无损检测技术在掺假肉及肉制品中的应用进展
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摘要
掺假肉及肉制品是全球普遍关注的食品安全问题,食用掺假肉及肉制品可能引发消费者的健康隐患。无损检测技术在鉴别掺假肉及肉制品中有重要的应用,包括红外光谱技术、拉曼光谱技术、高光谱成像技术、多光谱成像技术、核磁共振技术、电子鼻及电子舌技术。无损检测技术具有传统检测方法没有的优势,其优点包括经济、无损、准确及短时间内检测大量的掺假肉及肉制品等。文章综述了光谱学和生物传感器两类无损检测技术在鉴定掺假肉及肉制品的原理及实际应用,对无损检测技术在掺假肉及肉制品中的发展进行总结与展望,以期为完善鉴别掺假肉及肉制品的无损检测技术提供一定的理论参考,保障肉及肉制品的安全性及真实性。
Adulterated meat and meat products have become a global food safety concern,as its consumption may cause public health issues. Non-destructive testing techniques have important applications in rapid screening of adulterated meat and meat products,including infrared spectroscopy,raman spectroscopy,hyperspectral imaging,multispectral imaging,nuclear magnetic resonance,and electronic nose and tongue. Non-destructive testing techniques have advantages that traditional detection techniques do not have. They are cost-saving,non-destructive,accurate,requiring no pre-treatment and detecting a large number of adulterated meat and meat products within a short period of time. This article reviewed the principles and applications of spectroscopy and biosensor technologies in detecting adulterated meat. It also summarized the development and perspective of non-destructive testing techniques in adulterated meat and meat products,providing a theoretical reference for non-destructive testings in meat and meat products,ensuring the safety of meat and meat products and their authenticities in the future.
Adulterated meat and meat products have become a global food safety concern,as its consumption may cause public health issues. Non-destructive testing techniques have important applications in rapid screening of adulterated meat and meat products,including infrared spectroscopy,raman spectroscopy,hyperspectral imaging,multispectral imaging,nuclear magnetic resonance,and electronic nose and tongue. Non-destructive testing techniques have advantages that traditional detection techniques do not have. They are cost-saving,non-destructive,accurate,requiring no pre-treatment and detecting a large number of adulterated meat and meat products within a short period of time. This article reviewed the principles and applications of spectroscopy and biosensor technologies in detecting adulterated meat. It also summarized the development and perspective of non-destructive testing techniques in adulterated meat and meat products,providing a theoretical reference for non-destructive testings in meat and meat products,ensuring the safety of meat and meat products and their authenticities in the future.
引文
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[16] BOYACI I H,TEMIZ H T,UYSAL R S,et al. A novel method for discrimination of beef and horsemeat using raman spectroscopy[J]. Food Chemistry,2014,148:37-41.
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[18] KUMAR Y,KARNE S C. Spectral analysis:a rapid tool for species detection in meat products[J]. Trends in Food Science&Technology,2017,62:59-67.
[19] LOHUMI S,LEE S,LEE H,et al. A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration[J]. Trends in Food Science&Technology,2015,46(1):85-98.
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[22] MORSY N,SUN D W. Robust linear and non-linear models of NIR spectroscopy for detection and quantification of adulterants in fresh and frozen-thawed minced beef[J]. Meat Science,2013,93(2):292-302.
[23] BELLON-MAUREL V,MCBRATNEY A. Near-infrared(NIR)and mid-infrared(MIR)spectroscopic techniques for assessing the amount of carbon stock in soils-critical review and research perspectives[J]. Soil Biology and Biochemistry,2011,43(7):1 398-1 410.
[24] RAHMANIA H,ROHMAN A. The employment of FTIR spectroscopy in combination with chemometrics for analysis of rat meat in meatball formulation[J]. Meat Science,2015,100:301-305.
[25] NUNES K M,ANDRADE M V O,SANTOS FILHO A M P,et al. Detection and characterisation of frauds in bovine meat in natura by non-meat ingredient additions using data fusion of chemical parameters and ATR-FTIR spectroscopy[J]. Food Chemistry,2016,205:14-22.
