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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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2
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Abedini A, Salimi M, Mazaheri Y, Sadighara P, Alizadeh Sani M, Assadpour E, Jafari SM. Assessment of cheese frauds, and relevant detection methods: A systematic review. Food Chem X 2023; 19:100825. [PMID: 37780280 PMCID: PMC10534187 DOI: 10.1016/j.fochx.2023.100825] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 07/28/2023] [Accepted: 08/02/2023] [Indexed: 10/03/2023] Open
Abstract
Dairy products are widely consumed in the world due to their nutritional and functional characteristics. This group of food products are consumed by all age groups due to their health-giving properties. One of these products is cheese which has a high price compared to other dairy products. Because of this, it can be prone to fraud all over the world. Fraud in food products threatens the world's food safety and can cause serious damage to human health. There are many concerns among food authorities in the world about the fraud of food products. FDA, WHO, and the European Commission provide different legislations and definitions for fraud. The purpose of this review is to identify the most susceptible cheese type for fraud and effective methods for evaluating fraud in all types of cheeses. For this, we examined the Web of Science, Scopus, PubMed, and ScienceDirect databases. Mozzarella cheese had the largest share among all cheeses in terms of adulteration due to its many uses. Also, the methods used to evaluate different types of cheese frauds were PCR, Spectrometry, stable isotope, image analysis, electrophoretic, ELISA, sensors, sensory analysis, near-infrared and NMR. The methods that were most used in detecting fraud were PCR and spectrometry methods. Also, the least used method was sensory evaluation.
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Affiliation(s)
- Amirhossein Abedini
- Students Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
- Division of Food Safety and Hygiene, Department of Environmental Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahla Salimi
- Student Research Committee, Department of Food Science and Technology, National Nutrition and Food Technology Research Institute, Faculty of Nutrition Science and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Yeganeh Mazaheri
- Division of Food Safety and Hygiene, Department of Environmental Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Parisa Sadighara
- Division of Food Safety and Hygiene, Department of Environmental Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahmood Alizadeh Sani
- Division of Food Safety and Hygiene, Department of Environmental Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Elham Assadpour
- Food Industry Research Co., Gorgan, Iran
- Food and Bio-Nanotech International Research Center (Fabiano), Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
| | - Seid Mahdi Jafari
- Department of Food Materials and Process Design Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
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3
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Kröncke N, Wittke S, Steinmann N, Benning R. Analysis of the Composition of Different Instars of Tenebrio molitor Larvae using Near-Infrared Reflectance Spectroscopy for Prediction of Amino and Fatty Acid Content. INSECTS 2023; 14:310. [PMID: 37103125 PMCID: PMC10141721 DOI: 10.3390/insects14040310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/18/2023] [Accepted: 03/22/2023] [Indexed: 06/19/2023]
Abstract
Insects are a sustainable protein source for food and feed. The yellow mealworm (Tenebrio molitor L.) is a promising candidate for industrial insect rearing and was the focus of this study. This research revealed the diversity of Tenebrio molitor larvae in the varying larval instars in terms of the nutritional content. We hypothesized that water and protein are highest in the earlier instar, while fat content is very low but increases with larval development. Consequently, an earlier instar would be a good choice for harvest, since proteins and amino acids content decrease with larval development. Near-infrared reflectance spectroscopy (NIRS) was represented in this research as a tool for predicting the amino and fatty acid composition of mealworm larvae. Samples were scanned with a near-infrared spectrometer using wavelengths from 1100 to 2100 nm. The calibration for the prediction was developed with modified partial least squares (PLS) as the regression method. The coefficient for determining calibration (R2C) and prediction (R2P) were >0.82 and >0.86, with RPD values of >2.20 for 10 amino acids, resulting in a high prediction accuracy. The PLS models for glutamic acid, leucine, lysine and valine have to be improved. The prediction of six fatty acids was also possible with the coefficient of the determination of calibration (R2C) and prediction (R2P) > 0.77 and >0.66 with RPD values > 1.73. Only the prediction accuracy of palmitic acid was very weak, which was probably due to the narrow variation range. NIRS could help insect producers to analyze the nutritional composition of Tenebrio molitor larvae fast and easily in order to improve the larval feeding and composition for industrial mass rearing.
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Affiliation(s)
- Nina Kröncke
- Institute of Food Technology and Bioprocess Engineering, University of Applied Sciences Bremerhaven, An der Karlstadt 8, 27568 Bremerhaven, Germany
| | - Stefan Wittke
- Laboratory for (Marine) Biotechnology, University of Applied Sciences Bremerhaven, An der Karlstadt 8, 27568 Bremerhaven, Germany
| | - Nico Steinmann
- Laboratory for (Marine) Biotechnology, University of Applied Sciences Bremerhaven, An der Karlstadt 8, 27568 Bremerhaven, Germany
| | - Rainer Benning
- Institute of Food Technology and Bioprocess Engineering, University of Applied Sciences Bremerhaven, An der Karlstadt 8, 27568 Bremerhaven, Germany
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4
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A comprehensive overview of emerging techniques and chemometrics for authenticity and traceability of animal-derived food. Food Chem 2023; 402:134216. [DOI: 10.1016/j.foodchem.2022.134216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 08/21/2022] [Accepted: 09/09/2022] [Indexed: 11/17/2022]
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Mechanisms and Health Aspects of Food Adulteration: A Comprehensive Review. Foods 2023; 12:foods12010199. [PMID: 36613416 PMCID: PMC9818512 DOI: 10.3390/foods12010199] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 12/26/2022] [Accepted: 12/28/2022] [Indexed: 01/04/2023] Open
Abstract
Food adulteration refers to the alteration of food quality that takes place deliberately. It includes the addition of ingredients to modify different properties of food products for economic advantage. Color, appearance, taste, weight, volume, and shelf life are such food properties. Substitution of food or its nutritional content is also accomplished to spark the apparent quality. Substitution with species, protein content, fat content, or plant ingredients are major forms of food substitution. Origin misrepresentation of food is often practiced to increase the market demand of food. Organic and synthetic compounds are added to ensure a rapid effect on the human body. Adulterated food products are responsible for mild to severe health impacts as well as financial damage. Diarrhea, nausea, allergic reaction, diabetes, cardiovascular disease, etc., are frequently observed illnesses upon consumption of adulterated food. Some adulterants have shown carcinogenic, clastogenic, and genotoxic properties. This review article discusses different forms of food adulteration. The health impacts also have been documented in brief.
