1
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Novais LMRD, Melara VK, Salome KS, Barison A, Mascarenhas RDO, Andrade MVDO, Lasmar MC, Freitas JMD, Fernandes MRS, D'Oca CDRM. Investigation of fraud in the production of butter: a forensic case study of criminal association. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 2024:1-13. [PMID: 39133515 DOI: 10.1080/19440049.2024.2387191] [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: 04/05/2024] [Revised: 07/17/2024] [Accepted: 07/25/2024] [Indexed: 08/13/2024]
Abstract
Butter is among the most popular and commercially valuable dairy products. Its high commercial value makes it a major target for adulteration, which aims to reduce production costs by using lower-quality fats and oils from other sources. The annual global market is around USD 30 billion (2023), expected to reach USD 36 billion in 2028, which also justifies the enormous interest in adulteration. In this work, a confirmed case of butter adulteration was studied by Nuclear Magnetic Resonance (NMR) and Stable Carbon Isotopic Ratio Analysis (SCIRA) techniques, employed to detect the inclusion in butter production of vegetable oils, such as soybean and palm oils. A total of 21 samples seized by the Brazilian Federal Police were analysed by NMR and SCIR, and compared to original butter obtained from commercial sources. The composition of all the seized samples was a mixture of butter (dairy fat of animal origin) with fat of vegetable origin (soybean and palm oil) and did not contain milk as a major component. While NMR was an unequivocal choice to discriminate the chemical composition of food samples, identifying the short-chain saturated fatty acids present in milk fat, including the butyryl alkyl chain, SCIRA was able to discriminate the origin of fat present in the butter samples as C3 sources, such as palm vegetable oils.
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Affiliation(s)
| | - Vinícius Kemper Melara
- Multi-user NMR Laboratory, Department of Chemistry, Federal University of Paraná, Curitiba, Brazil
| | - Kahlil Schwanka Salome
- Multi-user NMR Laboratory, Department of Chemistry, Federal University of Paraná, Curitiba, Brazil
| | - Andersson Barison
- Multi-user NMR Laboratory, Department of Chemistry, Federal University of Paraná, Curitiba, Brazil
| | | | | | - Marcelo Carvalho Lasmar
- Brazilian Federal Police, Regional Superintendence of the Federal Police in Minas Gerais, Minas Gerais, Brazil
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2
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Zhang XH, Gu HW, Liu RJ, Qing XD, Nie JF. A comprehensive review of the current trends and recent advancements on the authenticity of honey. Food Chem X 2023; 19:100850. [PMID: 37780275 PMCID: PMC10534224 DOI: 10.1016/j.fochx.2023.100850] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/15/2023] [Accepted: 08/26/2023] [Indexed: 10/03/2023] Open
Abstract
The authenticity of honey currently poses challenges to food quality control, thus requiring continuous modernization and improvement of related analytical methodologies. This review provides a comprehensively overview of honey authenticity challenges and related analytical methods. Firstly, direct and indirect methods of honey adulteration were described in detail, commenting the existing challenges in current detection methods and market supervision approaches. As an important part, the integrated metabolomic workflow involving sample processing procedures, instrumental analysis techniques, and chemometric tools in honey authenticity studies were discussed, with a focus on their advantages, disadvantages, and scopes. Among them, various improved microscale extraction methods, combined with hyphenated instrumental analysis techniques and chemometric data processing tools, have broad application potential in honey authenticity research. The future of honey authenticity determination will involve the use of simplified and portable methods, which will enable on-site rapid detection and transfer detection technologies from the laboratory to the industry.
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Affiliation(s)
- Xiao-Hua Zhang
- Department of Chemistry and Chemical Engineering, Hunan Institute of Science and Technology, Yueyang, China
- Henan Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety, Food and Pharmacy College, Xuchang University, Xuchang, China
| | - Hui-Wen Gu
- College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou, China
| | - Ren-Jun Liu
- Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, China
| | - Xiang-Dong Qing
- Hunan Provincial Key Laboratory of Dark Tea and Jin-hua, College of Materials and Chemical Engineering, Hunan City University, Yiyang, China
| | - Jin-Fang Nie
- Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, China
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3
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Zhang S, Fang K, Ding Z, Wu J, Lin J, Xu D, Zhong J, Xia F, Feng J, Shen G. Untargeted Metabolomics Analysis Revealed the Difference of Component and Geographical Indication Markers of Panax notoginseng in Different Production Areas. Foods 2023; 12:2377. [PMID: 37372587 DOI: 10.3390/foods12122377] [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: 04/26/2023] [Revised: 05/31/2023] [Accepted: 06/13/2023] [Indexed: 06/29/2023] Open
Abstract
Panax notoginseng (P. notoginseng) has excellent medicinal and food dual-use characteristics. However, P. notoginseng with a unique origin label has become the target of fraud because of people confusing or hiding its origin. In this study, an untargeted nuclear magnetic resonance (NMR)-based metabolomics approach was used to discriminate the geographical origins of P. notoginseng from four major producing areas in China. Fifty-two components, including various saccharides, amino acids, saponins, organic acids, and alcohols, were identified and quantified through the NMR spectrum, and the area-specific geographical identification components were further screened. P. notoginseng from Yunnan had strong hypoglycemic and cardiovascular protective effects due to its high acetic acid, dopamine, and serine content, while P. notoginseng from Sichuan was more beneficial for diseases of the nervous system because of its high content of fumarate. P. notoginseng from Guizhou and Tibet had high contents of malic acid, notoginsenoside R1, and amino acids. Our results can help to distinguish the geographical origin of P. notoginseng and are readily available for nutritional recommendations in human consumption.
