Principles and Applications of Hyperspectral Imaging in Quality Evaluation of Agro-Food Products: A Review

被引:350
作者
Elmasry, Gamal [1 ]
Kamruzzaman, Mohammed [1 ]
Sun, Da-Wen [1 ]
Allen, Paul [2 ]
机构
[1] Natl Univ Ireland Univ Coll Dublin, Sch Biosyst Engn, Agr & Food Sci Ctr, Dublin 4, Ireland
[2] TEAGASC, AFRC, Dublin, Ireland
关键词
Hyperspectral imaging; imaging spectroscopy; imaging spectrometry; image processing; near infrared spectroscopy; NIRS; quality; food; meat; fruits; vegetables; INFRARED REFLECTANCE SPECTROSCOPY; SKIN TUMOR-DETECTION; FOOD QUALITY; NONDESTRUCTIVE DETERMINATION; BRUISE DETECTION; CHILLING INJURY; SOLUBLE SOLIDS; FAT-CONTENT; PATTERN-RECOGNITION; INTRAMUSCULAR FAT;
D O I
10.1080/10408398.2010.543495
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
The requirements of reliability, expeditiousness, accuracy, consistency, and simplicity for quality assessment of food products encouraged the development of non-destructive technologies to meet the demands of consumers to obtain superior food qualities. Hyperspectral imaging is one of the most promising techniques currently investigated for quality evaluation purposes in numerous sorts of applications. The main advantage of the hyperspectral imaging system is its aptitude to incorporate both spectroscopy and imaging techniques not only to make a direct assessment of different components simultaneously but also to locate the spatial distribution of such components in the tested products. Associated with multivariate analysis protocols, hyperspectral imaging shows a convinced attitude to be dominated in food authentication and analysis in future. The marvellous potential of the hyperspectral imaging technique as a non-destructive tool has driven the development of more sophisticated hyperspectral imaging systems in food applications. The aim of this review is to give detailed outlines about the theory and principles of hyperspectral imaging and to focus primarily on its applications in the field of quality evaluation of agro-food products as well as its future applicability in modern food industries and research.
引用
收藏
页码:999 / 1023
页数:25
相关论文
共 183 条
  • [21] Practical selection of SVM parameters and noise estimation for SVM regression
    Cherkassky, V
    Ma, YQ
    [J]. NEURAL NETWORKS, 2004, 17 (01) : 113 - 126
  • [22] Identification of wheat classes using wavelet features from near infrared hyperspectral images of bulk samples
    Choudhary, R.
    Mahesh, S.
    Paliwal, J.
    Jayas, D. S.
    [J]. BIOSYSTEMS ENGINEERING, 2009, 102 (02) : 115 - 127
  • [23] Mapping and measurement of tropical coastal environments with hyperspectral and high spatial resolution data
    Clark, CD
    Ripley, HT
    Green, EP
    Edwards, AJ
    Mumby, PJ
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 1997, 18 (02) : 237 - 242
  • [24] Optical scattering in beef steak to predict tenderness using hyperspectral imaging in the VIS-NIR region
    Cluff K.
    Naganathan G.K.
    Subbiah J.
    Lu R.
    Calkins C.R.
    Samal A.
    [J]. Sensing and Instrumentation for Food Quality and Safety, 2008, 2 (3): : 189 - 196
  • [25] Study of dissected lamb muscles by visible and near infrared reflectance spectroscopy for composition assessment
    Cozzolino, D
    Murray, I
    Scaife, JR
    Paterson, R
    [J]. ANIMAL SCIENCE, 2000, 70 : 417 - 423
  • [26] Effect of rapid and conventional cooling methods on the quality of cooked ham joints
    Desmond, EM
    Kenny, TA
    Ward, P
    Sun, DW
    [J]. MEAT SCIENCE, 2000, 56 (03) : 271 - 277
  • [27] Development of a hybrid image processing algorithm for automatic evaluation of intramuscular fat content in beef M-longissimus dorsi
    Du, Cheng-Jin
    Sun, Da-Wen
    Jackman, Patrick
    Allen, Paul
    [J]. MEAT SCIENCE, 2008, 80 (04) : 1231 - 1237
  • [28] Learning techniques used in computer vision for food quality evaluation: a review
    Du, CJ
    Sun, DW
    [J]. JOURNAL OF FOOD ENGINEERING, 2006, 72 (01) : 39 - 55
  • [29] Recent developments in the applications of image processing techniques for food quality evaluation
    Du, CJ
    Sun, DW
    [J]. TRENDS IN FOOD SCIENCE & TECHNOLOGY, 2004, 15 (05) : 230 - 249
  • [30] Detecting chilling injury in Red Delicious apple using hyperspectral imaging and neural networks
    ElMasry, Gamal
    Wang, Ning
    Vigneault, Clement
    [J]. POSTHARVEST BIOLOGY AND TECHNOLOGY, 2009, 52 (01) : 1 - 8