[26] MEZA-MRQUEZ O G,GALLARDO-VELZQUEZ T,OSORIO-REVILLA G. Application of mid-infrared spectroscopy with multivariate analysis and soft independent modeling of class analogies(SIMCA)for the detection of adulterants in minced beef[J]. Meat Science,2010,86(2):511-519.
[27] YANG D,YING Y. Applications of Raman spectroscopy in agricultural products and food analysis:A review[J].Applied Spectroscopy Reviews,2011,46(7):539-560.
[28]ZBALCI B,BOYACI·IH,TOPCU A,et al. Rapid analysis of sugars in honey by processing Raman spectrum using chemometric methods and artificial neural networks[J]. Food Chemistry,2013,136(3-4):1 444-1 452.
[29] DE BIASIO M,STAMPFER P,LEITNER R,et al. Micro-Raman spectroscopy for meat type detection[C]//Next-Generation Spectroscopic Technologies VIII. America:International Society for Optics and Photonics,2015.
[30] SOWOIDNICH K,KRONFELDT H D. Shifted excitation Raman difference spectroscopy at multiple wavelengths for in-situ meat species differentiation[J]. Applied Physics B,2012,108(4):975-982.
[31] ZAJAC A,HANUZA J,DYMI'NSKA L. Raman spectroscopy in determination of horse meat content in the mixture with other meats[J]. Food Chemistry,2014,156:333-338.
[32] TAO F,PENG Y,LI Y,et al. Simultaneous determination of tenderness and Escherichia coli contamination of pork using hyperspectral scattering technique[J]. Meat Science,2012,90(3):851-857.
[33] WU D,SHI H,HE Y,et al. Potential of hyperspectral imaging and multivariate analysis for rapid and non-invasive detection of gelatin adulteration in prawn[J]. Journal of Food Engineering,2013,119(3):680-686.
[34]刘友华,白亚斌,邱祝福.等.基于高光谱图像技术和波长选择方法的羊肉掺假检测方法研究[J].海南师范大学学报(自然科学版),2015,28(3):265-269.
[35] KAMRUZZAMAN M,MAKINO Y,OSHITA S. Rapid and non-destructive detection of chicken adulteration in minced beef using visible near-infrared hyperspectral imaging and machine learning[J]. Journal of Food Engineering,2016,170:8-15.
[36] QIN J,CHAO K,KIM M S,et al. Hyperspectral and multispectral imaging for evaluating food safety and quality[J].Journal of Food Engineering,2013,118(2):157-171.
[37] ROPODI A I,PAVLIDIS D E,MOHAREB F,et al.Multispectral image analysis approach to detect adulteration of beef and pork in raw meats[J]. Food Research International,2015,67:12-18.
[38] ROPODI A I,PANAGOU E Z,NYCHAS G J E. Multispectral imaging(MSI):A promising method for the detection of minced beef adulteration with horsemeat[J].Food Control,2017,73:57-63.
[39] ROPODI A I,PANAGOU E Z,NYCHAS G J E. Rapid detection of frozen-then-thawed minced beef using multispectral imaging and Fourier transform infrared spectroscopy[J]. Meat Science,2018,135:142-147.
[40] LAGHI L,PICONE G,CAPOZZI F. Nuclear magnetic resonance for foodomics beyond food analysis[J]. Tr AC Trends in Analytical Chemistry,2014,59:93-102.
[41] MARCONE M F,WANG S,ALBABISH W,et al. Diverse food-based applications of nuclear magnetic resonance(NMR)technology[J]. Food Research International,2013,51(2):729-747.
[42] PEARCE K L,ROSENVOLD K,ANDERSEN H J,et al. Water distribution and mobility in meat during the conversion of muscle to meat and ageing and the impacts on fresh meat quality attributes—A review[J]. Meat Science,2011,89(2):111-124.
