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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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Lintvedt TA, Andersen PV, Afseth NK, Wold JP. In-line Raman spectroscopy for characterization of an industrial poultry raw material stream. Talanta 2024; 266:125079. [PMID: 37633036 DOI: 10.1016/j.talanta.2023.125079] [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: 03/08/2023] [Revised: 08/04/2023] [Accepted: 08/13/2023] [Indexed: 08/28/2023]
Abstract
In this work, we evaluated the feasibility of Raman spectroscopy as an in-line raw material characterization tool for industrial process control of the hydrolysis of poultry rest raw material. We established calibrations (N = 59) for fat, protein, ash (proxy for bone) and hydroxyproline (proxy for collagen) in ground poultry rest raw material. Calibrations were established in the laboratory using poultry samples with high compositional variation. Samples were measured using a wide area illumination Raman probe at varying working distance (6 cm, 9 cm, 12 cm) and probe tilt angle (0°, 30°) to mimic expected in-line variations in the measurement situation. These moderate variations did not significantly affect performance for any analytes. The obtained calibrations were tested in-line with continuous measurements of the ground poultry by-product stream at a commercial hydrolysis facility over the course of two days. Measurements were acquired under demanding conditions, e.g. large variations in working distance. Reasonable estimates of compositional trends were obtained. Validation samples (N = 19) were also reasonably well predicted, with RMSEPcorr = [0.14, 1.37, 2.36, 1.51]% for hydroxyproline, protein, fat and ash, respectively. However, there were indications that further calibration development and robustification of pre-processing would be advantageous, particularly with respect to hydroxyproline and protein models. It is the authors' impression that with such efforts, potentially in combination with development of practical measurement setup, the use of Raman spectroscopy as a process control tool for the hydrolysis of poultry rest raw materials is within reach.
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Affiliation(s)
- Tiril Aurora Lintvedt
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway; Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, 1432, Norway.
| | - Petter Vejle Andersen
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway
| | - Nils Kristian Afseth
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway
| | - Jens Petter Wold
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway
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Måge I, Wubshet SG, Wold JP, Solberg LE, Böcker U, Dankel K, Lintvedt TA, Kafle B, Cattaldo M, Matić J, Sorokina L, Afseth NK. The role of biospectroscopy and chemometrics as enabling technologies for upcycling of raw materials from the food industry. Anal Chim Acta 2023; 1284:342005. [PMID: 37996160 DOI: 10.1016/j.aca.2023.342005] [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: 03/29/2023] [Revised: 09/25/2023] [Accepted: 11/05/2023] [Indexed: 11/25/2023]
Abstract
It is important to utilize the entire animal in meat and fish production to ensure sustainability. Rest raw materials, such as bones, heads, trimmings, and skin, contain essential nutrients that can be transformed into high-value products. Enzymatic protein hydrolysis (EPH) is a bioprocess that can upcycle these materials to create valuable proteins and fats. This paper focuses on the role of spectroscopy and chemometrics in characterizing the quality of the resulting protein product and understanding how raw material quality and processing affect it. The article presents recent developments in chemical characterisation and process modelling, with a focus on rest raw materials from poultry and salmon production. Even if some of the technology is relatively mature and implemented in many laboratories and industries, there are still open challenges and research questions. The main challenges are related to the transition of technology and insights from laboratory to industrial scale, and the link between peptide composition and critical product quality attributes.
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Affiliation(s)
- Ingrid Måge
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway.