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6
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In-depth chemometric strategy to detect up to four adulterants in cashew nuts by IR spectroscopic techniques. Microchem J 2022. [DOI: 10.1016/j.microc.2022.107816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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7
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Challenges and Opportunities in the Application of Chemometrics in the Pharmaceutical and Food Science Industries. J CHEM-NY 2022. [DOI: 10.1155/2022/9823497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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8
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Detection of sunflower oils adulteration by ATR-FTIR spectra. CHEMICAL PAPERS 2022. [DOI: 10.1007/s11696-022-02245-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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9
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Zhao T, Cao Z, Yu J, Weng X, Benjakul S, Guidi A, Ying X, Ma L, Xiao G, Deng S. Gas-phase ion migration spectrum analysis of the volatile flavors of large yellow croaker oil after different storage periods. Curr Res Food Sci 2022; 5:813-822. [PMID: 35592694 PMCID: PMC9110977 DOI: 10.1016/j.crfs.2022.04.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 04/11/2022] [Accepted: 04/28/2022] [Indexed: 12/18/2022] Open
Abstract
The large yellow croaker, a species of fish found in the northwestern Pacific, is favored by consumers because of its prevalence in saltwater bodies, golden yellow abdomen, high calcium content, high protein, high fat content, and a flavor that originates from its lipids and volatile components. Volatile organic compounds significantly affect the aroma of food. In this work, electronic nose and headspace gas chromatography-ion mobility spectrometry were applied to analyze the flavor differences in fish oil durations. Through electronic nose system analysis, sensors W1C, W3S, W6S, and W2S directly affected fish oil flavor, and their flavor components were different. Gas chromatography-ion mobility spectrometry identified 26 volatile components (19 aldehydes, 3 ketones, 2 alcohols, 1 furan, and 1 olefin). (E,E)-2,4-hexadienal (D), (E,E)-2,4-hexadienal (M), 2,4-heptadienal (M), (E)-2-octenal, 2-propanone, 2-heptanone (M), 3-pentanone (D), and 1-octen-3-ol were the key flavor components of the fish oil. In conclusion, the combination of GC-IMS and PCA can identify the differences in flavor changes of large yellow croaker oil during 0–120 days storage. After 60 days storage, the types and signals of 2-propanone, 2-heptanone (M) components increase significantly. When 120 days storage, at this time, (E,E)-2,4-hexadienal (D), (E,E)-2,4-hexadienal (M), 2,4-heptadienal (M), (E)-2-octenal,(E)-2-octenal significantly. It has become the main flavor substance of fish oil. In summary, as the storage period increases, the components increase, and the oxidizing substances will increase, resulting in the deterioration of fish oil. The oxidation state of Large yellow croaker oil in different storage periods was investigated. The volatile compounds of Large yellow croaker oil were studied by GC-IMS. The effects of storage period on the composition of large yellow croaker oil samples were tested. We believe GC-IMS will play a crucial role in controlling the flavor of fish oil.
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Affiliation(s)
- Tengfei Zhao
- Zhejiang Provincial Key Laboratory of Health Risk Factors for Seafood, Collaborative Innovation Center of Seafood Deep Processing, College of Food and Pharmacy, Zhejiang Ocean University, Zhoushan, 316022, China
| | - Zhongqi Cao
- Sinopec Dalian Research Institute of Petroleum and Petrochemicals, Dalian Lioaning, 116045, China
| | - Jin Yu
- Longyou Aquaculture Development Center, Agricultural and Rural Bureau of Longyou County, Quzhou, 324000, China
| | - Xudong Weng
- Longyou Aquaculture Development Center, Agricultural and Rural Bureau of Longyou County, Quzhou, 324000, China
| | - Soottawat Benjakul
- International Center of Excellence in Seafood Science and Innovation, Faculty of Agro-Industry. Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
| | - Alessandra Guidi
- Department of Agriculture, Food and Environment (DAFE), Pisa University, Via Del Borghetto, 80, 56124, Pisa, Italy
| | - Xiaoguo Ying
- Zhejiang Provincial Key Laboratory of Health Risk Factors for Seafood, Collaborative Innovation Center of Seafood Deep Processing, College of Food and Pharmacy, Zhejiang Ocean University, Zhoushan, 316022, China
- Longyou Aquaculture Development Center, Agricultural and Rural Bureau of Longyou County, Quzhou, 324000, China
- Corresponding author. No.1 Haida South Road, Lincheng Changzhi Island, Zhoushan, Zhejiang province, 316022, PR China.