[43]王胜威.基于低场核磁共振及电子舌对羊肉品质安全判别研究[D].贵阳:贵州大学,2015.
[44]王欣,王志永,陈利华,等.注水肉糜的低场核磁弛豫特性及判别分析[J].现代食品科技,2016(5):79-84.
[45] LI M,LI B,ZHANG W. Rapid and non-invasive detection and imaging of the hydrocolloid-injected prawns with low-field NMR and MRI[J]. Food Chemistry,2018,242:16-21.
[46] HONG X,WANG J,HAI Z. Discrimination and prediction of multiple beef freshness indexes based on electronic nose[J]. Sensors and Actuators B:Chemical,2012,161(1):381-389.
[47] TIAN X,WANG J,CUI S. Analysis of pork adulteration in minced mutton using electronic nose of metal oxide sensors[J]. Journal of Food Engineering,2013,119(4):744-749.
[48] NURJULIANA M,MAN Y B C,HASHIM D M,et al.Rapid identification of pork for halal authentication using the electronic nose and gas chromatography mass spectrometer with headspace analyzer[J]. Meat Science,2011,88(4):638-644.
[49]韩方凯.基于电子舌技术的鱼新鲜度无损检测方法研究[D].镇江:江苏大学,2013.
[50]田晓静,王俊,崔绍庆.羊肉纯度电子舌快速检测方法[J].农业工程学报,2013,29(20):255-262.
[2] RAHMATI S,JULKAPLI N M,YEHYE W A,et al. Identification of meat origin in food products-A review[J].Food Control,2016,68:379-390.
[3] HRBEK V,VACLAVIK L,ELICH O,et al. Authentication of milk and milk-based foods by direct analysis in real time ionization-high resolution mass spectrometry(DARTHRMS)technique:A critical assessment[J]. Food Control,2014,36(1):138-145.
[4] ZHAO M,DOWNEY G,O’DONNELL C P. Dispersive Raman spectroscopy and multivariate data analysis to detect offal adulteration of thawed beefburgers[J]. Journal of Agricultural and Food Chemistry,2015,63(5):1 433-1 441.
[5] BANSAL S,SINGH A,MANGAL M,et al. Food adulteration:sources,health risks,and detection methods[J].Critical Reviews in Food Science and Nutrition,2017,57(6):1 174-1 189.
[6] SHI Y,FENG Y,XU C,et al. Loop-mediated isothermal amplification assays for the rapid identification of duck-derived ingredients in adulterated meat[J]. Food Analytical Methods,2017,10(7):2 325-2 331.
[7] ROHMAN A,ERWANTO Y,MAN Y B C. Analysis of pork adulteration in beef meatball using fourier transform infrared(FTIR)spectroscopy[J]. Meat Science,2011,88(1):91-95.
[8] RAHMAN M M,ALI M E,HAMID S B A,et al. Polymerase chain reaction assay targeting cytochrome b gene for the detection of dog meat adulteration in meatball formulation[J]. Meat Science,2014,97(4):404-409.
[9] KAPPEL K,SCHRDER U. Substitution of high-priced fish with low-priced species:adulteration of common sole in German restaurants[J]. Food Control,2016,59:478-486.
[10] FANG X,ZHANG C. Detection of adulterated murine components in meat products by Taq Manreal-time PCR[J]. Food Chemistry,2016,192:485-490.
[11] BALLIN N Z. Authentication of meat and meat products[J]. Meat Science,2010,86(3):577-587.
[12] TANG M,WANG X,XU Y,et al. Water-injected detecting method research based on relative value of water content of beef[C]//2016 ASABE Annual International Meeting. America:American Society of Agricultural and Biological Engineers,2016:1.
[13] LEITNER A,CASTRO-RUBIO F,MARINA M L,et al.Identification of marker proteins for the adulteration of meat products with soybean proteins by multidimensional liquid chromatography-tandem mass spectrometry[J].Journal of Proteome Research,2006,5(9):2 424-2 430.
