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Ma H, Guo J, Liu G, Xie D, Zhang B, Li X, Zhang Q, Cao Q, Li X, Ma F, Li Y, Wan G, Li Y, Wu D, Ma P, Guo M, Yin J. Raman spectroscopy coupled with chemometrics for identification of adulteration and fraud in muscle foods: a review. Crit Rev Food Sci Nutr 2024:1-23. [PMID: 38523442 DOI: 10.1080/10408398.2024.2329956] [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: 03/26/2024]
Abstract
Muscle foods, valued for their significant nutrient content such as high-quality protein, vitamins, and minerals, are vulnerable to adulteration and fraud, stemming from dishonest vendor practices and insufficient market oversight. Traditional analytical methods, often limited to laboratory-scale., may not effectively detect adulteration and fraud in complex applications. Raman spectroscopy (RS), encompassing techniques like Surface-enhanced RS (SERS), Dispersive RS (DRS), Fourier transform RS (FTRS), Resonance Raman spectroscopy (RRS), and Spatially offset RS (SORS) combined with chemometrics, presents a potent approach for both qualitative and quantitative analysis of muscle food adulteration. This technology is characterized by its efficiency, rapidity, and noninvasive nature. This paper systematically summarizes and comparatively analyzes RS technology principles, emphasizing its practicality and efficacy in detecting muscle food adulteration and fraud when combined with chemometrics. The paper also discusses the existing challenges and future prospects in this field, providing essential insights for reviews and scientific research in related fields.
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Affiliation(s)
- Haiyang Ma
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Jiajun Guo
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Guishan Liu
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Delang Xie
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Bingbing Zhang
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Xiaojun Li
- School of Electronic and Electrical Engineering, Ningxia University, Yinchuan, China
| | - Qian Zhang
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Qingqing Cao
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Xiaoxue Li
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Fang Ma
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Yang Li
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Guoling Wan
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Yan Li
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Di Wu
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Ping Ma
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Mei Guo
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Junjie Yin
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
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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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Robotti E, Belay MH, Calà E, Benedetto A, Cerruti S, Pezzolato M, Pennisi F, Abete MC, Marengo E, Brizio P. Identification of Illicit Conservation Treatments in Fresh Fish by Micro-Raman Spectroscopy and Chemometric Methods. Foods 2023; 12:foods12030449. [PMID: 36765978 PMCID: PMC9913940 DOI: 10.3390/foods12030449] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/13/2023] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
In the field of food control for fresh products, the identification of foods subjected to illicit conservation treatments to extend their shelf life is fundamental. Fresh fish products are particularly subjected to this type of fraud due to their high commercial value and the fact that they often have to be transported over a long distance, keeping their organoleptic characteristics unaltered. Treatments of this type involve, e.g., the bleaching of the meat and/or the momentary abatement of the microbial load, while the degradation process continues. It is therefore important to find rapid methods that allow the identification of illicit treatments. The study presented here was performed on 24 sea bass samples divided into four groups: 12 controls (stored on ice in the fridge for 3 or 24 h), and 12 treated with a Cafodos-like solution for 3 or 24 h. Muscle and skin samples were then characterized using micro-Raman spectroscopy. The data were pre-processed by smoothing and taking the first derivative and then PLS-DA models were built to identify short- and long- term effects on the fish's muscle and skin. All the models provided the perfect classification of the samples both in fitting and cross-validation and an analysis of the bands responsible for the effects was also reported. To the best of the authors' knowledge, this is the first time Raman spectroscopy has been applied for the identification of a Cafodos-like illicit treatment, focusing on both fish muscle and skin evaluation. The procedure could pave the way for a future application directly on the market through the use of a portable device.
