1
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Dewantier GR, Torley PJ, Blanch EW. Identifying Chemical Differences in Cheddar Cheese Based on Maturity Level and Manufacturer Using Vibrational Spectroscopy and Chemometrics. Molecules 2023; 28:8051. [PMID: 38138541 PMCID: PMC10745544 DOI: 10.3390/molecules28248051] [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: 10/23/2023] [Revised: 12/03/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
Cheese is a nutritious dairy product and a valuable commodity. Internationally, cheddar cheese is produced and consumed in large quantities, and it is the main cheese variety that is exported from Australia. Despite its importance, the analytical methods to that are used to determine cheese quality rely on traditional approaches that require time, are invasive, and which involve potentially hazardous chemicals. In contrast, spectroscopic techniques can rapidly provide molecular information and are non-destructive, fast, and chemical-free methods. Combined with partner recognition methods (chemometrics), they can identify small changes in the composition or condition of cheeses. In this work, we combined FTIR and Raman spectroscopies with principal component analysis (PCA) to investigate the effects of aging in commercial cheddar cheeses. Changes in the amide I and II bands were the main spectral characteristics responsible for classifying commercial cheddar cheeses based on the ripening time and manufacturer using FTIR, and bands from lipids, including β'-polymorph of fat crystals, were more clearly determined through changes in the Raman spectra.
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Affiliation(s)
- Gerson R. Dewantier
- Applied Chemistry and Environmental Science, School of Science, Royal Melbourne Institute of Technology University, Melbourne, VIC 3001, Australia;
| | - Peter J. Torley
- Biosciences and Food Technology, School of Science, Royal Melbourne Institute of Technology University, Bundoora, VIC 3083, Australia;
| | - Ewan W. Blanch
- Applied Chemistry and Environmental Science, School of Science, Royal Melbourne Institute of Technology University, Melbourne, VIC 3001, Australia;
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2
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Anwar H, Anwar T, Murtaza S. Review on food quality assessment using machine learning and electronic nose system. BIOSENSORS AND BIOELECTRONICS: X 2023; 14:100365. [DOI: 10.1016/j.biosx.2023.100365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
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3
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Liu T, Tian Y, Cao Y, Wang Z, Zha G, Liu W, Wei L, Xiao H, Zhang Q, Cao C. Isoelectric point barcode and similarity analysis with the earth mover's distance for identification of species origin of raw meat. Food Res Int 2023; 166:112600. [PMID: 36914325 DOI: 10.1016/j.foodres.2023.112600] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 02/07/2023] [Accepted: 02/14/2023] [Indexed: 02/20/2023]
Abstract
In this work, by combining the microcolumn isoelectric focusing (mIEF) and similarity analysis with the earth mover's distance (EMD) metric, we proposed the concept of isoelectric point (pI) barcode for the identification of species origin of raw meat. At first, we used the mIEF to analyze 14 meat species, including 8 species of livestock and 6 species of poultry, to generate 140 electropherograms of myoglobin/hemoglobin (Mb/Hb) markers. Secondly, we binarized the electropherograms and converted them into the pI barcodes that only showed the major Mb/Hb bands for the EMD analysis. Thirdly, we efficiently developed the barcode database of 14 meat species and successfully used the EMD method to identify 9 meat products thanks to the high throughput of mIEF and the simplified format of the barcode for similarity analysis. The developed method had the merits of facility, rapidity and low cost. The developed concept and method had evident potential to the facile identification of meat species.
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Affiliation(s)
- Tian Liu
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Youli Tian
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; School of Life Sciences and Biotechnology, State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yiren Cao
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zihao Wang
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Genhan Zha
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; School of Life Sciences and Biotechnology, State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Weiwen Liu
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Li Wei
- Shanghai 6(th) People's Hospital, Shanghai Jiao Tong University, Shanghai 200233, China
| | - Hua Xiao
- School of Life Sciences and Biotechnology, State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Qiang Zhang
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; School of Life Sciences and Biotechnology, State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Chengxi Cao
- School of Life Sciences and Biotechnology, State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai 200240, China; Shanghai 6(th) People's Hospital, Shanghai Jiao Tong University, Shanghai 200233, China.