[14] PERISIC N,AFSETH N K,OFSTAD R,et al. Monitoring protein structural changes and hydration in bovine meat tissue due to salt substitutes by fourier transform infrared(FTIR)microspectroscopy[J]. Journal of Agricultural and Food Chemistry,2011,59(18):10 052-10 061.
[15] PERISIC N,AFSETH N K,OFSTAD R,et al. Characterizing salt substitution in beef meat processing by vibrational spectroscopy and sensory analysis[J]. Meat Science,2013,95(3):576-585.
[16] BOYACI I H,TEMIZ H T,UYSAL R S,et al. A novel method for discrimination of beef and horsemeat using raman spectroscopy[J]. Food Chemistry,2014,148:37-41.
[17] PEIRIS K,POSUDIN Y,KAYS S. Non-destructive detection of food adulteration to guarantee human health and safety[J]. Ukrainian Food Journal,2015,4:207-260.
[18] KUMAR Y,KARNE S C. Spectral analysis:a rapid tool for species detection in meat products[J]. Trends in Food Science&Technology,2017,62:59-67.
[19] LOHUMI S,LEE S,LEE H,et al. A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration[J]. Trends in Food Science&Technology,2015,46(1):85-98.
[20]黄伟,杨秀娟,张燕鸣,等.近红外光谱技术在肉类定性鉴别中的研究进展[J].肉类研究,2014,28(1):31-34.
[21] ALAMPRESE C,AMIGO J M,CASIRAGHI E,et al. Identification and quantification of turkey meat adulteration in fresh,frozen-thawed and cooked minced beef by FTNIR spectroscopy and chemometrics[J]. Meat Science,2016,121:175-181.
[22] MORSY N,SUN D W. Robust linear and non-linear models of NIR spectroscopy for detection and quantification of adulterants in fresh and frozen-thawed minced beef[J]. Meat Science,2013,93(2):292-302.
[23] BELLON-MAUREL V,MCBRATNEY A. Near-infrared(NIR)and mid-infrared(MIR)spectroscopic techniques for assessing the amount of carbon stock in soils-critical review and research perspectives[J]. Soil Biology and Biochemistry,2011,43(7):1 398-1 410.
[24] RAHMANIA H,ROHMAN A. The employment of FTIR spectroscopy in combination with chemometrics for analysis of rat meat in meatball formulation[J]. Meat Science,2015,100:301-305.
[25] NUNES K M,ANDRADE M V O,SANTOS FILHO A M P,et al. Detection and characterisation of frauds in bovine meat in natura by non-meat ingredient additions using data fusion of chemical parameters and ATR-FTIR spectroscopy[J]. Food Chemistry,2016,205:14-22.
[26] MEZA-MRQUEZ O G,GALLARDO-VELZQUEZ T,OSORIO-REVILLA G. Application of mid-infrared spectroscopy with multivariate analysis and soft independent modeling of class analogies(SIMCA)for the detection of adulterants in minced beef[J]. Meat Science,2010,86(2):511-519.
[27] YANG D,YING Y. Applications of Raman spectroscopy in agricultural products and food analysis:A review[J].Applied Spectroscopy Reviews,2011,46(7):539-560.
[28]ZBALCI B,BOYACI·IH,TOPCU A,et al. Rapid analysis of sugars in honey by processing Raman spectrum using chemometric methods and artificial neural networks[J]. Food Chemistry,2013,136(3-4):1 444-1 452.
[29] DE BIASIO M,STAMPFER P,LEITNER R,et al. Micro-Raman spectroscopy for meat type detection[C]//Next-Generation Spectroscopic Technologies VIII. America:International Society for Optics and Photonics,2015.
[30] SOWOIDNICH K,KRONFELDT H D. Shifted excitation Raman difference spectroscopy at multiple wavelengths for in-situ meat species differentiation[J]. Applied Physics B,2012,108(4):975-982.