| | - Lukai Ma
- Guangdong Provincial Key Laboratory of Lingnan Specialty Food Science and Technology, College of Light Industry and Food, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China
- Academy of Contemporary Agricultural Engineering Innovations, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China
- Corresponding author. No.24 Dongsha Road, Haizhu District, Guangzhou, Guangdong province, 510225, PR China.
| | - Gengsheng Xiao
- Guangdong Provincial Key Laboratory of Lingnan Specialty Food Science and Technology, College of Light Industry and Food, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China
| | - Shanggui Deng
- Zhejiang Provincial Key Laboratory of Health Risk Factors for Seafood, Collaborative Innovation Center of Seafood Deep Processing, College of Food and Pharmacy, Zhejiang Ocean University, Zhoushan, 316022, China
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10
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Zhao T, Sheng B, Ying X, Sanmartin C, Benjakul S, Ma L, Xiao G, Liu G. Role of lipid deterioration on the quality of aquatic products during low‐temperature storage: a lipidomics‐based study using large yellow croaker (
Larimichthys crocea
). Int J Food Sci Technol 2022. [DOI: 10.1111/ijfs.15465] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Tengfei Zhao
- Zhejiang Provincial Key Laboratory of Health Risk Factors for Seafood Collaborative Innovation Center of Seafood Deep Processing College of Food and Pharmacy Zhejiang Ocean University Zhoushan China
| | - Bulei Sheng
- Department of Food Science Aarhus University Aarhus Denmark
| | - Xiaoguo Ying
- Zhejiang Provincial Key Laboratory of Health Risk Factors for Seafood Collaborative Innovation Center of Seafood Deep Processing College of Food and Pharmacy Zhejiang Ocean University Zhoushan China
- College of Biosystems Engineering and Food Science Zhejiang University Hangzhou China
| | - Chiara Sanmartin
- Department of Agriculture, Food and Environment (DAFE) Pisa University Pisa Italy
| | - Soottawat Benjakul
- International Center of Excellence in Seafood Science and Innovation Faculty of Agro‐Industry Prince of Songkla University Hat Yai Songkhla Thailand
| | - Lukai Ma
- Guangdong Provincial Key Laboratory of Lingnan Specialty Food Science and Technology College of Light Industry and Food Zhongkai University of Agriculture and Engineering Guangzhou China
- Academy of Contemporary Agricultural Engineering Innovations Zhongkai University of Agriculture and Engineering Guangzhou China
| | - Gengsheng Xiao
- Guangdong Provincial Key Laboratory of Lingnan Specialty Food Science and Technology College of Light Industry and Food Zhongkai University of Agriculture and Engineering Guangzhou China
| | - Guoqin Liu
- School of Food Science and Engineering South China University of Technology Guangzhou China
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11
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HOU Y, ZHAO P, ZHANG F, YANG S, RADY A, WIJEWARDANE NK, HUANG J, LI M. Fourier-transform infrared spectroscopy and machine learning to predict amino acid content of nine commercial insects. FOOD SCIENCE AND TECHNOLOGY 2022. [DOI: 10.1590/fst.100821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- Yinchen HOU
- Henan University of Animal Husbandry and Economy, China
| | | | - Fan ZHANG
- China Agricultural University, People’s Republic of China
| | - Shengru YANG
- Henan University of Animal Husbandry and Economy, China
| | | | | | | | - Mengxing LI
- University of Nebraska-Lincoln, USA; University of Nebraska-Lincoln, USA
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12
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Brooks C, Parr L, Smith JM, Buchanan D, Snioch D, Hebishy E. A review of food fraud and food authenticity across the food supply chain, with an examination of the impact of the COVID-19 pandemic and Brexit on food industry. Food Control 2021. [DOI: 10.1016/j.foodcont.2021.108171] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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13
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Zhao S, Liu H, Qie M, Zhang J, Tan L, Zhao Y. Stable Isotope Analysis for Authenticity and Traceability in Food of Animal Origin. FOOD REVIEWS INTERNATIONAL 2021. [DOI: 10.1080/87559129.2021.2005087] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Shanshan Zhao
- Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Institute of Quality Standard & Testing Technology for Agro-Products, Beijing, China
- Key Laboratory of Agro-product Quality and Safety, Ministry of Agriculture, Beijing, China
| | - Haijin Liu
- Tibet Autonomous Region Agricultural and Livestock Product Quality and Safety Inspection Testing Center, Lhasa, China
| | - Mengjie Qie
- Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Institute of Quality Standard & Testing Technology for Agro-Products, Beijing, China
- Key Laboratory of Agro-product Quality and Safety, Ministry of Agriculture, Beijing, China
| | - Jiukai Zhang
- Agro-Product Safety Research Center, Chinese Academy of Inspection and Quarantine, Beijing, China
| | - Liqin Tan
- Changgao Agricultural Technology Extension Station, Beipiao, China
| | - Yan Zhao
- Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Institute of Quality Standard & Testing Technology for Agro-Products, Beijing, China
- Key Laboratory of Agro-product Quality and Safety, Ministry of Agriculture, Beijing, China
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14
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Diving Deep into the Data: A Review of Deep Learning Approaches and Potential Applications in Foodomics. Foods 2021; 10:foods10081803. [PMID: 34441579 PMCID: PMC8392494 DOI: 10.3390/foods10081803] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/30/2021] [Accepted: 08/02/2021] [Indexed: 01/18/2023] Open
Abstract
Deep learning is a trending field in bioinformatics; so far, mostly known for image processing and speech recognition, but it also shows promising possibilities for data processing in food analysis, especially, foodomics. Thus, more and more deep learning approaches are used. This review presents an introduction into deep learning in the context of metabolomics and proteomics, focusing on the prediction of shelf-life, food authenticity, and food quality. Apart from the direct food-related applications, this review summarizes deep learning for peptide sequencing and its context to food analysis. The review’s focus further lays on MS (mass spectrometry)-based approaches. As a result of the constant development and improvement of analytical devices, as well as more complex holistic research questions, especially with the diverse and complex matrix food, there is a need for more effective methods for data processing. Deep learning might offer meeting this need and gives prospect to deal with the vast amount and complexity of data.