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4
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Chen R, Liu F, Zhang C, Wang W, Yang R, Zhao Y, Peng J, Kong W, Huang J. Trends in digital detection for the quality and safety of herbs using infrared and Raman spectroscopy. FRONTIERS IN PLANT SCIENCE 2023; 14:1128300. [PMID: 37025139 PMCID: PMC10072231 DOI: 10.3389/fpls.2023.1128300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 02/27/2023] [Indexed: 06/19/2023]
Abstract
Herbs have been used as natural remedies for disease treatment, prevention, and health care. Some herbs with functional properties are also used as food or food additives for culinary purposes. The quality and safety inspection of herbs are influenced by various factors, which need to be assessed in each operation across the whole process of herb production. Traditional analysis methods are time-consuming and laborious, without quick response, which limits industry development and digital detection. Considering the efficiency and accuracy, faster, cheaper, and more environment-friendly techniques are highly needed to complement or replace the conventional chemical analysis methods. Infrared (IR) and Raman spectroscopy techniques have been applied to the quality control and safety inspection of herbs during the last several decades. In this paper, we generalize the current application using IR and Raman spectroscopy techniques across the whole process, from raw materials to patent herbal products. The challenges and remarks were proposed in the end, which serve as references for improving herb detection based on IR and Raman spectroscopy techniques. Meanwhile, make a path to driving intelligence and automation of herb products factories.
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Affiliation(s)
- Rongqin Chen
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China
| | - Fei Liu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China
| | - Chu Zhang
- School of Information Engineering, Huzhou University, Huzhou, China
| | - Wei Wang
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China
| | - Rui Yang
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China
| | - Yiying Zhao
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China
| | - Jiyu Peng
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Wenwen Kong
- College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou, China
| | - Jing Huang
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China
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5
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Liu Q, Dong P, Fengou LC, Nychas GJ, Fowler SM, Mao Y, Luo X, Zhang Y. Preliminary investigation into the prediction of indicators of beef spoilage using Raman and Fourier transform infrared spectroscopy. Meat Sci 2023; 200:109168. [PMID: 36963260 DOI: 10.1016/j.meatsci.2023.109168] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 03/13/2023] [Accepted: 03/16/2023] [Indexed: 03/22/2023]
Abstract
The objective of this study was to assess the potential to predict the microbial beef spoilage indicators by Raman and Fourier transform infrared (FT-IR) spectroscopies. Vacuum skin packaged (VSP) beef steaks were stored at 0 °C, 4 °C, 8 °C and under a dynamic temperature condition (0 °C ∼ 4 °C ∼ 8 °C, for 36 d). Total viable count (TVC) and total volatile basic nitrogen (TVB-N) were obtained during the storage period along with spectroscopic data. The Raman and FTIR spectra were baseline corrected, pre-processed using Savitzky-Golay smoothing and normalized. Subsequently partial least squares regression (PLSR) models of TVC and TVB-N were developed and evaluated. The root mean squared error (RMSE) ranged from 0.81 to1.59 (log CFU/g or mg/100 g) and the determination coefficient (R2) from 0.54 to 0.75. The performance of PLSR model based on data fusion (combination of Raman and FT-IR data) is better than that based on Raman spectra and similar to that of FT-IR. Overall, Raman spectroscopy, FT-IR spectroscopy, and a combination of both exhibited a potential for the prediction of the beef spoilage.
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Affiliation(s)
- Qingsen Liu
- Lab of Beef Processing and Quality Control, College of Food Science and Engineering, Shandong Agricultural University, Tai'an, Shandong 271018, PR China
| | - Pengcheng Dong
- Lab of Beef Processing and Quality Control, College of Food Science and Engineering, Shandong Agricultural University, Tai'an, Shandong 271018, PR China.
| | - Lemonia-Christina Fengou
- Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food and Nutritional Sciences, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece.
| | - George-John Nychas
- Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food and Nutritional Sciences, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece.
| | - Stephanie Marie Fowler
- NSW Department of Primary Industries, Centre for Red Meat and Sheep Development, PO Box 129, Cowra, NSW 2794, Australia.
| | - Yanwei Mao
- Lab of Beef Processing and Quality Control, College of Food Science and Engineering, Shandong Agricultural University, Tai'an, Shandong 271018, PR China.
| | - Xin Luo
- Lab of Beef Processing and Quality Control, College of Food Science and Engineering, Shandong Agricultural University, Tai'an, Shandong 271018, PR China.
| | - Yimin Zhang
- Lab of Beef Processing and Quality Control, College of Food Science and Engineering, Shandong Agricultural University, Tai'an, Shandong 271018, PR China.
