A rapid HPLC-UV method was developed for the determination of tocopherols in walnut seed oils. The method was validated and the LODs ranged between 0.15 and 0.30 mg/kg, while the LOQs were calculated over the range of 0.50 to 1.00 mg/kg. The accuracy [...] Read more.
A rapid HPLC-UV method was developed for the determination of tocopherols in walnut seed oils. The method was validated and the LODs ranged between 0.15 and 0.30 mg/kg, while the LOQs were calculated over the range of 0.50 to 1.00 mg/kg. The accuracy values ranged between 90.8 and 97.1% for the within-day assay (n = 6) and between 90.4 and 95.8% for the between-day assay (n = 3 × 3), respectively. The precision of the method was evaluated and the RSD% values were lower than 6.1 and 8.2, respectively. Overall, 40 samples of walnuts available on the Greek market, originating from four different European countries (Greece, Ukraine, France, and Bulgaria), were processed into oils and analyzed. One-way ANOVA was implemented in order to investigate potential statistically significant disparities between the concentrations of tocopherols in the walnut oils on the basis of the geographical origin, and Tukey’s post hoc test was also performed to examine exactly which varieties differed. The statistical analysis of the results demonstrated that the Ukrainian walnut seed oils exhibited significantly higher total concentrations compared to the rest of the samples. Full article
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16 pages, 1748 KiB  
Article
Proposing Two Local Modeling Approaches for Discriminating PGI Sunite Lamb from Other Origins Using Stable Isotopes and Machine Learning
by Ruting Zhao, Xiaoxia Liu, Jishi Wang, Yanyun Wang, Ai-Liang Chen, Yan Zhao and Shuming Yang
Foods 2022, 11(6), 846; https://doi.org/10.3390/foods11060846 - 16 Mar 2022
Cited by 3 | Viewed by 1631
Abstract
For the protection of Protected Geographical Indication (PGI) Sunite lamb, PGI Sunite lamb samples and lamb samples from two other banners in the Inner Mongolia autonomous region were distinguished by stable isotopes (δ13C, δ15N, δ2H, and δ [...] Read more.
For the protection of Protected Geographical Indication (PGI) Sunite lamb, PGI Sunite lamb samples and lamb samples from two other banners in the Inner Mongolia autonomous region were distinguished by stable isotopes (δ13C, δ15N, δ2H, and δ18O) and two local modeling approaches. In terms of the main characteristics and predictive performance, local modeling was better than global modeling. The accuracies of five local models (LDA, RF, SVM, BPNN, and KNN) obtained by the Adaptive Kennard–Stone algorithm were 91.30%, 95.65%, 91.30%, 100%, and 91.30%, respectively. The accuracies of the five local models obtained by an approach of PCA–Full distance based on DD–SIMCA were 91.30%, 91.30%, 91.30%, 100%, and 95.65%, respectively. The accuracies of the five global models were 91.30%, 91.30%, 91.30%, 100%, and 91.30%, respectively. Stable isotope ratio analysis combined with local modeling can be used as an effective indicator for protecting PGI Sunite lamb. Full article
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12 pages, 758 KiB  
Article
Discrimination of Four Cinnamomum Species with Physico-Functional Properties and Chemometric Techniques: Application of PCA and MDA Models
by Priya Rana, Shu-Yi Liaw, Meng-Shiou Lee and Shyang-Chwen Sheu
Foods 2021, 10(11), 2871; https://doi.org/10.3390/foods10112871 - 19 Nov 2021
Cited by 7 | Viewed by 1811
Abstract
Discrimination of highly valued and non-hepatotoxic Cinnamomum species (C. verum) from hepatotoxic (C. burmannii, C. loureiroi, and C. cassia) is essential for preventing food adulteration and safety problems. In this study, we developed a [...] Read more.