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Affiliation(s)
- Shijia Zhang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Kexin Fang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Zenan Ding
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jinxia Wu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jianzhong Lin
- Technology Center of Xiamen Customs, Xiamen 361012, China
| | - Dunming Xu
- Technology Center of Xiamen Customs, Xiamen 361012, China
| | - Jinshui Zhong
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Feng Xia
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jianghua Feng
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Guiping Shen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
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4
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Dong W, Hong Q, Cheng J, He H, Li Y, Hu R, Long Y. Simultaneous analysis of the oxidation of solvent-extracted and cold-pressed green coffee oil during accelerated storage using 1H NMR and 13C NMR spectroscopy. Food Res Int 2023; 165:112470. [PMID: 36869483 DOI: 10.1016/j.foodres.2023.112470] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 11/29/2022] [Accepted: 01/05/2023] [Indexed: 01/09/2023]
Abstract
Green coffee oil (GCO) extracted from green coffee beans, is known for its antioxidant and anticancer properties, and has been increasingly utilised in cosmetic and other consumer products. However, lipid oxidation of GCO fatty acid components during storage may be harmful to human health, and there remains a need to understand the evolution of GCO chemical component oxidation. In this study, proton nuclear magnetic resonance (1H and 13C NMR) spectroscopy was used to investigate the oxidation status of solvent-extracted and cold-pressed GCO under accelerated storage conditions. Results show that the signal intensity of oxidation products gradually increased with increasing oxidation time, while unsaturated fatty acid signals gradually weakened. Five different types of GCO extracts were clustered according to their properties, except for minor overlapping in the two-dimensional plane of the principal component analysis. Partial least squares-least analysis results demonstrate that oxidation products (δ = 7.8-10.3 ppm), unsaturated fatty acids (δ = 5.28-5.42 ppm), and linoleic acid (δ = 2.70-2.85 ppm) in 1H NMR can be used as characteristic indicators of GCO oxidation levels. Furthermore, the kinetics curves of unsaturated fatty acids, linoleic, and linolenic acyl groups all fit an exponential equation with high coefficients of GCO for 36 days under accelerated storage conditions. Our results show that the current NMR system is a fast, easy-operated and convenient tool for the oxidation process monitoring and quality control of GCO.
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Affiliation(s)
- Wenjiang Dong
- Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China; Key Laboratory of Processing Suitability and Quality Control of the Special Tropical Crops of Hainan Province, Wanning, Hainan 571533, China; National Center of Important Tropical Crops Engineering and Technology Research, Wanning, Hainan 571533, China.