| | - Sileshi Gizachew Wubshet
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway
| | - Jens Petter Wold
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway
| | - Lars Erik Solberg
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway
| | - Ulrike Böcker
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway
| | - Katinka Dankel
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway
| | - Tiril Aurora Lintvedt
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway; Norwegian University of Life Sciences, Faculty of Science and Technology, 1432, Ås, Norway
| | - Bijay Kafle
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway; Norwegian University of Life Sciences, Faculty of Science and Technology, 1432, Ås, Norway
| | - Marco Cattaldo
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway; Universidad Politécnica de Valencia, Department of Applied Statistics, Operations Research and Quality, 46022, Valencia, Spain
| | - Josipa Matić
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway
| | - Liudmila Sorokina
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway; University of Oslo, Department of Chemistry, 0371, Oslo, Norway
| | - Nils Kristian Afseth
- Nofima - Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291, Tromsø, Norway
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Fomina P, Femenias A, Hlavatsch M, Scheuermann J, Schäfer N, Freitag S, Patel N, Kohler A, Krska R, Koeth J, Mizaikoff B. A Portable Infrared Attenuated Total Reflection Spectrometer for Food Analysis. APPLIED SPECTROSCOPY 2023; 77:1073-1086. [PMID: 37525897 PMCID: PMC10478342 DOI: 10.1177/00037028231190660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 06/11/2023] [Indexed: 08/02/2023]
Abstract
The analytical performance of a compact infrared attenuated total reflection spectrometer using a pyroelectric detector array has been evaluated and compared to a conventional laboratory Fourier transform infrared system for applications in food analysis. Analytical characteristics including sensitivity, repeatability, linearity of the calibration functions, signal-to-noise ratio, and spectral resolution have been derived for both approaches. Representative analytes of relevance in food industries (i.e., organic solvents, fatty acids, and mycotoxins) have been used for the assessment of the performance of the device and to discuss the potential of this technology in food and feed analysis.
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Affiliation(s)
- Polina Fomina
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Ulm, Germany
| | - Antoni Femenias
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Ulm, Germany
| | - Michael Hlavatsch
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Ulm, Germany
| | | | - Nicolas Schäfer
- Nanoplus Nanosystems and Technologies GmbH, Gerbrunn, Germany
| | - Stephan Freitag
- Department of Agrobiotechnology IFA-Tulln, Institute of Bioanalytics and Agro-Metabolomics, University of Natural Resources and Life Sciences Vienna, Tulln, Austria
| | - Nageshvar Patel
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Achim Kohler
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Rudolf Krska
- Department of Agrobiotechnology IFA-Tulln, Institute of Bioanalytics and Agro-Metabolomics, University of Natural Resources and Life Sciences Vienna, Tulln, Austria
- School of Biological Science, Institute for Global Food Security, Queen's University Belfast, Belfast, Northern Ireland
| | - Johannes Koeth
- Nanoplus Nanosystems and Technologies GmbH, Gerbrunn, Germany
| | - Boris Mizaikoff
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Ulm, Germany
- Hahn-Schickard, Ulm, Germany
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Tan Z, Liu R, Liu J. BR-Net: Band reweighted network for quantitative analysis of rapeseed protein spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 299:122828. [PMID: 37192577 DOI: 10.1016/j.saa.2023.122828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 04/14/2023] [Accepted: 05/05/2023] [Indexed: 05/18/2023]
Abstract
Compared with the complexity of chemical methods, near-infrared spectroscopy (NIRS) is widely used in the detection of protein content because of its advantages of being fast and non-destructive. Aiming to tackle the problem that the raw near-infrared spectroscopy contains many redundant wavelengths, which affects the accuracy of quantitative prediction and requires expertise to process, we propose an end-to-end network: Band Reweighted Network (BR-Net) that automates wavelength reweighted and quantitative prediction of protein content in rapeseed. Unlike extracting part of wavelengths by the traditional wavelength selection methods, BR-Net retains all spectral wavelengths and assigns different weights to the wavelengths to express the correlation with the corresponding concentration, which enables wavelength selection without ignoring the information contained in the less relevant wavelengths. We compare BR-Net with traditional selection methods such as SPA, LARS, CARS, and UVE to verify its efficiency and robustness, finding that the R2 of the training set and test set are 0.9797 and 0.9215, the RMSEC and RMSEP are 0.4053 and 0.8501, respectively, and the RPD is 3.5686, which prove BR-Net outperforms all the traditional methods. The network described here is universally applicable to a variety of NIR quantitative analyses.