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The use of analytical techniques coupled with chemometrics for tracing the geographical origin of oils: A systematic review (2013-2020). Food Chem 2021; 366:130633. [PMID: 34332421 DOI: 10.1016/j.foodchem.2021.130633] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 06/14/2021] [Accepted: 07/16/2021] [Indexed: 11/20/2022]
Abstract
The global market for imported, high-quality priced foods has grown dramatically in the last decade, as consumers become more conscious of food originating from around the world. Many countries require the origin label of food to protect consumers need about true characteristics and origin. Regulatory authorities are looking for an extended and updated list of the analytical techniques for verification of authentic oils and to support law implementation. This review aims to introduce the efforts made using various analytical tools in combination with the multivariate analysis for the verification of the geographical origin of oils. The popular analytical tools have been discussed, and scientometric assessment that underlines research trends in geographical authentication and preferred journals used for dissemination has been indicated. Overall, we believe this article will be a good guideline for food industries and food quality control authority to assist in the selection of appropriate methods to authenticate oils.
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The Combination of Vibrational Spectroscopy and Chemometrics for Analysis of Milk Products Adulteration. INTERNATIONAL JOURNAL OF FOOD SCIENCE 2021; 2021:8853358. [PMID: 34307647 PMCID: PMC8263233 DOI: 10.1155/2021/8853358] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Accepted: 06/12/2021] [Indexed: 11/18/2022]
Abstract
Milk products obtained from cow, goat, buffalo, sheep, and camel as well as fermented forms such as cheese, yogurt, kefir, and butter are in a category of the most nutritious foods due to their high contents of high protein contributing to total daily energy intake. For certain reasons, high price milk products may be adulterated with low-quality ones or with foreign substances such as melamine and formalin which are added into them; therefore, a comprehensive review on analytical methods capable of detecting milk adulteration is needed. The objective of this narrative review is to highlight the use of vibrational spectroscopies (near infrared, mid infrared, and Raman) combined with multivariate analysis for authentication of milk products. Articles, conference reports, and abstracts from several databases including Scopus, PubMed, Web of Science, and Google Scholar were used in this review. By selecting the correct conditions (spectral treatment, normal versus derivative spectra at wavenumbers region, and chemometrics techniques), vibrational spectroscopy is a rapid and powerful analytical technique for detection of milk adulteration. This review can give comprehensive information for selecting vibrational spectroscopic methods combined with chemometrics techniques for screening the adulteration practice of milk products.
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Valdés García A, Beltrán Sanahuja A, Karabagias IK, Badeka A, Kontominas MG, Garrigós MC. Effect of Frying and Roasting Processes on the Oxidative Stability of Sunflower Seeds ( Helianthus annuus) under Normal and Accelerated Storage Conditions. Foods 2021; 10:944. [PMID: 33925837 PMCID: PMC8146532 DOI: 10.3390/foods10050944] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/19/2021] [Accepted: 04/24/2021] [Indexed: 01/23/2023] Open
Abstract
The effect of different cooking processes such as frying and roasting on the oxidative stability of sunflower seeds was evaluated under accelerated oxidation and normal storage conditions. The fatty acid composition by GC-MS showed a higher amount of linoleic acid in fried samples due to the replacement of the seed moisture by the frying oil. On the other hand, roasted samples presented a higher oleic acid content. DSC and TGA results showed some decrease in the thermal stability of sunflower seed samples, whereas PV and AV showed the formation of primary and secondary products, with increasing oxidation time. Roasted sunflower seeds showed seven main volatile compounds characteristic of the roasting process by HS-SPME-GC-MS: 2-pentylfuran, 2,3-dimethyl-pyrazine, methyl-pyrazine, 2-octanone, 2-ethyl-6-methylpyrazine, trimethyl-pyrazine, and trans,cis-2,4-decadienal, whereas fried samples showed six volatile characteristic compounds of the frying process: butanal, 2-methyl-butanal, 3-methyl-butanal, heptanal, 1-hexanol, and trans,trans-2,4-decadienal. The generation of hydroperoxides, their degradation, and the formation of secondary oxidation products were also investigated by ATR-FTIR analysis. The proposed methodologies in this work could be suitable for monitoring the quality and shelf-life of commercial processed sunflower seeds with storage time.
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Affiliation(s)
- Arantzazu Valdés García
- Department of Analytical Chemistry, University of Alicante, Nutrition & Food Sciences, San Vicente del Raspeig, ES-03690 Alicante, Spain; (A.B.S.); (M.C.G.)
| | - Ana Beltrán Sanahuja
- Department of Analytical Chemistry, University of Alicante, Nutrition & Food Sciences, San Vicente del Raspeig, ES-03690 Alicante, Spain; (A.B.S.); (M.C.G.)
| | - Ioannis K. Karabagias
- Laboratory of Food Chemistry and Technology, Department of Chemistry, University of Ioannina, 45110 Ioannina, Greece; (I.K.K.); (A.B.); (M.G.K.)
| | - Anastasia Badeka
- Laboratory of Food Chemistry and Technology, Department of Chemistry, University of Ioannina, 45110 Ioannina, Greece; (I.K.K.); (A.B.); (M.G.K.)
| | - Michael G. Kontominas
- Laboratory of Food Chemistry and Technology, Department of Chemistry, University of Ioannina, 45110 Ioannina, Greece; (I.K.K.); (A.B.); (M.G.K.)
| | - María Carmen Garrigós
- Department of Analytical Chemistry, University of Alicante, Nutrition & Food Sciences, San Vicente del Raspeig, ES-03690 Alicante, Spain; (A.B.S.); (M.C.G.)