| | - Qidi Hong
- Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China; College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Jinhuan Cheng
- Tropical and Subtropical Economic Crops Research Institute, Yunnan Academy of Agricultural Sciences, Baoshan, Yunnan 678000, China
| | - Hongyan He
- Tropical and Subtropical Economic Crops Research Institute, Yunnan Academy of Agricultural Sciences, Baoshan, Yunnan 678000, China
| | - Yanan Li
- Tropical and Subtropical Economic Crops Research Institute, Yunnan Academy of Agricultural Sciences, Baoshan, Yunnan 678000, China
| | - Rongsuo Hu
- Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China; Key Laboratory of Processing Suitability and Quality Control of the Special Tropical Crops of Hainan Province, Wanning, Hainan 571533, China; National Center of Important Tropical Crops Engineering and Technology Research, Wanning, Hainan 571533, China
| | - Yuzhou Long
- Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China
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Mehdizadeh SA, Abdolahzare Z, Karaji FK, Mouazen A. Design and manufacturing a microcontroller based measurement device for honey adulteration detection. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.105049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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6
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7
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Cagliani L, Maestri G, Consonni R. Detection and evaluation of saccharide adulteration in Italian honey by NMR spectroscopy. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108574] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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8
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Ji Hye L, Jae Min A, Dong Jin K, Ho Jin K, Seong Hun L. Use of LC-Orbitrap MS and FT-NIRS with multivariate analysis to determine geographic origin of Boston butt pork. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2022. [DOI: 10.1080/10942912.2022.2027962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Lee Ji Hye
- Experiment Research Institute, National Agricultural Products Quality Management Service, Gimcheon, Republic of Korea
| | - An Jae Min
- Experiment Research Institute, National Agricultural Products Quality Management Service, Gimcheon, Republic of Korea
| | - Kang Dong Jin
- Experiment Research Institute, National Agricultural Products Quality Management Service, Gimcheon, Republic of Korea
| | - Kim Ho Jin
- Experiment Research Institute, National Agricultural Products Quality Management Service, Gimcheon, Republic of Korea
| | - Lee Seong Hun
- Experiment Research Institute, National Agricultural Products Quality Management Service, Gimcheon, Republic of Korea
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9
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10
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Shen S, Yang Y, Wang J, Chen X, Liu T, Zhuo Q. [Analysis of differences between unifloral honeys from different botanical origins based on non-targeted metabolomics by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry]. Se Pu 2021; 39:291-300. [PMID: 34227310 PMCID: PMC9403802 DOI: 10.3724/sp.j.1123.2020.06029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
不同的蜜源植物具有结构多样的次生代谢产物。该研究以8种不同蜜源单花蜜(洋槐蜜、枣花蜜、荆条蜜、椴树蜜、荞麦蜜、麦卢卡蜜、枸杞蜜、益母草蜜)为研究对象,建立了基于超高效液相色谱-四极杆飞行时间质谱技术(UPLC-Q-TOF-MSE)的非靶向代谢组学方法,考察了不同蜜源中次生代谢产物的差异。该研究采用固相萃取前处理方法和UPLC-Q-TOF-MSE方法,获得不同蜜源单花蜜的植物代谢组信息,并构建了多变量统计分析模型,对不同来源的单花蜜进行模式识别和差异分析,发现洋槐蜜、枣花蜜、荆条蜜、椴树蜜、荞麦蜜、麦卢卡蜜相互间存在不同程度的显著差异。结合模型的变量重要性投影、方差分析与最大差异倍数值,根据精确前体离子和碎片离子质量信息检索Chemspider、HMDB数据库,该研究筛选并鉴定出32个代谢差异化合物,其中黄酮类化合物18个、酚酸类化合物7个、苯苷与萜苷类化合物6个、甾体类化合物1个;研究发现麦卢卡蜜和荞麦蜜以黄酮类化合物为主要差异代谢物,荆条蜜中酚酸类化合物为特征性表达,苯苷与萜苷类化合物主要为椴树蜜的特征代谢物。该研究从植物代谢组学角度初步揭示了不同单花蜜的代谢产物差异性以及特征化合物,为基于化学分析技术的蜂蜜溯源识别与质量评价提供了有效的研究策略。
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Affiliation(s)
- Shi Shen
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Yi Yang
- Beijing Center for Disease Control and Prevention, Beijing 100013, China
| | - Jingbo Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Xi Chen
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Tingting Liu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Qin Zhuo
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
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11
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Khamsopha D, Woranitta S, Teerachaichayut S. Utilizing near infrared hyperspectral imaging for quantitatively predicting adulteration in tapioca starch. Food Control 2021. [DOI: 10.1016/j.foodcont.2020.107781] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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12
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Mei J, Zhao F, Xu R, Huang Y. A review on the application of spectroscopy to the condiments detection: from safety to authenticity. Crit Rev Food Sci Nutr 2021; 62:6374-6389. [PMID: 33739226 DOI: 10.1080/10408398.2021.1901257] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Condiments are the magical ingredients that make the food present a richer taste. In recent years, due to the increasing consciousness of food safety and human health, much progress has been made in developing rapid and nondestructive techniques for the evaluation of food condiments safety, authentication, and traceability. The potential of spectroscopy techniques, such as near-infrared (NIR), mid-infrared (MIR), Raman, fluorescence, inductively coupled plasma (ICP), and hyperspectral imaging techniques, has been widely enhanced by numerous applications in this field because of their advantages over other analytical techniques. Following a brief introduction of condiment and safety basics, this review mainly focuses on recent vibrational and atomic spectral applications for condiment nondestructive analysis and evaluation, including (1) chemical hazards detection; (2) microbiological hazards detection; and (3) authenticity concerns. The review shows current spectroscopies to be effective tools that will play indispensable roles for food condiment evaluation. In addition, online/real-time applications of these techniques promise to be a huge growth field in the near future.