[31] ZAJAC A,HANUZA J,DYMI'NSKA L. Raman spectroscopy in determination of horse meat content in the mixture with other meats[J]. Food Chemistry,2014,156:333-338.
[32] TAO F,PENG Y,LI Y,et al. Simultaneous determination of tenderness and Escherichia coli contamination of pork using hyperspectral scattering technique[J]. Meat Science,2012,90(3):851-857.
[33] WU D,SHI H,HE Y,et al. Potential of hyperspectral imaging and multivariate analysis for rapid and non-invasive detection of gelatin adulteration in prawn[J]. Journal of Food Engineering,2013,119(3):680-686.
[34]刘友华,白亚斌,邱祝福.等.基于高光谱图像技术和波长选择方法的羊肉掺假检测方法研究[J].海南师范大学学报(自然科学版),2015,28(3):265-269.
[35] KAMRUZZAMAN M,MAKINO Y,OSHITA S. Rapid and non-destructive detection of chicken adulteration in minced beef using visible near-infrared hyperspectral imaging and machine learning[J]. Journal of Food Engineering,2016,170:8-15.
[36] QIN J,CHAO K,KIM M S,et al. Hyperspectral and multispectral imaging for evaluating food safety and quality[J].Journal of Food Engineering,2013,118(2):157-171.
[37] ROPODI A I,PAVLIDIS D E,MOHAREB F,et al.Multispectral image analysis approach to detect adulteration of beef and pork in raw meats[J]. Food Research International,2015,67:12-18.
[38] ROPODI A I,PANAGOU E Z,NYCHAS G J E. Multispectral imaging(MSI):A promising method for the detection of minced beef adulteration with horsemeat[J].Food Control,2017,73:57-63.
[39] ROPODI A I,PANAGOU E Z,NYCHAS G J E. Rapid detection of frozen-then-thawed minced beef using multispectral imaging and Fourier transform infrared spectroscopy[J]. Meat Science,2018,135:142-147.
[40] LAGHI L,PICONE G,CAPOZZI F. Nuclear magnetic resonance for foodomics beyond food analysis[J]. Tr AC Trends in Analytical Chemistry,2014,59:93-102.
[41] MARCONE M F,WANG S,ALBABISH W,et al. Diverse food-based applications of nuclear magnetic resonance(NMR)technology[J]. Food Research International,2013,51(2):729-747.
[42] PEARCE K L,ROSENVOLD K,ANDERSEN H J,et al. Water distribution and mobility in meat during the conversion of muscle to meat and ageing and the impacts on fresh meat quality attributes—A review[J]. Meat Science,2011,89(2):111-124.
[43]王胜威.基于低场核磁共振及电子舌对羊肉品质安全判别研究[D].贵阳:贵州大学,2015.
[44]王欣,王志永,陈利华,等.注水肉糜的低场核磁弛豫特性及判别分析[J].现代食品科技,2016(5):79-84.
[45] LI M,LI B,ZHANG W. Rapid and non-invasive detection and imaging of the hydrocolloid-injected prawns with low-field NMR and MRI[J]. Food Chemistry,2018,242:16-21.
[46] HONG X,WANG J,HAI Z. Discrimination and prediction of multiple beef freshness indexes based on electronic nose[J]. Sensors and Actuators B:Chemical,2012,161(1):381-389.
[47] TIAN X,WANG J,CUI S. Analysis of pork adulteration in minced mutton using electronic nose of metal oxide sensors[J]. Journal of Food Engineering,2013,119(4):744-749.
[48] NURJULIANA M,MAN Y B C,HASHIM D M,et al.Rapid identification of pork for halal authentication using the electronic nose and gas chromatography mass spectrometer with headspace analyzer[J]. Meat Science,2011,88(4):638-644.
[49]韩方凯.基于电子舌技术的鱼新鲜度无损检测方法研究[D].镇江:江苏大学,2013.
[50]田晓静,王俊,崔绍庆.羊肉纯度电子舌快速检测方法[J].农业工程学报,2013,29(20):255-262.