Discrimination of highly valued and non-hepatotoxic Cinnamomum species (C. verum) from hepatotoxic (C. burmannii, C. loureiroi, and C. cassia) is essential for preventing food adulteration and safety problems. In this study, we developed a new method for the discrimination of four Cinnamomum species using physico-functional properties and chemometric techniques. The data were analyzed through principal component analysis (PCA) and multiclass discriminant analysis (MDA). The results showed that the cumulative variability of the first three principal components was 81.70%. The PCA score plot indicated a clear separation of the different Cinnamomum species. The training set was used to build the discriminant MDA model. The testing set was verified by this model. The prediction rate of 100% proved that the model was valid and reliable. Therefore, physico-functional properties coupled with chemometric techniques constitute a practical approach for discrimination of Cinnamomum species to prevent food fraud. Full article
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13 pages, 2102 KiB  
Article
Multivariate Analysis Coupled with M-SVM Classification for Lard Adulteration Detection in Meat Mixtures of Beef, Lamb, and Chicken Using FTIR Spectroscopy
by Muhammad Aadil Siddiqui, Mohd Haris Md Khir, Gunawan Witjaksono, Ali Shaan Manzoor Ghumman, Muhammad Junaid, Saeed Ahmed Magsi and Abdul Saboor
Foods 2021, 10(10), 2405; https://doi.org/10.3390/foods10102405 - 11 Oct 2021
Cited by 13 | Viewed by 2471
Abstract
Adulteration of meat products is a delicate issue for people around the globe. The mixing of lard in meat causes a significant problem for end users who are sensitive to halal meat consumption. Due to the highly similar lipid profiles of meat species, [...] Read more.
Adulteration of meat products is a delicate issue for people around the globe. The mixing of lard in meat causes a significant problem for end users who are sensitive to halal meat consumption. Due to the highly similar lipid profiles of meat species, the identification of adulteration becomes more difficult. Therefore, a comprehensive spectral detailing of meat species is required, which can boost the adulteration detection process. The experiment was conducted by distributing samples labeled as “Pure (80 samples)” and “Adulterated (90 samples)”. Lard was mixed with the ratio of 10–50% v/v with beef, lamb, and chicken samples to obtain adulterated samples. Functional groups were discovered for pure pork, and two regions of difference (RoD) at wavenumbers 1700–1800 cm−1 and 2800–3000 cm−1 were identified using absorbance values from the FTIR spectrum for all samples. The principal component analysis (PCA) described the studied adulteration using three principal components with an explained variance of 97.31%. The multiclass support vector machine (M-SVM) was trained to identify the sample class values as pure and adulterated clusters. The acquired overall classification accuracy for a cluster of pure samples was 81.25%, whereas when the adulteration ratio was above 10%, 71.21% overall accuracy was achieved for a group of adulterated samples. Beef and lamb samples for both adulterated and pure classes had the highest classification accuracy value of 85%, whereas chicken had the lowest value of 78% for each category. This paper introduces a comprehensive spectrum analysis for pure and adulterated samples of beef, chicken, lamb, and lard. Moreover, we present a rapid M-SVM model for an accurate classification of lard adulteration in different samples despite its low-level presence. Full article
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10 pages, 2705 KiB  
Article
Detecting Dye-Contaminated Vegetables Using Low-Field NMR Relaxometry
by Sumaiya Shomaji, Naren Vikram Raj Masna, David Ariando, Shubhra Deb Paul, Kelsey Horace-Herron, Domenic Forte, Soumyajit Mandal and Swarup Bhunia
Foods 2021, 10(9), 2232; https://doi.org/10.3390/foods10092232 - 21 Sep 2021
Cited by 9 | Viewed by 4018
Abstract
Dyeing vegetables with harmful compounds has become an alarming public health issue over the past few years. Excessive consumption of these dyed vegetables can cause severe health hazards, including cancer. Copper sulfate, malachite green, and Sudan red are some of the non-food-grade dyes [...] Read more.
Dyeing vegetables with harmful compounds has become an alarming public health issue over the past few years. Excessive consumption of these dyed vegetables can cause severe health hazards, including cancer. Copper sulfate, malachite green, and Sudan red are some of the non-food-grade dyes widely used on vegetables by untrusted entities in the food supply chain to make them look fresh and vibrant. In this study, the presence and quantity of dye-based adulteration in vegetables are determined by applying 1H-nuclear magnetic resonance (NMR) relaxometry. The proposed technique was validated by treating some vegetables in-house with different dyes and then soaking them in various solvents. The resulting solutions were collected and analyzed using NMR relaxometry. Specifically, the effective transverse relaxation time constant, T2,eff, of each solution was estimated using a Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence. Finally, the estimated time constants (i.e., measured signatures) were compared with a library of existing T2,eff data to detect and quantify the presence of unwanted dyes. The latter consists of data-driven models of transverse decay times for various concentrations of each water-soluble dye. The time required to analyze each sample using the proposed approach is dye-dependent but typically no longer than a few minutes. The analysis results can be used to generate warning flags if the detected dye concentrations violate widely accepted standards for food dyes. The proposed low-cost detection approach can be used in various stages of a produce supply chain, including consumer household. Full article
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16 pages, 2980 KiB  
Article
Authentication and Chemometric Discrimination of Six Greek PDO Table Olive Varieties through Morphological Characteristics of Their Stones
by Sofia Agriopoulou, Maria Tarapoulouzi, Marie Ampères Bedine Boat, Catherine Rébufa, Nathalie Dupuy, Charis R. Theocharis, Theodoros Varzakas, Sevastianos Roussos and Jacques Artaud
Foods 2021, 10(8), 1829; https://doi.org/10.3390/foods10081829 - 07 Aug 2021
Cited by 8 | Viewed by 3038
Abstract
Table olives, the number one consumed fermented food in Europe, are widely consumed as they contain many valuable ingredients for health. It is also a food which may be the subject of adulteration, as many different olive varieties with different geographical origin, exist [...] Read more.