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6
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Decker C, Krapf R, Kuballa T, Bunzel M. Differentiation of meat species of raw and processed meat based on polar metabolites using 1H NMR spectroscopy combined with multivariate data analysis. Front Nutr 2022; 9:985797. [PMID: 36245505 PMCID: PMC9566576 DOI: 10.3389/fnut.2022.985797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 09/07/2022] [Indexed: 11/13/2022] Open
Abstract
Meat species of raw meat and processed meat products were investigated by 1H NMR spectroscopy with subsequent multivariate data analysis. Sample preparation was based on aqueous extraction combined with ultrafiltration in order to reduce macromolecular components in the extracts. 1H NMR data was analyzed by using a non-targeted approach followed by principal component analysis (PCA), linear discrimination analysis (LDA), and cross-validation (CV) embedded in a Monte Carlo (MC) resampling approach. A total of 379 raw meat samples (pork, beef, poultry, and lamb) and 81 processed meat samples (pork, beef, poultry) were collected between the years 2018 and 2021. A 99% correct prediction rate was achieved if the raw meat samples were classified according to meat species. Predicting processed meat products was slightly less successful (93 %) with this approach. Furthermore, identification of spectral regions that are relevant for the classification via polar chemical markers was performed. Finally, data on polar metabolites were fused with previously published 1H NMR data on non-polar metabolites in order to build a broader classification model and to improve prediction accuracy.
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Affiliation(s)
- Christina Decker
- Karlsruhe Institute of Technology (KIT), Department of Food Chemistry and Phytochemistry, Karlsruhe, Germany
- Chemisches und Veterinäruntersuchungsamt Karlsruhe, Karlsruhe, Germany
| | - Reiner Krapf
- Bosch Power Tools, Leinfelden-Echterdingen, Germany
| | - Thomas Kuballa
- Chemisches und Veterinäruntersuchungsamt Karlsruhe, Karlsruhe, Germany
| | - Mirko Bunzel
- Karlsruhe Institute of Technology (KIT), Department of Food Chemistry and Phytochemistry, Karlsruhe, Germany
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7
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Cristea G, Voica C, Feher I, Puscas R, Magdas DA. Isotopic and elemental characterization of Romanian pork meat in corroboration with advanced chemometric methods: A first exploratory study. Meat Sci 2022; 189:108825. [PMID: 35461107 DOI: 10.1016/j.meatsci.2022.108825] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 04/03/2022] [Accepted: 04/06/2022] [Indexed: 11/23/2022]
Abstract
In this study 93 pork meat samples (tenderloin) were analyzed via isotope ratios mass spectrometry (δ2H, δ18O, δ13C) and inductively coupled plasma - Mass spectrometry (55 elements). The meat samples are coming from Romania and abroad. Those from Romania are originating from conventional farms and yard rearing system. The analytical results in conjunction with linear discriminant analysis (LDA) and artificial neural networks (ANNs) were used to assess: The geographical origin, and animal diet. The most powerful markers which could differentiate pork meat samples concerning the geographical origin were δ18O, terbium, and tin. The results of chemometric models showed that, along with 13C signature, rubidium concentration, and a few rare earth-elements (lanthanum, and cerium) were efficient to discriminate animal diet in a percent of 97.8% (initial classification) and 94.6% (cross-validation), respectively. Some of predictors for feeding regime differentiation by using LDA were identified also to be the best markers to distinguish corn-based diet by using ANNs (δ13C, Rb, La).
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Affiliation(s)
- Gabriela Cristea
- National Institute for Research, Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
| | - Cezara Voica
- National Institute for Research, Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania.
| | - Ioana Feher
- National Institute for Research, Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania.
