1
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Aslam N, Fatima R, Altemimi AB, Ahmad T, Khalid S, Hassan SA, Aadil RM. Overview of industrial food fraud and authentication through chromatography technique and its impact on public health. Food Chem 2024; 460:140542. [PMID: 39079380 DOI: 10.1016/j.foodchem.2024.140542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/09/2024] [Accepted: 07/18/2024] [Indexed: 09/05/2024]
Abstract
Food fraud is widespread nowadays in the food products supply chain, from raw materials processing to the final product and during storage and transport. The most frequent fraud is practiced in staple food commodities like cereals. Their origin, variety, genotype, and bioactive compounds are altered to deceive consumers. Similarly, in various food sectors like beverage, baking, and confectionary, items like melamine, flour improver, and food colors are used in the market to temple consumers. To tackle food fraud and authentication, non-destructive techniques are being used. These techniques have limitations like lack of standardization, interference from multiple absorbing species, ambiguous results, and time-consuming to perform, depending on the type, size, and location of the system proved difficult to quantify the samples of adulteration. Chromatography has been introduced as an effective technique. It serves to safeguard public health due to its detection capabilities. Chromatography proved a crucial tool against fraudulent practices to preserve consumer trust.
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Affiliation(s)
- Nabila Aslam
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan
| | - Rida Fatima
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan
| | - Ammar B Altemimi
- Food Science Department, College of Agriculture, University of Basrah, Basrah 61004, Iraq
| | - Talha Ahmad
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan
| | - Samran Khalid
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan
| | - Syed Ali Hassan
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan
| | - Rana Muhammad Aadil
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan.
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2
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Ferreira MM, Marins-Gonçalves L, De Souza D. An integrative review of analytical techniques used in food authentication: A detailed description for milk and dairy products. Food Chem 2024; 457:140206. [PMID: 38936134 DOI: 10.1016/j.foodchem.2024.140206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/04/2024] [Accepted: 06/22/2024] [Indexed: 06/29/2024]
Abstract
The use of suitable analytical techniques for the detection of adulteration, falsification, deliberate substitution, and mislabeling of foods has great importance in the industrial, scientific, legislative, and public health contexts. This way, this work reports an integrative review with a current analytical approach for food authentication, indicating the main analytical techniques to identify adulteration and perform the traceability of chemical components in processed and non-processed foods, evaluating the authenticity and geographic origin. This work presents results from a systematic search in Science Direct® and Scopus® databases using the keywords "authentication" AND "food", "authentication," AND "beverage", from published papers from 2013 to, 2024. All research and reviews published were employed in the bibliometric analysis, evaluating the advantages and disadvantages of analytical techniques, indicating the perspectives for direct, quick, and simple analysis, guaranteeing the application of quality standards, and ensuring food safety for consumers. Furthermore, this work reports the analysis of natural foods to evaluate the origin (traceability), and industrialized foods to detect adulterations and fraud. A focus on research to detect adulteration in milk and dairy products is presented due to the importance of these products in the nutrition of the world population. All analytical tools discussed have advantages and drawbacks, including sample preparation steps, the need for reference materials, and mathematical treatments. So, the main advances in modern analytical techniques for the identification and quantification of food adulterations, mainly milk and dairy products, were discussed, indicating trends and perspectives on food authentication.
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Affiliation(s)
- Mariana Martins Ferreira
- Laboratory of Electroanalytical Applied to Biotechnology and Food Engineering (LEABE), Chemistry Institute, Uberlândia Federal University, Major Jerônimo Street, 566, Patos de Minas, MG, 38700-002, Brazil
| | - Lorranne Marins-Gonçalves
- Laboratory of Electroanalytical of Food and Environmental Contaminants (LECAA), Chemistry Institute, Uberlândia Federal University, João Naves de Ávila Street, 2121, 1D block, Santa Mônica, Uberlândia, MG, 38400-902, Brazil
| | - Djenaine De Souza
- Laboratory of Electroanalytical of Food and Environmental Contaminants (LECAA), Chemistry Institute, Uberlândia Federal University, João Naves de Ávila Street, 2121, 1D block, Santa Mônica, Uberlândia, MG, 38400-902, Brazil..