Table olives, the number one consumed fermented food in Europe, are widely consumed as they contain many valuable ingredients for health. It is also a food which may be the subject of adulteration, as many different olive varieties with different geographical origin, exist all over the word. In the present study, the image analysis of stones of six main Greek protected designation of origin (PDO) table olive varieties was performed for the control of their authentication and discrimination, with cv. Prasines Chalkidikis, cv. Kalamata Olive, cv. Konservolia Stylidas, cv. Konservolia Amfissis, cv. Throuba Thassos and cv. Throuba Chios being the studied olive varieties. Orthogonal partial least square discriminant analysis (OPLS-DA) was used for discrimination and classification of the six Greek table olive varieties. With a 98.33% of varietal discrimination, the OPLS-DA model proved to be an efficient tool to authentify table olive varieties from their morphological characteristics. Full article
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13 pages, 3980 KiB  
Article
Chemical Analysis Combined with Multivariate Statistical Methods to Determine the Geographical Origin of Milk from Four Regions in China
by Ruting Zhao, Meicheng Su, Yan Zhao, Gang Chen, Ailiang Chen and Shuming Yang
Foods 2021, 10(5), 1119; https://doi.org/10.3390/foods10051119 - 18 May 2021
Cited by 6 | Viewed by 2028
Abstract
Traceability of milk origin in China is conducive to the implementation of the protection of regional products. In order to distinguish milk from different geographical distances in China, we traced the milk of eight farms in four neighboring provinces of China (Inner Mongolia [...] Read more.
Traceability of milk origin in China is conducive to the implementation of the protection of regional products. In order to distinguish milk from different geographical distances in China, we traced the milk of eight farms in four neighboring provinces of China (Inner Mongolia autonomous region, Hebei, Ningxia Hui autonomous and Shaanxi), and multivariate data analysis was applied to the data including elemental analysis, stable isotope analysis and fatty acid analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) is used to determine the optimal classification model, and it is explored whether the combination of different technologies is better than a single technical analysis. It was confirmed that in the inter-provincial samples, the combination of the two techniques was better than the analysis using a single technique (fatty acids: R2 = 0.716, Q2 = 0.614; fatty acid-binding isotopes: R2 = 0.760, Q2 = 0.635). At the same time, milk produced by farms with different distances of less than 11 km in each province was discriminated, and the discriminant distance was successfully reduced to 0.7 km (Ningxia Hui Autonomous Region: the distance between the two farms was 0.7 km, R2 = 0.771, Q2 = 0.631). For short-distance samples, the combination multiple technologies are not completely superior to a single technique, and sometimes, it is easy to cause model over-fitting. Full article
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13 pages, 2747 KiB  
Article
Chemometric Discrimination of the Geographical Origin of Three Greek Cultivars of Olive Oils by Stable Isotope Ratio Analysis
by Maria Tarapoulouzi, Vasiliki Skiada, Sofia Agriopoulou, David Psomiadis, Catherine Rébufa, Sevastianos Roussos, Charis R. Theocharis, Panagiotis Katsaris and Theodoros Varzakas
Foods 2021, 10(2), 336; https://doi.org/10.3390/foods10020336 - 04 Feb 2021
Cited by 17 | Viewed by 2639
Abstract
Α stable isotope ratio mass spectrometer was used for stable isotope ratio (i.e., δ13C, δ18O, and δ2H) measurements, achieving geographical discrimination using orthogonal projections to latent structures discriminant analysis. A total of 100 Greek monovarietal olive oil [...] Read more.