| | - Romulus Puscas
- National Institute for Research, Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
| | - Dana Alina Magdas
- National Institute for Research, Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
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8
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Lestari D, Rohman A, Syofyan S, Yuliana ND, Abu Bakar NKB, Hamidi D. Analysis of beef meatballs with rat meat adulteration using Fourier Transform Infrared (FTIR) spectroscopy in combination with chemometrics. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2022. [DOI: 10.1080/10942912.2022.2083637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Dwi Lestari
- Faculty of Pharmacy, Universitas Andalas, Padang, Indonesia
- Faculty of Pharmacy, Universitas Muhammadiyah Kalimantan Timur, Samarinda, Indonesia
| | - Abdul Rohman
- Center of Excellence, Institute for Halal Industry and Systems, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | | | - Nancy Dewi Yuliana
- Department of Food Science and Technology, IPB University, Bogor, Indonesia
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9
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Sangaré M, Karoui R. Evaluation and monitoring of the quality of sausages by different analytical techniques over the last five years. Crit Rev Food Sci Nutr 2022; 63:8136-8160. [PMID: 35333686 DOI: 10.1080/10408398.2022.2053059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Sausages are among the most vulnerable and perishable products, although those products are an important source of essential nutrients for human organisms. The evaluation of the quality of sausages becomes more and more required by consumers, producers, and authorities to thwarter falsification. Numerous analytical techniques including chemical, sensory, chromatography, and so on, are employed for the determination of the quality and authenticity of sausages. These methods are expensive and time consuming, and are often sensitive to significant sources of variation. Therefore, rapid analytical techniques such as fluorescence spectroscopy, near infrared (NIR), mid infrared (MIR), nuclear magnetic resonance (NMR), among others were considered helpful tools in this domain. This review will identify current gaps related to different analytical techniques in assessing and monitoring the quality of sausages and discuss the drawbacks of existing analytical methods regarding the quality and authenticity of sausages from 2015 up to now.
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Affiliation(s)
- Moriken Sangaré
- Univ. Artois, Univ. Lille, Univ. Littoral Côte d'Opale, Univ. Picardie Jules Verne, Univ. de Liège, INRAE, BioEcoAgro, Lens, France
- Institut Supérieur des Sciences et Médecine Vétérinaire de Dalaba, Département de Technologie et Contrôle des Produits Alimentaires, DTCPA, ISSMV/Dalaba, Guinée
- Univ. Gamal Abdel Nasser de Conakry, Guinée, Uganc, Guinée
| | - Romdhane Karoui
- Univ. Artois, Univ. Lille, Univ. Littoral Côte d'Opale, Univ. Picardie Jules Verne, Univ. de Liège, INRAE, BioEcoAgro, Lens, France
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10
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Huang C, Gu Y. A Machine Learning Method for the Quantitative Detection of Adulterated Meat Using a MOS-Based E-Nose. Foods 2022; 11:foods11040602. [PMID: 35206078 PMCID: PMC8870927 DOI: 10.3390/foods11040602] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 02/08/2022] [Accepted: 02/17/2022] [Indexed: 12/28/2022] Open
Abstract
Meat adulteration is a global problem which undermines market fairness and harms people with allergies or certain religious beliefs. In this study, a novel framework in which a one-dimensional convolutional neural network (1DCNN) serves as a backbone and a random forest regressor (RFR) serves as a regressor, named 1DCNN-RFR, is proposed for the quantitative detection of beef adulterated with pork using electronic nose (E-nose) data. The 1DCNN backbone extracted a sufficient number of features from a multichannel input matrix converted from the raw E-nose data. The RFR improved the regression performance due to its strong prediction ability. The effectiveness of the 1DCNN-RFR framework was verified by comparing it with four other models (support vector regression model (SVR), RFR, backpropagation neural network (BPNN), and 1DCNN). The proposed 1DCNN-RFR framework performed best in the quantitative detection of beef adulterated with pork. This study indicated that the proposed 1DCNN-RFR framework could be used as an effective tool for the quantitative detection of meat adulteration.