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3
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Vinothkanna A, Dar OI, Liu Z, Jia AQ. Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents. Food Chem 2024; 446:138893. [PMID: 38432137 DOI: 10.1016/j.foodchem.2024.138893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Revised: 02/15/2024] [Accepted: 02/26/2024] [Indexed: 03/05/2024]
Abstract
Modern food chain supply management necessitates the dire need for mitigating food fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent and systematic review analyses (2018-2023) revealed both destructive and non-destructive methods to demarcate a rational approach for food fraud detection in various countries. These intricate hygiene standards and AI-based technology are also summarized for further prospective research. Chemometrics or AI-based techniques for extensive food fraud detection are demanded. A systematic assessment reveals that various methods to detect food fraud involving multiple substances need to be simple, expeditious, precise, cost-effective, eco-friendly and non-intrusive. The scrutiny resulted in 39 relevant experimental data sets answering key questions. However, additional research is necessitated for an affirmative conclusion in food fraud detection system with modern AI and machine learning approaches.
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Affiliation(s)
- Annadurai Vinothkanna
- School of Life and Health Sciences, Hainan University, Haikou 570228, China; Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570311, China.
| | - Owias Iqbal Dar
- School of Chemistry and Chemical Engineering, Hainan University, Haikou 570228, China
| | - Zhu Liu
- School of Life and Health Sciences, Hainan University, Haikou 570228, China.
| | - Ai-Qun Jia
- Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570311, China.
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4
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Wen H, Yang T, Yang W, Yang M, Wang Y, Zhang J. Comparison of Metabolites and Species Classification of Thirteen Zingiberaceae Spices Based on GC-MS and Multi-Spectral Fusion Technology. Foods 2023; 12:3714. [PMID: 37893607 PMCID: PMC10606731 DOI: 10.3390/foods12203714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 09/28/2023] [Accepted: 09/30/2023] [Indexed: 10/29/2023] Open
Abstract
Due to a similar plant morphology in the majority of Zingiberaceae spices, substitution and adulteration frequently take place during the sales process. Therefore, it is important to analyze the metabolites and species classification of different Zingiberaceae spices. This study preliminarily explored the differences in the metabolites in thirteen Zingiberaceae spices through untargeted gas chromatography-mass spectrometry (GC-MS) and combined spectroscopy, establishing models for classifying different Zingiberaceae spices. On one hand, a total of 81 metabolites were successfully identified by GC-MS. Thirty-seven differential metabolites were screened using variable important in projection (VIP ≥ 1). However, the orthogonal partial least squares discriminant analysis (OPLS-DA) model established using GC-MS data only explained about 30% of the variation. On the other hand, the partial least squares discriminant analysis (PLS-DA) models with three spectral data fusion strategies were compared, and their classification accuracy reached 100%. Among them, the mid-level data fusion model based on latent variables had the best performance. This study provides a powerful tool for distinguishing different Zingiberaceae spices and assists in reducing the occurrence of substitution and adulteration phenomena.
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Affiliation(s)
- Hui Wen
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650200, China; (H.W.); (T.Y.); (W.Y.); (M.Y.); (Y.W.)
- School of Agriculture, Yunnan University, Kunming 650504, China
| | - Tianmei Yang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650200, China; (H.W.); (T.Y.); (W.Y.); (M.Y.); (Y.W.)
| | - Weize Yang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650200, China; (H.W.); (T.Y.); (W.Y.); (M.Y.); (Y.W.)
| | - Meiquan Yang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650200, China; (H.W.); (T.Y.); (W.Y.); (M.Y.); (Y.W.)
| | - Yuanzhong Wang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650200, China; (H.W.); (T.Y.); (W.Y.); (M.Y.); (Y.W.)
| | - Jinyu Zhang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650200, China; (H.W.); (T.Y.); (W.Y.); (M.Y.); (Y.W.)