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Affiliation(s)
- Elisa Robotti
- Department of Sciences and Technological Innovation, University of Piemonte Orientale, Viale Michel 11, 15121 Alessandria, Italy
- Correspondence: ; Tel.: +39-0131-360272
| | - Masho Hilawie Belay
- Department of Sciences and Technological Innovation, University of Piemonte Orientale, Viale Michel 11, 15121 Alessandria, Italy
| | - Elisa Calà
- Department of Sciences and Technological Innovation, University of Piemonte Orientale, Viale Michel 11, 15121 Alessandria, Italy
| | - Alessandro Benedetto
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, Via Bologna 148, 10154 Torino, Italy
| | - Simone Cerruti
- Department of Sciences and Technological Innovation, University of Piemonte Orientale, Viale Michel 11, 15121 Alessandria, Italy
| | - Marzia Pezzolato
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, Via Bologna 148, 10154 Torino, Italy
| | - Francesco Pennisi
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, Via Bologna 148, 10154 Torino, Italy
| | - Maria Cesarina Abete
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, Via Bologna 148, 10154 Torino, Italy
| | - Emilio Marengo
- Department of Sciences and Technological Innovation, University of Piemonte Orientale, Viale Michel 11, 15121 Alessandria, Italy
| | - Paola Brizio
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, Via Bologna 148, 10154 Torino, Italy
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Qu C, Li Y, Du S, Geng Y, Su M, Liu H. Raman spectroscopy for rapid fingerprint analysis of meat quality and security: Principles, progress and prospects. Food Res Int 2022; 161:111805. [DOI: 10.1016/j.foodres.2022.111805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 07/06/2022] [Accepted: 08/18/2022] [Indexed: 11/28/2022]
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Dooley M, Paterson T, Dexter L, Matousek P, Dehghani H, Notingher I. Model-Based Optimization of Laser Excitation and Detection Improves Spectral Contrast in Noninvasive Diffuse Raman Spectroscopy. APPLIED SPECTROSCOPY 2022; 76:801-811. [PMID: 35081779 DOI: 10.1177/00037028211072900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Spatially offset Raman spectroscopy (SORS) is a powerful technique for subsurface molecular analysis of optically turbid samples. Numerical modeling of light propagation has been used to investigate opportunities for improving spectral contrast and signal to noise ratio when imaging regions of interest located 0-4.5 mm below the surface in polymer bulk material. Two- and three-dimensional modeling results demonstrate that when analyzing a certain region of interest (ROI) of finite lateral dimensions below the sample surface, offsetting both the laser source and detector in opposite directions from the central point of the ROI can increase the spectral contrast as compared to conventional SORS approach where the detector or the laser source is maintained at the central point (centered SORS). The outlined modeling results have been validated experimentally using a bulk polymer sample with a trans-stilbene ROI (cylinder) below the sample surface. The results show that modeling of the spatial configurations of laser excitation and detection points can be used to optimize the instrument configuration to achieve significant improvements (up to 2.25-fold) in performance over the conventional centered SORS. Such optimal solutions can then be implemented, for example, using robust fiber optic probes, moveable optics, or flexible spatial light modulator instruments for specific applications.
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Affiliation(s)
- Max Dooley
- School of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK
| | - Thomas Paterson
- School of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK
| | - Louise Dexter
- School of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK
| | - Pavel Matousek
- Central Laser Facility, UK Research and Innovation (UKRI), STFC Rutherford Appleton Laboratory, Harwell Oxford, UK
| | - Hamid Dehghani
- School of Computer Sciences, 1724University of Birmingham, Birmingham, UK
| | - Ioan Notingher
- School of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK
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Prediction of fatty acids composition in the rainbow trout Oncorhynchus mykiss by using Raman micro-spectroscopy. Anal Chim Acta 2022; 1191:339212. [PMID: 35033269 DOI: 10.1016/j.aca.2021.339212] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 09/26/2021] [Accepted: 10/23/2021] [Indexed: 11/21/2022]
Abstract
The importance of poly-unsaturated fatty acids (PUFAs) in food is crucial for the animal and human development and health. As a complementary strategy to nutrition approaches, genetic selection has been suggested to improve fatty acids (FAs) composition in farmed fish. Gas chromatography (GC) is used as a reference method for the quantification of FAs; nevertheless, the high cost prevents large scale phenotyping as needed in breeding programs. Therefore, a calibration by means of Raman scattering spectrometry has been established in order to predict FA composition of visceral adipose tissue in rainbow trout Onchorhynchus mykiss. FA composition was analyzed by both GC and Raman micro-spectrometry techniques on 268 individuals fed with three different feeds, which have different FA compositions. Among the possible regression methods, the ridge regression method, was found to be efficient to establish calibration models from the GC and spectral data. The best cross-validated R2 values were obtained for total PUFAs, omega-6 (Ω-6) and omega-3 (Ω-3) PUFA (0.79, 0.83 and 0.66, respectively). For individual Ω-3 PUFAs, α-linolenic acid (ALA, C18:3), eicosapentaenoic acid (EPA, C20:5) and docosahexenoic acid (DHA, C22:6) were found to have the best R2 values (0.82, 0.76 and 0.81, respectively). This study demonstrates that Raman spectroscopy could be used to predict PUFAs with good correlation coefficients on adipocytes, for future on adipocytes physiology or for large scale and high throughput phenotyping in rainbow trout.
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Landry JD, Torley PJ, Blanch EW. Quantitation of carotenoids and fatty acids from Atlantic salmon using a portable Raman device. Analyst 2022; 147:4379-4388. [DOI: 10.1039/d2an01140a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Raman spectra collected using subsurface measurement on a portable device can be used to quantify carotenoid and lipid levels in Atlantic salmon.
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Affiliation(s)
- Jeremy D. Landry
- Applied Chemistry and Environmental Sciences, School of Science, STEM College, RMIT University, 124a La Trobe Street, Melbourne, Victoria, Australia
- Biosciences and Food Technology, RMIT University, School of Science, STEM College, Bundoora, Victoria, Australia
| | - Peter J. Torley
- Biosciences and Food Technology, RMIT University, School of Science, STEM College, Bundoora, Victoria, Australia
| | - Ewan W. Blanch
- Applied Chemistry and Environmental Sciences, School of Science, STEM College, RMIT University, 124a La Trobe Street, Melbourne, Victoria, Australia
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Arroyo-Cerezo A, Jimenez-Carvelo AM, González-Casado A, Koidis A, Cuadros-Rodríguez L. Deep (offset) non-invasive Raman spectroscopy for the evaluation of food and beverages – A review. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.111822] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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