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Affiliation(s)
- Zhenglin Tan
- Department of Cuisine and Nutrition, Hubei University of Economics, Wuhan 430205, China; Hubei Chu Cuisine Research Institute, Wuhan 430205, China
| | - Ruirui Liu
- Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430205, China; School of Computer Science & Engineering, Wuhan Institute of Technology, Wuhan 430205, China
| | - Jun Liu
- Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430205, China; School of Computer Science & Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
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Kröncke N, Neumeister M, Benning R. Near-Infrared Reflectance Spectroscopy for Quantitative Analysis of Fat and Fatty Acid Content in Living Tenebrio molitor Larvae to Detect the Influence of Substrate on Larval Composition. INSECTS 2023; 14:insects14020114. [PMID: 36835684 PMCID: PMC9964368 DOI: 10.3390/insects14020114] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/17/2023] [Accepted: 01/21/2023] [Indexed: 05/12/2023]
Abstract
Several studies have shown that mealworms (Tenebrio molitor L.) could provide animals and humans with valuable nutrients. Tenebrio molitor larvae were studied to determine whether their rearing diets affected their fat and fatty acid content and to ascertain if it is possible to detect the changes in the larval fat composition using near-infrared reflectance spectroscopy (NIRS). For this reason, a standard control diet (100% wheat bran) and an experimental diet, consisting of wheat bran and the supplementation of a different substrate (coconut flour, flaxseed flour, pea protein flour, rose hip hulls, grape pomace, or hemp protein flour) were used. The results showed lesser weight gain and slower growth rates for larvae raised on diets with a high fat content. A total of eight fatty acids were identified and quantified, where palmitic, oleic, and linoleic acids were the most prevalent and showed a correlation between larval content and their content in the rearing diets. There was a high content of lauric acid (3.2-4.6%), myristic acid (11.4-12.9%), and α-linolenic acid 8.4-13.0%) in mealworm larvae as a result of the high dietary content of these fatty acids. NIR spectra were also influenced by the fat and fatty acid composition, as larval absorbance values differed greatly. The coefficient of the determination of prediction (R2P) was over 0.97, with an RPD value of 8.3 for the fat content, which indicates the high predictive accuracy of the NIR model. Furthermore, it was possible to develop calibration models with great predictive efficiency (R2P = 0.81-0.95, RPD = 2.6-5.6) for all fatty acids, except palmitoleic and stearic acids which had a low predictive power (R2P < 0.5, RPD < 2.0). The detection of fat and fatty acids using NIRS can help insect producers to quickly and easily analyze the nutritional composition of mealworm larvae during the rearing process.
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Pchelkina V, Chernukha I, Nikitina M, Ilin N. Pig adipose tissue of two different breeds and locations: morphology and Raman studies. FOODS AND RAW MATERIALS 2022. [DOI: 10.21603/2308-4057-2023-1-547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
According to the recent data, there are 4–5-local pig breeds left in Russia by now. Livni is among them. This breed is characterized by high fat content. Back fat has been analyzed earlier. We aimed to assess fat morphometrics from other localizations in pigs.
Sacral, axillary, and perirenal fat samples from 6-month-old Duroc and Livni pig breeds were analyzed using morphological and Raman-based techniques.
Livni adipocytes were characterized by dense packing with a polyhedron-like structure. In Duroc fat, they were more rounded (spherical). A “two-phase” cell disperse was identified in all samples. Fat cells in Livni pigs were bigger than those in the Duroc breed: 70–102%; 15–18 and 26% for sacral, axillary, and perirenal locations. Differences in the intensity of the Raman signal between the samples were found: in the samples of subcutaneous adipose tissue, more intense peaks were observed, which are responsible for unsaturation; the samples of Livni axillary fat were characterized by greater unsaturation than sacral fat.
Livni and Duroc adipocytes differ from each other in form and size and the difference depends on location. Pork fat from local breeds is expected to have potentially more health protecting (for animals) and health promoting (for consumers) properties.
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Affiliation(s)
| | - Irina Chernukha
- V.M. Gorbatov Federal Research Center for Food Systems of RAS
| | - Marina Nikitina
- V.M. Gorbatov Federal Research Center for Food Systems of RAS
| | - Nikolai Ilin
- V.M. Gorbatov Federal Research Center for Food Systems of RAS
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