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5
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Bagnulo E, Scavarda C, Bortolini C, Cordero C, Bicchi C, Liberto E. Cocoa quality: Chemical relationship of cocoa beans and liquors in origin identitation. Food Res Int 2023; 172:113199. [PMID: 37689847 DOI: 10.1016/j.foodres.2023.113199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/23/2023] [Accepted: 06/27/2023] [Indexed: 09/11/2023]
Abstract
In this study, HS-SPME-GC-MS was applied in combination with machine learning tools to the identitation of a set of cocoa samples of different origins. Untargeted fingerprinting and profiling approaches were tested for their informative, discriminative and classification ability provided by the volatilome of the raw beans and liquors inbound at the factory in search of robust tools exploitable for long-time studies. The ability to distinguish the country of origin on both beans and liquors is not so obvious due to processing steps accompanying the transformation of the beans, but this capacity is of particular interest to the chocolate industry as both beans and liquors can enter indifferently into the processing of chocolate. Both fingerprinting (untargeted) and profiling (targeted) strategies enable to decipher of the information contained in the complex dataset and the cross-validation of the results, affording to discriminate between the origins with effective classification models.
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Affiliation(s)
- Eloisa Bagnulo
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy
| | - Camilla Scavarda
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy
| | - Cristian Bortolini
- Soremartec Italia S.r.l. (Ferrero Group), P.le P. Ferrero 1, 12051 Alba, CN, Italy
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy
| | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy
| | - Erica Liberto
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy.
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Soon-Sinclair JM, Imathiu S, Obadina AO, Dongho Dongmo FF, Kamgain ADT, Moholisa E, Saba CKS, Walekhwa AW, Hunga H, Kussaga J. How Worried Are You about Food Fraud? A Preliminary Multi-Country Study among Consumers in Selected Sub-Saharan African Countries. Foods 2023; 12:3627. [PMID: 37835280 PMCID: PMC10572961 DOI: 10.3390/foods12193627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/18/2023] [Accepted: 09/28/2023] [Indexed: 10/15/2023] Open
Abstract
Food fraud is an old, recurring, and global threat to public health. It poses a serious threat to food security in sub-Saharan Africa (SSA). Despite the prevalence of food fraud in SSA, little is known about how food fraud is viewed by consumers. This study aims to provide an overview of consumers' concerns about food fraud in SSA. A multi-country survey was conducted in October 2022-31 January 2023, and 838 valid responses were returned. To reduce the large and correlated dataset, Principal Component Analysis (PCA) was used. Five components were derived from PCA: (i) Staple foods; (ii) Premium food and drink products; (iii) Trust in reliable sources; (iv) Trust in less reliable sources; and (v) Trust in food vendors. The findings revealed Ghanaian (mean rank = 509.47) and Nigerian (mean rank = 454.82) consumers tended to score higher on the measure of food fraud concern suggesting that they were less confident in the safety and quality of the food they consume. Demographic characteristics including age, number of children, personal and family experience of food fraud and PCA components such as 'Staple foods', 'Trust in reliable sources', and 'Trust in food vendors' significantly predicted the model. This is the first preliminary study to provide empirical findings on consumers' concerns about food fraud in SSA. Practical and policy recommendations for the region are suggested. This includes (i) modelling the AfriFoodinTegrity in West Africa across other major regions such as Central, East, and Southern Africa; (ii) establish a regional sub-Saharan Africa Rapid Alert System for Food and Feed (SSA-RASFF) platform; and (iii) food safety and food fraud reports could be incorporated into SSA-RASFF portal for information sharing.