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Affiliation(s)
- Changquan Huang
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;
| | - Yu Gu
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
- Guangdong Province Key Laboratory of Petrochemical Equipment Fault Diagnosis, Guangdong University of Petrochemical Technology, Maoming 525000, China
- Department of Chemistry, Institute of Inorganic and Analytical Chemistry, Goethe-University, Max-von-Laue-Str. 9, 60438 Frankfurt, Germany
- Correspondence:
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11
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Modern on-site tool for monitoring contamination of halal meat with products from five non-halal animals using multiplex polymerase chain reaction coupled with DNA strip. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108540] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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12
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Selamat J, Rozani NAA, Murugesu S. Application of the Metabolomics Approach in Food Authentication. Molecules 2021; 26:molecules26247565. [PMID: 34946647 PMCID: PMC8706891 DOI: 10.3390/molecules26247565] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/28/2021] [Accepted: 11/03/2021] [Indexed: 02/04/2023] Open
Abstract
The authentication of food products is essential for food quality and safety. Authenticity assessments are important to ensure that the ingredients or contents of food products are legitimate and safe to consume. The metabolomics approach is an essential technique that can be utilized for authentication purposes. This study aimed to summarize food authentication through the metabolomics approach, to study the existing analytical methods, instruments, and statistical methods applied in food authentication, and to review some selected food commodities authenticated using metabolomics-based methods. Various databases, including Google Scholar, PubMed, Scopus, etc., were used to obtain previous research works relevant to the objectives. The review highlights the role of the metabolomics approach in food authenticity. The approach is technically implemented to ensure consumer protection through the strict inspection and enforcement of food labeling. Studies have shown that the study of metabolomics can ultimately detect adulterant(s) or ingredients that are added deliberately, thus compromising the authenticity or quality of food products. Overall, this review will provide information on the usefulness of metabolomics and the techniques associated with it in successful food authentication processes, which is currently a gap in research that can be further explored and improved.
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Affiliation(s)
- Jinap Selamat
- Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang 43400, Malaysia;
- Institute of Tropical Agriculture and Food Security (ITAFoS), Universiti Putra Malaysia, Serdang 43400, Malaysia;
- Correspondence: or ; Tel.: +603-97691146
| | | | - Suganya Murugesu
- Institute of Tropical Agriculture and Food Security (ITAFoS), Universiti Putra Malaysia, Serdang 43400, Malaysia;
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Zhang T, Chen C, Xie K, Wang J, Pan Z. Current State of Metabolomics Research in Meat Quality Analysis and Authentication. Foods 2021; 10:2388. [PMID: 34681437 PMCID: PMC8535928 DOI: 10.3390/foods10102388] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 12/23/2022] Open
Abstract
In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.
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Affiliation(s)
- Tao Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.Z.); (C.C.); (K.X.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
| | - Can Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.Z.); (C.C.); (K.X.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
| | - Kaizhou Xie
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.Z.); (C.C.); (K.X.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
| | - Jinyu Wang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.Z.); (C.C.); (K.X.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
| | - Zhiming Pan
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
- Jiangsu Key Laboratory of Zoonosis, Key Laboratory of Prevention and Control of Biological Hazard Factors (Animal Origin) for Agrifood Safety and Quality, Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Yangzhou University, Yangzhou 225009, China
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14
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Recent advances in assessing qualitative and quantitative aspects of cereals using nondestructive techniques: A review. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2021.08.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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15
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Fast label-free identification of bacteria by synchronous fluorescence of amino acids. Anal Bioanal Chem 2021; 413:6857-6866. [PMID: 34491394 DOI: 10.1007/s00216-021-03642-8] [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] [Received: 07/12/2021] [Revised: 08/28/2021] [Accepted: 08/30/2021] [Indexed: 10/20/2022]
Abstract
Fast identification of pathogenic bacteria is an essential need for patient's diagnostic in hospitals and environmental monitoring of water and air quality. Bacterial cells consist of a very high amount of biological molecules whose content changes in response to different environmental conditions. The similarity between the molecular compositions of different bacterial cells limits the possibility to find unique markers to enable differentiation among species. Although many biological molecules in the cells absorb at the UV-Vis region, only a few of them can be detected in whole cells by their intrinsic fluorescence. Among these molecules are the amino acids phenylalanine, tyrosine, and tryptophan. In this work, we develop a rapid method for bacterial identification by synchronous fluorescence. We show that we can quantify the concentration for the 3 amino acids without any significant interference from other fluorophores in the cells and that we can differentiate among 6 pathogenic bacterial species by using the concentrations of their amino acids as a bacterial fingerprint. Fluorescent amino acids exist in all living cells. Therefore, this method has the potential to be applicative for the rapid identification of cells from all kinds of organisms.