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18
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Data processing strategies for non-targeted analysis of foods using liquid chromatography/high-resolution mass spectrometry. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116188] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Fourier-transform infrared spectroscopy and machine learning to predict fatty acid content of nine commercial insects. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2021. [DOI: 10.1007/s11694-020-00694-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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20
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Akın PA, Sezer B, Bean SR, Peiris K, Tilley M, Apaydın H, Boyacı İH. Analysis of corn and sorghum flour mixtures using laser-induced breakdown spectroscopy. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2021; 101:1076-1084. [PMID: 32776325 DOI: 10.1002/jsfa.10717] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 07/29/2020] [Accepted: 08/09/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND In a world constantly challenged by climate change, corn and sorghum are two important grains because of their high productivity and adaptability, and their multifunctional use for different purposes such as human food, animal feed, and feedstock for many industrial products and biofuels. Corn and sorghum can be utilized interchangeably in certain applications; one grain may be preferred over the other for several reasons. The determination of the composition corn and sorghum flour mixtures may be necessary for economic, regulatory, environmental, functional, or nutritional reasons. RESULTS Laser-induced breakdown spectroscopy (LIBS) in combination with chemometrics, was used for the classification of flour samples based on the LIBS spectra of flour types and mixtures using partial least squares discriminant analysis (PLS-DA) and the determination of the sorghum ratio in sorghum / corn flour mixture based on their elemental composition using partial least squares (PLS) regression. Laser-induced breakdown spectroscopy with PLS-DA successfully identified the samples as either pure corn, pure sorghum, or corn-sorghum mixtures. Moreover, the addition of various levels of sorghum flour to mixtures of corn-sorghum flour were used for PLS analysis. The coefficient of determination values of calibration and validation PLS models are 0.979 and 0.965, respectively. The limit of detection of the PLS models is 4.36%. CONCLUSION This study offers a rapid method for the determination of the sorghum level in corn-sorghum flour mixtures and the classification of flour samples with high accuracy, a short analysis time, and no requirement for time-consuming sample preparation procedures. © 2020 Society of Chemical Industry.
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Affiliation(s)
- Pervin A Akın
- Central Field Crop Research Institute, Ankara, Turkey
- Department of Food Engineering, Hacettepe University, Ankara, Turkey
| | - Banu Sezer
- Department of Food Engineering, Hacettepe University, Ankara, Turkey
| | - Scott R Bean
- Center for Grain and Animal Health Research, USDA-ARS, Manhattan, KS, USA
| | - Kamaranga Peiris
- Department of Agronomy, Kansas State University, Manhattan, KS, USA
| | - Michael Tilley
- Center for Grain and Animal Health Research, USDA-ARS, Manhattan, KS, USA
| | - Hakan Apaydın
- Hitit University Scientific Technique Application and Research Center, Çorum, Turkey
| | - İsmail H Boyacı
- Department of Food Engineering, Hacettepe University, Ankara, Turkey
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21
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22
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Liang N, Sun S, Zhang C, He Y, Qiu Z. Advances in infrared spectroscopy combined with artificial neural network for the authentication and traceability of food. Crit Rev Food Sci Nutr 2020; 62:2963-2984. [PMID: 33345592 DOI: 10.1080/10408398.2020.1862045] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
The authentication and traceability of food attract more attention due to the increasing consumer awareness regarding nutrition and health, being a new hotspot of food science. Infrared spectroscopy (IRS) combined with shallow neural network has been widely proven to be an effective food analysis technology. As an advanced deep learning technology, deep neural network has also been explored to analyze and solve food-related IRS problems in recent years. The present review begins with brief introductions to IRS and artificial neural network (ANN), including shallow neural network and deep neural network. More notably, it emphasizes the comprehensive overview of the advances of the technology combined IRS with ANN for the authentication and traceability of food, based on relevant literature from 2014 to early 2020. In detail, the types of IRS and ANN, modeling processes, experimental results, and model comparisons in related studies are described to set forth the usage and performance of the combined technology for food analysis. The combined technology shows excellent ability to authenticate food quality and safety, involving chemical components, freshness, microorganisms, damages, toxic substances, and adulteration. As well, it shows excellent performance in the traceability of food variety and origin. The advantages, current limitations, and future trends of the combined technology are further discussed to provide a thoughtful viewpoint on the challenges and expectations of online applications for the authentication and traceability of food.