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Affiliation(s)
- Jan Mei Soon-Sinclair
- Faculty of Allied-Health and Wellbeing, University of Central Lancashire, Preston PRI 2HE, UK
| | - Samuel Imathiu
- Department of Food Science and Technology, Jomo Kenyatta University of Agriculture and Technology, Nairobi 00200, Kenya;
| | - Adewale Olusegun Obadina
- Department of Food Science and Technology, Federal University of Agriculture, Abeokuta P.M.B 2240, Nigeria;
- Department of Biotechnology and Food Technology, University of Johannesburg, Johannesburg 2092, South Africa
| | | | - Alex Dimitri Tchuenchieu Kamgain
- Institute of Medical Research and Medicinal Plants Studies, Yaoundé 13033, Cameroon;
- Food Evolution Research Laboratory, School of Tourism and Hospitality, University of Johannesburg, Johannesburg 2092, South Africa
| | - Ennet Moholisa
- Agricultural Research Council-Animal Production Institute, Irene 0062, South Africa;
| | - Courage Kosi Setsoafia Saba
- Department of Microbiology, Faculty of Biosciences, University for Development Studies, Tamale P.O. Box TL 1882, Ghana;
| | - Abel Wilson Walekhwa
- Infectious Diseases Epidemiology and Modelling Unit, Makerere University, Kampala P.O. Box 22418, Uganda;
| | - Henry Hunga
- Department of Land Resources Conservation, Ministry of Agriculture, Lilongwe P.O. Box 30291, Malawi;
| | - Jamal Kussaga
- Department of Food Science and Agroprocessing, School of Engineering and Technology, College of Agriculture, Sokoine University of Agriculture, Morogoro P.O. Box 3000, Tanzania;
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7
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Qi F, Liu X, Deng Z, Lu Y, Chen Y, Geng H, Zhang Q, Rao Q, Song W. Effects of Thiamethoxam and Fenvalerate Residue Levels on Light-Stable Isotopes of Leafy Vegetables. Foods 2023; 12:2655. [PMID: 37509747 PMCID: PMC10378639 DOI: 10.3390/foods12142655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/04/2023] [Accepted: 07/06/2023] [Indexed: 07/30/2023] Open
Abstract
Accurate identification of the rational and standardized use of pesticides is important for the sustainable development of agriculture while maintaining a high quality. The insecticides thiamethoxam and fenvalerate and the vegetables spinach, cabbage, and lettuce were used here as study objects. Descriptive analysis and primary reaction kinetic equations were used to analyze the changes in metabolic residues of the two insecticides after different numbers of application in three vegetables. The effects of pesticide residue levels on the δ13C, δ15N, δ2H, and δ18O values of vegetables were analyzed by one-way analysis of variance and correlation analysis. Partial least squares discriminant analysis (PLS-DA) was applied to build discrimination models of the vegetables with different pesticide residues based on stable isotopes. The results showed that the first degradation residues of thiamethoxam and fenvalerate in spinach, cabbage, and lettuce conformed to primary reaction kinetic equations, but the degradation half-lives were long, and accumulation occurred in the second application. The differences in the four stable isotope ratios in the control group of the three vegetables were statistically significant, and two-thirds of the stable isotope ratios in the three vegetables with different numbers of pesticide applications were significantly different. The δ13C and δ15N values of spinach, the δ13C, δ15N, and δ2H values of cabbage, and the δ13C, δ15N, δ2H, and δ18O values of lettuce were significantly correlated with different residues of thiamethoxam and/or fenvalerate applications. The control groups of the three vegetables, spinach-thiamethoxam-first, spinach-thiamethoxam-second, cabbage-thiamethoxam-second, cabbage-fenvalerate-first, and lettuce-thiamethoxam-first, were fully identified by PLS-DA models, while the identification models of other vegetables containing pesticide residues still need to be further improved. The results provide technical support for identifying the rational use of pesticides in vegetables and provide a reference method for guaranteeing the authenticity of green and organic vegetables.