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16
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Hassan N, Ahmad T, Ashaari A, Awang SR, Mamat SS, Wan Mohamad WM, Ahmad Fuad AA. A fuzzy graph approach analysis for COVID-19 outbreak. RESULTS IN PHYSICS 2021; 25:104267. [PMID: 33968605 PMCID: PMC8093164 DOI: 10.1016/j.rinp.2021.104267] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 04/17/2021] [Accepted: 04/26/2021] [Indexed: 06/12/2023]
Abstract
Complex systems require rigorous analysis using effective method, in order to handle and interpret their information. Spectrum produced from Fourier transform infrared (FTIR) instrument is an example of a complex system, due to their overlapped bands and interactions within the spectrum. Thus, chemometrics techniques are required to further analyze the data, in particular, chemometrics fuzzy autocatalytic set (c-FACS). The c-FACS is initially used to analyze the FTIR spectra of gelatins. However, in this study, the c-FACS is generalized and implemented for analysis of Coronavirus disease 2019 (Covid-19), particularly, the pandemic outbreak in Malaysia. The daily Covid-19 cases in states in Malaysia are modeled and analyzed using c-FACS, to observe the trend and severity of the disease in Malaysia. As a result, the classification of severity of zones in Malaysia are identified. The obtained results offer descriptive insight for strategizing purposes in combating the Covid-19 outbreak in Malaysia.
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Affiliation(s)
- Nurfarhana Hassan
- Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
| | - Tahir Ahmad
- Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
| | - Azmirul Ashaari
- Azman Hashim International Business School, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
| | - Siti Rahmah Awang
- Azman Hashim International Business School, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
| | - Siti Salwana Mamat
- Centre of Foundation Studies, Universiti Teknologi MARA Selangor Dengkil Campus, 43800 Dengkil, Selangor, Malaysia
| | - Wan Munirah Wan Mohamad
- Department of Mathematics, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Johor Branch, Pasir Gudang Campus, Jalan Purnama, Bandar Seri Alam, 81750 Masai, Johor, Malaysia
| | - Amirul Aizad Ahmad Fuad
- Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
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Acciaro M, Decandia M, Sitzia M, Manca C, Giovanetti V, Cabiddu A, Addis M, Rassu SPG, Molle G, Dimauro C. Discriminant analysis as a tool to identify bovine and ovine meat produced from pasture or stall-fed animals. ITALIAN JOURNAL OF ANIMAL SCIENCE 2020. [DOI: 10.1080/1828051x.2020.1816507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Corrado Dimauro
- Dipartimento di Agraria, Università di Sassari, Sassari, Italy
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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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19
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Authentication and Quality Assessment of Meat Products by Fourier-Transform Infrared (FTIR) Spectroscopy. FOOD ENGINEERING REVIEWS 2020. [DOI: 10.1007/s12393-020-09251-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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20
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Abstract
AbstractThere is a growing need for chemical analyses to be performed in the field, at the point of need. Tools and techniques often found in analytical chemistry laboratories are necessary in performing these analyses, yet have, historically, been unable to do so owing to their size, cost and complexity. Technical advances in miniaturisation and liquid chromatography are enabling the translation of these techniques out of the laboratory, and into the field. Here we examine the advances that are enabling portable liquid chromatography (LC). We explore the evolution of portable instrumentation from its inception to the most recent advances, highlighting the trends in the field and discussing the necessary criteria for developing in-field solutions. While instrumentation is becoming more capable it has yet to find adoption outside of research.
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Rohman A, Windarsih A. The Application of Molecular Spectroscopy in Combination with Chemometrics for Halal Authentication Analysis: A Review. Int J Mol Sci 2020; 21:E5155. [PMID: 32708254 PMCID: PMC7403989 DOI: 10.3390/ijms21145155] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 04/25/2020] [Accepted: 04/29/2020] [Indexed: 12/18/2022] Open
Abstract
Halal is an Arabic term used to describe any components allowed to be used in any products by Muslim communities. Halal food and halal pharmaceuticals are any food and pharmaceuticals which are safe and allowed to be consumed according to Islamic law (Shariah). Currently, in line with halal awareness, some Muslim countries such as Indonesia, Malaysia, and Middle East regions have developed some standards and regulations on halal products and halal certification. Among non-halal components, the presence of pig derivatives (lard, pork, and porcine gelatin) along with other non-halal meats (rat meat, wild boar meat, and dog meat) is typically found in food and pharmaceutical products. This review updates the recent application of molecular spectroscopy, including ultraviolet-visible, infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies, in combination with chemometrics of multivariate analysis, for analysis of non-halal components in food and pharmaceutical products. The combination of molecular spectroscopic-based techniques and chemometrics offers fast and reliable methods for screening the presence of non-halal components of pig derivatives and non-halal meats in food and pharmaceutical products.