Α stable isotope ratio mass spectrometer was used for stable isotope ratio (i.e., δ13C, δ18O, and δ2H) measurements, achieving geographical discrimination using orthogonal projections to latent structures discriminant analysis. A total of 100 Greek monovarietal olive oil samples from three different olive cultivars (cv. Koroneiki, cv. Lianolia Kerkyras, and cv. Maurolia), derived from Central Greece and Peloponnese, were collected during the 2019–2020 harvest year aiming to investigate the effect of botanical and geographical origin on their discrimination through isotopic data. The selection of these samples was made from traditionally olive-growing areas in which no significant research has been done so far. Samples were discriminated mainly by olive cultivar and, partially, by geographical origin, which is congruent with other authors. Based on this model, correct recognition of 93.75% in the training samples and correct prediction of 100% in the test set were achieved. The overall correct classification of the model was 91%. The predictability based on the externally validated method of discrimination was good (Q2 (cum) = 0.681) and illustrated that δ18O and δ2H were the most important isotope markers for the discrimination of olive oil samples. The authenticity of olive oil based on the examined olive varieties can be determined using this technique. Full article
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Review

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41 pages, 2586 KiB  
Review
Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage
by Maria Tarapoulouzi, Monica Mironescu, Chryssoula Drouza, Ion Dan Mironescu and Sofia Agriopoulou
Foods 2023, 12(3), 473; https://doi.org/10.3390/foods12030473 - 19 Jan 2023
Cited by 6 | Viewed by 3039
Abstract
The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually [...] Read more.
The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing. Full article
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28 pages, 1381 KiB  
Review
How Chemometrics Can Fight Milk Adulteration
by Silvia Grassi, Maria Tarapoulouzi, Alessandro D’Alessandro, Sofia Agriopoulou, Lorenzo Strani and Theodoros Varzakas
Foods 2023, 12(1), 139; https://doi.org/10.3390/foods12010139 - 27 Dec 2022
Cited by 10 | Viewed by 3090
Abstract
Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as [...] Read more.
Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as the origin of the food products, and investment in these technologies is highly critical. In this context, chemometric techniques proved to be very efficient in detecting and even quantifying the number of substances used as adulterants. The extraction of relevant information from different kinds of data is a crucial feature to achieve this aim. However, these techniques are not always used properly. In fact, training is important along with investment in these technologies in order to cope effectively and not only reduce fraud but also advertise the geographical origin of the various food and drink products. The aim of this paper is to present an overview of the different chemometric techniques (from clustering to classification and regression applied to several analytical data) along with spectroscopy, chromatography, electrochemical sensors, and other on-site detection devices in the battle against milk adulteration. Moreover, the steps which should be followed to develop a chemometric model to face adulteration issues are carefully presented with the required critical discussion. Full article
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27 pages, 646 KiB  
Review
Detection of Saffron’s Main Bioactive Compounds and Their Relationship with Commercial Quality
by Raul Avila-Sosa, Guadalupe Virginia Nevárez-Moorillón, Carlos Enrique Ochoa-Velasco, Addí Rhode Navarro-Cruz, Paola Hernández-Carranza and Teresa Soledad Cid-Pérez
Foods 2022, 11(20), 3245; https://doi.org/10.3390/foods11203245 - 18 Oct 2022
Cited by 14 | Viewed by 2886
Abstract
This review aims to evaluate the state of saffron’s main bioactive compounds and their relationship with its commercial quality. Saffron is the commercial name for the dried red stigmas of the Crocus sativus L. flower. It owes its sensory and functional properties mainly [...] Read more.
This review aims to evaluate the state of saffron’s main bioactive compounds and their relationship with its commercial quality. Saffron is the commercial name for the dried red stigmas of the Crocus sativus L. flower. It owes its sensory and functional properties mainly to the presence of its carotenoid derivatives, synthesized throughout flowering and also during the whole production process. These compounds include crocin, crocetin, picrocrocin, and safranal, which are bioactive metabolites. Saffron’s commercial value is determined according to the ISO/TS3632 standard that determines their main apocatotenoids. Other techniques such as chromatography (gas and liquid) are used to detect the apocarotenoids. This, together with the determination of spectral fingerprinting or chemo typing are essential for saffron identification. The determination of the specific chemical markers coupled with chemometric methods favors the discrimination of adulterated samples, possible plants, or adulterating compounds and even the concentrations at which these are obtained. Chemical characterization and concentration of various compounds could be affected by saffron’s geographical origin and harvest/postharvest characteristics. The large number of chemical compounds found in the by-products (flower parts) of saffron (catechin, quercetin, delphinidin, etc.) make it an interesting aromatic spice as a colorant, antioxidant, and source of phytochemicals, which can also bring additional economic value to the most expensive aromatic species in the world. Full article
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