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Affiliation(s)
- Fang Qi
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- College of Food Sciences, Shanghai Ocean University, Shanghai 201306, China
| | - Xing Liu
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- Shanghai Service Platform of Agro-Products Quality and Safety Evaluation Technology, Shanghai 201403, China
| | - Zhongsheng Deng
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- Shanghai Service Platform of Agro-Products Quality and Safety Evaluation Technology, Shanghai 201403, China
| | - Yangyang Lu
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- Shanghai Service Platform of Agro-Products Quality and Safety Evaluation Technology, Shanghai 201403, China
| | - Yijiao Chen
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- Shanghai Service Platform of Agro-Products Quality and Safety Evaluation Technology, Shanghai 201403, China
| | - Hao Geng
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- Shanghai Service Platform of Agro-Products Quality and Safety Evaluation Technology, Shanghai 201403, China
| | - Qicai Zhang
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- Shanghai Service Platform of Agro-Products Quality and Safety Evaluation Technology, Shanghai 201403, China
| | - Qinxiong Rao
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- Shanghai Service Platform of Agro-Products Quality and Safety Evaluation Technology, Shanghai 201403, China
| | - Weiguo Song
- Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
- Shanghai Service Platform of Agro-Products Quality and Safety Evaluation Technology, Shanghai 201403, China
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Non-targeted authentication of black pepper using a local web platform: Development, validation and post-analytical challenges of a combined NIR spectroscopy and LASSO method. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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9
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A geographical traceability method for Lanmaoa asiatica mushrooms from 20 township-level geographical origins by near infrared spectroscopy and ResNet image analysis techniques. ECOL INFORM 2022. [DOI: 10.1016/j.ecoinf.2022.101808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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10
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Prandi B, Righetti L, Caligiani A, Tedeschi T, Cirlini M, Galaverna G, Sforza S. Assessing food authenticity through protein and metabolic markers. ADVANCES IN FOOD AND NUTRITION RESEARCH 2022; 102:233-274. [PMID: 36064294 DOI: 10.1016/bs.afnr.2022.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
This chapter aims to address an issue of ancient origins, but more and more topical in a globalized world in which consumers and stakeholders are increasingly aware: the authenticity of food. Foods are systems that can also be very complex, and verifying the correspondence between what is declared and the actual characteristics of the product is often a challenging issue. The complexity of the question we want to answer (is the food authentic?) means that the answer is equally articulated and makes use of many different analytical techniques. This chapter will consider the chemical analyses of foods aimed at guaranteeing their authenticity and will focus on frontier methods that have been developed in recent years to address the need to respond to ever-increasing guarantees of authenticity. Targeted and non-targeted approaches will be considered for verifying the authenticity of foods, through the study of different classes of constituents (proteins, metabolites, lipids, flavors). The numerous approaches available (proteomics, metabolomics, lipidomics) and the related analytical techniques (LC-MS, GC-MS, NMR) are first described from a more general point of view, after which their specific application for the purposes of authentication of food is addressed.
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Affiliation(s)
- Barbara Prandi
- Department of Food and Drug, University of Parma, Parma, Italy.
| | - Laura Righetti
- Department of Food and Drug, University of Parma, Parma, Italy
| | | | - Tullia Tedeschi
- Department of Food and Drug, University of Parma, Parma, Italy
| | - Martina Cirlini
- Department of Food and Drug, University of Parma, Parma, Italy
| | | | - Stefano Sforza
- Department of Food and Drug, University of Parma, Parma, Italy
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Jiang S, Wang F, Li Q, Sun H, Wang H, Yao Z. Environment and food safety: a novel integrative review. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:54511-54530. [PMID: 34431060 PMCID: PMC8384557 DOI: 10.1007/s11356-021-16069-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 08/16/2021] [Indexed: 04/12/2023]
Abstract
Environment protection and food safety are two critical issues in the world. In this review, a novel approach which integrates statistical study and subjective discussion was adopted to review recent advances on environment and food safety. Firstly, a scientometric-based statistical study was conducted based on 4904 publications collected from the Web of Science Core Collection database. It was found that the research on environment and food safety was growing steadily from 2001 to 2020. Interestingly, the statistical analysis of most-cited papers, titles, abstracts, keywords, and research areas revealed that the research on environment and food safety was diverse and multidisciplinary. In addition to the scientometric study, strategies to protect environment and ensure food safety were critically discussed, followed by a discussion on the emerging research topics, including emerging contaminates (e.g., microplastics), rapid detection of contaminants (e.g., biosensors), and environment friendly food packaging materials (e.g., biodegradable polymers). Finally, current challenges and future research directions were proposed.
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Affiliation(s)
- Shanxue Jiang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Fang Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Qirun Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Haishu Sun
- Department of Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
| | - Huijiao Wang
- School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China.
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