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Affiliation(s)
- Abdul Rohman
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Institute of Halal Industry and Systems (IHIS), Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
| | - Anjar Windarsih
- Research Division for Natural Product Technology (BPTBA), Indonesian Institute of Sciences (LIPI), Yogyakarta 55861, Indonesia
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Li YC, Liu SY, Meng FB, Liu DY, Zhang Y, Wang W, Zhang JM. Comparative review and the recent progress in detection technologies of meat product adulteration. Compr Rev Food Sci Food Saf 2020; 19:2256-2296. [PMID: 33337107 DOI: 10.1111/1541-4337.12579] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 05/06/2020] [Accepted: 05/06/2020] [Indexed: 12/11/2022]
Abstract
Meat adulteration, mainly for the purpose of economic pursuit, is widespread and leads to serious public health risks, religious violations, and moral loss. Rapid, effective, accurate, and reliable detection technologies are keys to effectively supervising meat adulteration. Considering the importance and rapid advances in meat adulteration detection technologies, a comprehensive review to summarize the recent progress in this area and to suggest directions for future progress is beneficial. In this review, destructive meat adulteration technologies based on DNA, protein, and metabolite analyses and nondestructive technologies based on spectroscopy were comparatively analyzed. The advantages and disadvantages, application situations of these technologies were discussed. In the future, determining suitable indicators or markers is particularly important for destructive methods. To improve sensitivity and save time, new interdisciplinary technologies, such as biochips and biosensors, are promising for application in the future. For nondestructive techniques, convenient and effective chemometric models are crucial, and the development of portable devices based on these technologies for onsite monitoring is a future trend. Moreover, omics technologies, especially proteomics, are important methods in laboratory detection because they enable multispecies detection and unknown target screening by using mass spectrometry databases.
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Affiliation(s)
- Yun-Cheng Li
- College of Pharmacy and Biological Engineering, Chengdu University, Chengdu, China.,Key Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China
| | - Shu-Yan Liu
- College of Pharmacy and Biological Engineering, Chengdu University, Chengdu, China
| | - Fan-Bing Meng
- College of Pharmacy and Biological Engineering, Chengdu University, Chengdu, China.,Key Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China
| | - Da-Yu Liu
- College of Pharmacy and Biological Engineering, Chengdu University, Chengdu, China.,Key Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China
| | - Yin Zhang
- College of Pharmacy and Biological Engineering, Chengdu University, Chengdu, China.,Key Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China
| | - Wei Wang
- Key Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China
| | - Jia-Min Zhang
- Key Laboratory of Meat Processing of Sichuan Province, Chengdu University, Chengdu, China
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23
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Zia Q, Alawami M, Mokhtar NFK, Nhari RMHR, Hanish I. Current analytical methods for porcine identification in meat and meat products. Food Chem 2020; 324:126664. [PMID: 32380410 DOI: 10.1016/j.foodchem.2020.126664] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 03/20/2020] [Accepted: 03/20/2020] [Indexed: 12/21/2022]
Abstract
Authentication of meat products is critical in the food industry. Meat adulteration may lead to religious apprehensions, financial gain and food-toxicities such as meat allergies. Thus, empirical validation of the quality and constituents of meat is paramount. Various analytical methods often based on protein or DNA measurements are utilized to identify meat species. Protein-based methods, including electrophoretic and immunological techniques, are at times unsuitable for discriminating closely related species. Most of these methods have been replaced by more accurate and sensitive detection methods, such as DNA-based techniques. Emerging technologies like DNA barcoding and mass spectrometry are still in their infancy when it comes to their utilization in meat detection. Gold nanobiosensors have shown some promise in this regard. However, its applicability in small scale industries is distant. This article comprehensively reviews the recent developments in the field of analytical methods used for porcine identification.
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Affiliation(s)
- Qamar Zia
- A New Mind, Ash Shati, Al Qatif 32617-3732, Saudi Arabia.
| | - Mohammad Alawami
- A New Mind, Ash Shati, Al Qatif 32617-3732, Saudi Arabia; Depaartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, United Kingdom
| | | | | | - Irwan Hanish
- Halal Product Research Institute, Universiti Putra Malaysia, UPM Serdang, Selangor 43400, Malaysia; Department of Microbiology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, UPM Serdang, Selangor 43400, Malaysia
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