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Affiliation(s)
- Ning Liang
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou, China
| | - Sashuang Sun
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou, China
| | - Chu Zhang
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou, China
| | - Yong He
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou, China
| | - Zhengjun Qiu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou, China
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23
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Comprehensive Review on Application of FTIR Spectroscopy Coupled with Chemometrics for Authentication Analysis of Fats and Oils in the Food Products. Molecules 2020; 25:molecules25225485. [PMID: 33238638 PMCID: PMC7700317 DOI: 10.3390/molecules25225485] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 11/18/2020] [Accepted: 11/20/2020] [Indexed: 11/16/2022] Open
Abstract
Currently, the authentication analysis of edible fats and oils is an emerging issue not only by producers but also by food industries, regulators, and consumers. The adulteration of high quality and expensive edible fats and oils as well as food products containing fats and oils with lower ones are typically motivated by economic reasons. Some analytical methods have been used for authentication analysis of food products, but some of them are complex in sampling preparation and involving sophisticated instruments. Therefore, simple and reliable methods are proposed and developed for these authentication purposes. This review highlighted the comprehensive reports on the application of infrared spectroscopy combined with chemometrics for authentication of fats and oils. New findings of this review included (1) FTIR spectroscopy combined with chemometrics, which has been used to authenticate fats and oils; (2) due to as fingerprint analytical tools, FTIR spectra have emerged as the most reported analytical techniques applied for authentication analysis of fats and oils; (3) the use of chemometrics as analytical data treatment is a must to extract the information from FTIR spectra to be understandable data. Next, the combination of FTIR spectroscopy with chemometrics must be proposed, developed, and standardized for authentication and assuring the quality of fats and oils.
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Segelke T, von Wuthenau K, Kuschnereit A, Müller MS, Fischer M. Origin Determination of Walnuts ( Juglans regia L.) on a Worldwide and Regional Level by Inductively Coupled Plasma Mass Spectrometry and Chemometrics. Foods 2020; 9:E1708. [PMID: 33233794 PMCID: PMC7699883 DOI: 10.3390/foods9111708] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 11/12/2020] [Accepted: 11/18/2020] [Indexed: 11/17/2022] Open
Abstract
To counteract food fraud, this study aimed at the differentiation of walnuts on a global and regional level using an isotopolomics approach. Thus, the multi-elemental profiles of 237 walnut samples from ten countries and three years of harvest were analyzed with inductively coupled plasma mass spectrometry (ICP-MS), and the resulting element profiles were evaluated with chemometrics. Using support vector machine (SVM) for classification, validated by stratified nested cross validation, a prediction accuracy of 73% could be achieved. Leave-one-out cross validation was also applied for comparison and led to less satisfactory results because of the higher variations in sensitivity for distinct classes. Prediction was still possible using only elemental ratios instead of the absolute element concentrations; consequently, a drying step is not mandatory. In addition, the isotopolomics approach provided the classification of walnut samples on a regional level in France, Germany, and Italy, with accuracies of 91%, 77%, and 94%, respectively. The ratio of the model's accuracy to a random sample distribution was calculated, providing a new parameter with which to evaluate and compare the performance of classification models. The walnut cultivar and harvest year had no observable influence on the origin differentiation. Our results show the high potential of element profiling for the origin authentication of walnuts.
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Affiliation(s)
| | | | | | | | - Markus Fischer
- Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany; (T.S.); (K.v.W.); (A.K.); (M.-S.M.)
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Gao B, Xu S, Han L, Liu X. FT-IR-based quantitative analysis strategy for target adulterant in fish oil multiply adulterated with terrestrial animal lipid. Food Chem 2020; 343:128420. [PMID: 33143969 DOI: 10.1016/j.foodchem.2020.128420] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 08/27/2020] [Accepted: 10/14/2020] [Indexed: 11/15/2022]
Abstract
The interference of nontarget adulterant on FT-IR-based target adulterant quantitative analysis was explored and a sequential strategy was proposed to improve the prediction accuracy of the quantitative analysis model. Based on the FT-IR data of fish oil adulterated with terrestrial animal lipid, PLS and PLS-DA results show that quantitative analysis modeled by multiple and single adulteration data do not apply to each other; quantitative models based on the fusion of single and multiple adulteration data were established and showed a low quantitative analysis precision (higher RSD); and the sensitivity and specificity of discrimination analysis for multiply and singly adulterated fish oils both all exceed 0.910. To enhance the detection accuracy, a sequential strategy was proposed; identifying singly or multiply adulterated fish oil and then quantifying the content of adulterant was considered an efficient approach.
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Affiliation(s)
- Bing Gao
- College of Engineering, China Agricultural University, Beijing 100083, China.
| | - Shuai Xu
- College of Engineering, China Agricultural University, Beijing 100083, China.
| | - Lujia Han
- College of Engineering, China Agricultural University, Beijing 100083, China.
| | - Xian Liu
- College of Engineering, China Agricultural University, Beijing 100083, China.