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Affiliation(s)
- Jianhua Mei
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, P. R. China.,Health Food Industry Research Institute (Xinghua), China Agricultural University, Xinghua, Jiangsu, 225700, P. R. China
| | - Fangyuan Zhao
- College of Food Science and Engineering, Qingdao Agricultural University, Qingdao, Shandong, 266109, P. R. China
| | - Runqi Xu
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, P. R. China.,Health Food Industry Research Institute (Xinghua), China Agricultural University, Xinghua, Jiangsu, 225700, P. R. China
| | - Yue Huang
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, P. R. China.,Health Food Industry Research Institute (Xinghua), China Agricultural University, Xinghua, Jiangsu, 225700, P. R. China
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13
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Zhang J, Chen H, Fan C, Gao S, Zhang Z, Bo L. Classification of the botanical and geographical origins of Chinese honey based on 1H NMR profile with chemometrics. Food Res Int 2020; 137:109714. [PMID: 33233286 DOI: 10.1016/j.foodres.2020.109714] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 09/07/2020] [Accepted: 09/07/2020] [Indexed: 12/21/2022]
Abstract
In this paper, we report a newly developed non-target 1H NMR detection associated with chemometrics method to classify the botanical and geographical origins of the monofloral Chinese honey. 1H NMR tests of 218 monofloral honey samples of 8 classes (Acacia, Jujube, Linden, Longan, Orange, Rape, Sunflower, Vitex) collected in 2017-2019 across China were conducted under the optimal sample preparation conditions and NMR acquisition parameters. The whole profiles of NMR spectra instead of individual or partial signals from specific components were processed and extracted, then fed to SIMCA-P to classify the botanical and geographical origins through non-target statistical analysis. For the botanical origins, most of them could be classified clearly according to Principal Component Analysis (PCA) with both R2 and Q2 close to 1. Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) model could classify the honey floral types successfully with R2Y and Q2 greater than 0.85. It is found that the integral bin for data extraction has no obvious influence on the classification. For the geographical origins, the classification at different geographical levels (providence and town) could be successfully distinguished by OPLS-DA model. The promising preliminary results with the geographical classification at 40 km level unambiguously demonstrate the application of this NMR-based multi-species non-targeted method for the honey authenticity. Successful result is obtained on a pilot prediction of the geographical classification. Comparing with the methods based on other techniques, the advantages of this reported one are less sample amount needed, simple preparation, short test time, and non-targeted multi-species detection.
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Affiliation(s)
- Jialin Zhang
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
| | - Hui Chen
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
| | - Chunlin Fan
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
| | - Shuai Gao
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
| | - Zijuan Zhang
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China.
| | - Lin Bo
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
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14
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Hassoun A, Måge I, Schmidt WF, Temiz HT, Li L, Kim HY, Nilsen H, Biancolillo A, Aït-Kaddour A, Sikorski M, Sikorska E, Grassi S, Cozzolino D. Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years. Foods 2020; 9:E1069. [PMID: 32781687 PMCID: PMC7466239 DOI: 10.3390/foods9081069] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 07/29/2020] [Accepted: 08/01/2020] [Indexed: 12/27/2022] Open
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 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.
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Affiliation(s)
- Abdo Hassoun
- Nofima AS, Norwegian Institute of Food, Fisheries, and Aquaculture Research, Muninbakken 9-13, 9291 Tromsø, Norway; (I.M.); (H.N.)
| | - Ingrid Måge
- Nofima AS, Norwegian Institute of Food, Fisheries, and Aquaculture Research, Muninbakken 9-13, 9291 Tromsø, Norway; (I.M.); (H.N.)
| | - Walter F. Schmidt
- United States Department of Agriculture, Agricultural Research Service, 10300 Baltimore Avenue, Beltsville, MD 20705-2325, USA;
| | - Havva Tümay Temiz
- Department of Food Engineering, Bingol University, 12000 Bingol, Turkey;
| | - Li Li
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China;
| | - Hae-Yeong Kim
- Department of Food Science and Biotechnology, Kyung Hee University, Yongin 17104, Korea;
| | - Heidi Nilsen
- Nofima AS, Norwegian Institute of Food, Fisheries, and Aquaculture Research, Muninbakken 9-13, 9291 Tromsø, Norway; (I.M.); (H.N.)
| | - Alessandra Biancolillo
- Department of Physical and Chemical Sciences, University of L’Aquila, 67100 Via Vetoio, Coppito, L’Aquila, Italy;
| | | | - Marek Sikorski
- Faculty of Chemistry, Adam Mickiewicz University in Poznan, Uniwersytetu Poznanskiego 8, 61-614 Poznan, Poland;
| | - Ewa Sikorska
- Institute of Quality Science, Poznań University of Economics and Business, al. Niepodległości 10, 61-875 Poznań, Poland;
| | - Silvia Grassi
- Department of Food, Environmental and Nutritional Sciences (DeFENS), Università degli Studi di Milano, via Celoria, 2, 20133 Milano, Italy;
| | - Daniel Cozzolino
- Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, 39 Kessels Rd, Coopers Plains, QLD 4108, Australia;
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