Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: A review

被引:110
作者
Kamruzzaman, Mohammed [1 ,2 ]
Makino, Yoshio [1 ]
Oshita, Seiichi [1 ]
机构
[1] Univ Tokyo, Grad Sch Agr & Life Sci, Tokyo 1138654, Japan
[2] Bangladesh Agr Univ, Fac Agr Engn & Technol, Dept Food Technol & Rural Ind, Mymensingh 2202, Bangladesh
基金
奥地利科学基金会; 日本学术振兴会;
关键词
Non-destructive method; Hyperspectral imaging; Meat; Poultry; Fish; Adulteration; Contamination; Authenticity; HYPERSPECTRAL IMAGING-SYSTEM; INFRARED REFLECTANCE SPECTROSCOPY; SKIN TUMOR-DETECTION; ESCHERICHIA-COLI CONTAMINATION; AUTOMATIC NEMATODE DETECTION; LEAST-SQUARES REGRESSION; FILLETS GADUS-MORHUA; VIABLE COUNT TVC; MULTISPECTRAL IMAGES; MICROBIAL SPOILAGE;
D O I
10.1016/j.aca.2014.08.043
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The requirement of real-time monitoring of food products has encouraged the development of non-destructive measurement systems. Hyperspectral imaging is a rapid, reagentless, non-destructive analytical technique that integrates traditional spectroscopic and imaging techniques into one system to attain both spectral and spatial information from an object that cannot be achieved with either digital imaging or conventional spectroscopic techniques. Recently, this technique has emerged as one of the most powerful and inspiring techniques for assessing different meat species and building chemical images to show the distribution maps of constituents in a direct and easy manner. After presenting a brief description of the fundamentals of hyperspectral imaging, this paper reviews the potential applications of hyperspectral imaging for detecting the adulteration, contamination, and authenticity of meat, poultry, and fish. These applications envisage that hyperspectral imaging can be considered as a promising non-invasive analytical technique for predicting the contamination, adulteration, and authenticity of meat, poultry, and fish in a real-time mode. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:19 / 29
页数:11
相关论文
共 100 条
[1]   Chemical and discriminant analysis of bovine meat by near infrared reflectance spectroscopy (NIRS) [J].
Alomar, D ;
Gallo, C ;
Castañeda, M ;
Fuchslocher, R .
MEAT SCIENCE, 2003, 63 (04) :441-450
[2]  
[Anonymous], INNOVATIVE FOOD SCI
[3]   Quality evaluation of pickling cucumbers using hyperspectral reflectance and transmittance imaging - Part II. Performance of a prototype [J].
Ariana D.P. ;
Lu R. .
Sensing and Instrumentation for Food Quality and Safety, 2008, 2 (3) :152-160
[4]   Near-infrared hyperspectral imaging for grading and classification of pork [J].
Barbin, Douglas ;
Elmasry, Gamal ;
Sun, Da-Wen ;
Allen, Paul .
MEAT SCIENCE, 2012, 90 (01) :259-268
[5]   NIR hyperspectral imaging as non-destructive evaluation tool for the recognition of fresh and frozen-thawed porcine longissimus dorsi muscles [J].
Barbin, Douglas F. ;
Sun, Da-Wen ;
Su, Chao .
INNOVATIVE FOOD SCIENCE & EMERGING TECHNOLOGIES, 2013, 18 :226-236
[6]   Non-destructive determination of chemical composition in intact and minced pork using near-infrared hyperspectral imaging [J].
Barbin, Douglas F. ;
ElMasry, Gamal ;
Sun, Da-Wen ;
Allen, Paul .
FOOD CHEMISTRY, 2013, 138 (2-3) :1162-1171
[7]   Predicting quality and sensory attributes of pork using near-infrared hyperspectral imaging [J].
Barbin, Douglas F. ;
ElMasry, Gamal ;
Sun, Da-Wen ;
Allen, Paul .
ANALYTICA CHIMICA ACTA, 2012, 719 :30-42
[8]   Line-scan hyperspectral imaging for real-time in-line poultry fecal detection [J].
Park B. ;
Yoon S.-C. ;
Windham W.R. ;
Lawrence K.C. ;
Kim M.S. ;
Chao K. .
Sensing and Instrumentation for Food Quality and Safety, 2011, 5 (1) :25-32
[9]   Real-time multispectral imaging system for online poultry fecal inspection using unified modeling language [J].
Bosoon Park ;
Michio Kise ;
Kurt C. Lawrence ;
William R. Windham ;
Douglas P. Smith ;
Chi N. Thai .
Sensing and Instrumentation for Food Quality and Safety, 2007, 1 (2) :45-54
[10]   Reducing the fat content in ground beef without sacrificing quality: A review [J].
Brewer, M. Susan .
MEAT SCIENCE, 2012, 91 (04) :385-395