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26
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Visible/near infrared spectroscopy and machine learning for predicting polyhydroxybutyrate production cultured on alkaline pretreated liquor from corn stover. ACTA ACUST UNITED AC 2020. [DOI: 10.1016/j.biteb.2020.100386] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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27
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Fourati M, Smaoui S, Ben Hlima H, Ennouri K, Chakchouk Mtibaa A, Sellem I, Elhadef K, Mellouli L. Synchronised interrelationship between lipid/protein oxidation analysis and sensory attributes in refrigerated minced beef meat formulated with
Punica granatum
peel extract. Int J Food Sci Technol 2019. [DOI: 10.1111/ijfs.14398] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Mariam Fourati
- Laboratory of Microorganisms and Biomolecules Center of Biotechnology of Sfax University of Sfax Road of Sidi Mansour Km 6, P. O. Box 1177 3018 Sfax Tunisia
| | - Slim Smaoui
- Laboratory of Microorganisms and Biomolecules Center of Biotechnology of Sfax University of Sfax Road of Sidi Mansour Km 6, P. O. Box 1177 3018 Sfax Tunisia
| | - Hajer Ben Hlima
- Algae Biotechnology Unit Biological Engineering Department National School of Engineers of Sfax University of Sfax Sfax 3038 Tunisia
| | - Karim Ennouri
- Laboratory of Microorganisms and Biomolecules Center of Biotechnology of Sfax University of Sfax Road of Sidi Mansour Km 6, P. O. Box 1177 3018 Sfax Tunisia
| | - Ahlem Chakchouk Mtibaa
- Laboratory of Microorganisms and Biomolecules Center of Biotechnology of Sfax University of Sfax Road of Sidi Mansour Km 6, P. O. Box 1177 3018 Sfax Tunisia
| | - Imen Sellem
- Laboratory of Microorganisms and Biomolecules Center of Biotechnology of Sfax University of Sfax Road of Sidi Mansour Km 6, P. O. Box 1177 3018 Sfax Tunisia
| | - Khaoula Elhadef
- Laboratory of Microorganisms and Biomolecules Center of Biotechnology of Sfax University of Sfax Road of Sidi Mansour Km 6, P. O. Box 1177 3018 Sfax Tunisia
| | - Lotfi Mellouli
- Laboratory of Microorganisms and Biomolecules Center of Biotechnology of Sfax University of Sfax Road of Sidi Mansour Km 6, P. O. Box 1177 3018 Sfax Tunisia
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Bergamaschi M, Cipolat-Gotet C, Cecchinato A, Schiavon S, Bittante G. Chemometric authentication of farming systems of origin of food (milk and ripened cheese) using infrared spectra, fatty acid profiles, flavor fingerprints, and sensory descriptions. Food Chem 2019; 305:125480. [PMID: 31522125 DOI: 10.1016/j.foodchem.2019.125480] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 09/03/2019] [Accepted: 09/04/2019] [Indexed: 12/21/2022]
Abstract
Milk samples from 1264 cows in 85 farms were authenticated for different farming-systems using a 10-fold cross-validated linear-discriminant-analysis using Fourier-transform infrared spectra (FTIRS) and gas-chromatographic fatty-acid (FA) profiles. FTIRS gave correct classification greater than FAs (97.4% vs. 81.1%) during calibration, but slightly worse in validation (73.5% vs 77.3%) and their combination improved the results. All milk samples were processed into ripened model-cheeses, and analyzed by near-infrared-spectrometry (NIRS), by proton-transfer-reaction time-of-flight mass-spectrometry for their volatile organic compound (VOCs) fingerprint and by panel sensory profiling (SENS). Farming-system authentication on cheese samples was less efficient than on milk, but still possible. The instrumental methods yielded similar validation results, better than SENS, and their combination improved the correct classification rate. The efficiency of the different technics was affected by specific farming systems. In conclusion, dairy products could be discriminated for farming-systems with acceptable accuracy, but the methods tested differ in sampling procedure, rapidity and costs.
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Affiliation(s)
- Matteo Bergamaschi
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy
| | - Claudio Cipolat-Gotet
- Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy
| | - Alessio Cecchinato
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy.
| | - Stefano Schiavon
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy
| | - Giovanni Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy
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Martín-Torres S, Jiménez-Carvelo AM, González-Casado A, Cuadros-Rodríguez L. Differentiation of avocados according to their botanical variety using liquid chromatographic fingerprinting and multivariate classification tree. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2019; 99:4932-4941. [PMID: 30953356 DOI: 10.1002/jsfa.9725] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 03/31/2019] [Accepted: 04/01/2019] [Indexed: 06/09/2023]
Abstract
BACKGROUND The oil content, composition and marketing threshold value of an avocado depends on the cultivar hence, identifying the cultivar of the avocado fruit is desirable. However, analytical methods have not been reported with this aim. RESULTS A multivariate classification tree method was proposed to discriminate three commercial botanical varieties of avocado: Hass, Fuerte and Bacon, using high-performance liquid chromatography coupled to a charged aerosol detector (HPLC-CAD). Prior to the chromatographic analysis the avocados were lyophilized and then the oil fraction was extracted using a pressurized liquid extraction system. Normal and reverse phase liquid chromatography were applied in order to obtain the chromatographic fingerprint for each sample. Soft independent modelling of class analogies (SIMCA) and partial least-squares discriminant analysis (PLS-DA) were applied. Classification quality metrics were determined to evaluate the performance of the classification. Several strategies to develop the classification models were employed. Finally, the useful application of 'classification trees' methodology, which has been scarcely applied in the field of analytical food control, was evaluated to perform a multiclass classification. CONCLUSION Discrimination of the three botanical varieties was achieved. The best classification was obtained when the PLS-DA is applied on the normal-phase chromatographic fingerprints. Classification trees are showed to be useful tools that provide complementary information to single concatenated models showing different results from the same prediction sample set. © 2019 Society of Chemical Industry.
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30
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Soon J, Krzyzaniak S, Shuttlewood Z, Smith M, Jack L. Food fraud vulnerability assessment tools used in food industry. Food Control 2019. [DOI: 10.1016/j.foodcont.2019.03.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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31
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Characterization and discrimination of selected China's domestic pork using an LC-MS-based lipidomics approach. Food Control 2019. [DOI: 10.1016/j.foodcont.2019.02.001] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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32
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Campmajó G, Navarro GJ, Núñez N, Puignou L, Saurina J, Núñez O. Non-Targeted HPLC-UV Fingerprinting as Chemical Descriptors for the Classification and Authentication of Nuts by Multivariate Chemometric Methods. SENSORS (BASEL, SWITZERLAND) 2019; 19:E1388. [PMID: 30901822 PMCID: PMC6471388 DOI: 10.3390/s19061388] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 03/18/2019] [Accepted: 03/19/2019] [Indexed: 01/07/2023]
Abstract
Recently, the authenticity of food products has become a great social concern. Considering the complexity of the food chain and that many players are involved between production and consumption; food adulteration practices are rising as it is easy to conduct fraud without being detected. This is the case for nut fruit processed products, such as almond flours, that can be adulterated with cheaper nuts (hazelnuts or peanuts), giving rise to not only economic fraud but also important effects on human health. Non-targeted HPLC-UV chromatographic fingerprints were evaluated as chemical descriptors to achieve nut sample characterization and classification using multivariate chemometric methods. Nut samples were extracted by sonication and centrifugation, and defatted with hexane; extracting procedure and conditions were optimized to maximize the generation of enough discriminant features. The obtained HPLC-UV chromatographic fingerprints were then analyzed by means of principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) to carry out the classification of nut samples. The proposed methodology allowed the classification of samples not only according to the type of nut but also based on the nut thermal treatment employed (natural, fried or toasted products).
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Affiliation(s)
- Guillem Campmajó
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès, 1-11, E08028 Barcelona, Spain.
| | - Gemma J Navarro
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès, 1-11, E08028 Barcelona, Spain.
| | - Nerea Núñez
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès, 1-11, E08028 Barcelona, Spain.
| | - Lluís Puignou
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès, 1-11, E08028 Barcelona, Spain.
- Research Institute in Food Nutrition and Food Safety, University of Barcelona, Recinte Torribera, Av. Prat de la Riba 171, Edifici de Recerca (Gaudí), Santa Coloma de Gramenet, E08921 Barcelona, Spain.
| | - Javier Saurina
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès, 1-11, E08028 Barcelona, Spain.
- Research Institute in Food Nutrition and Food Safety, University of Barcelona, Recinte Torribera, Av. Prat de la Riba 171, Edifici de Recerca (Gaudí), Santa Coloma de Gramenet, E08921 Barcelona, Spain.
| | - Oscar Núñez
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès, 1-11, E08028 Barcelona, Spain.
- Research Institute in Food Nutrition and Food Safety, University of Barcelona, Recinte Torribera, Av. Prat de la Riba 171, Edifici de Recerca (Gaudí), Santa Coloma de Gramenet, E08921 Barcelona, Spain.
- Serra Húnter Fellow, Generalitat de Catalunya, Rambla de Catalunya 19-21, E08007 Barcelona, Spain.
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Dasenaki ME, Thomaidis NS. Quality and Authenticity Control of Fruit Juices-A Review. Molecules 2019; 24:E1014. [PMID: 30871258 PMCID: PMC6470824 DOI: 10.3390/molecules24061014] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 03/08/2019] [Accepted: 03/09/2019] [Indexed: 12/22/2022] Open
Abstract
Food fraud, being the act of intentional adulteration of food for financial advantage, has vexed the consumers and the food industry throughout history. According to the European Committee on the Environment, Public Health and Food Safety, fruit juices are included in the top 10 food products that are most at risk of food fraud. Therefore, reliable, efficient, sensitive and cost-effective analytical methodologies need to be developed continuously to guarantee fruit juice quality and safety. This review covers the latest advances in the past ten years concerning the targeted and non-targeted methodologies that have been developed to assure fruit juice authenticity and to preclude adulteration. Emphasis is placed on the use of hyphenated techniques and on the constantly-growing role of MS-based metabolomics in fruit juice quality control area.
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Affiliation(s)
- Marilena E Dasenaki
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771 Athens, Greece.
| | - Nikolaos S Thomaidis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771 Athens, Greece.
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Hatzakis E. Nuclear Magnetic Resonance (NMR) Spectroscopy in Food Science: A Comprehensive Review. Compr Rev Food Sci Food Saf 2018; 18:189-220. [PMID: 33337022 DOI: 10.1111/1541-4337.12408] [Citation(s) in RCA: 135] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 09/28/2018] [Accepted: 10/18/2018] [Indexed: 12/15/2022]
Abstract
Nuclear magnetic resonance (NMR) spectroscopy is a robust method, which can rapidly analyze mixtures at the molecular level without requiring separation and/or purification steps, making it ideal for applications in food science. Despite its increasing popularity among food scientists, NMR is still an underutilized methodology in this area, mainly due to its high cost, relatively low sensitivity, and the lack of NMR expertise by many food scientists. The aim of this review is to help bridge the knowledge gap that may exist when attempting to apply NMR methodologies to the field of food science. We begin by covering the basic principles required to apply NMR to the study of foods and nutrients. A description of the discipline of chemometrics is provided, as the combination of NMR with multivariate statistical analysis is a powerful approach for addressing modern challenges in food science. Furthermore, a comprehensive overview of recent and key applications in the areas of compositional analysis, food authentication, quality control, and human nutrition is provided. In addition to standard NMR techniques, more sophisticated NMR applications are also presented, although limitations, gaps, and potentials are discussed. We hope this review will help scientists gain some of the knowledge required to apply the powerful methodology of NMR to the rich and diverse field of food science.
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Affiliation(s)
- Emmanuel Hatzakis
- Dept. of Food Science and Technology, The Ohio State Univ., Parker Building, 2015 Fyffe Rd., Columbus, OH, U.S.A.,Foods for Health Discovery Theme, The Ohio State Univ., Parker Building, 2015 Fyffe Rd., Columbus, OH, U.S.A
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