Recent developments of hyperspectral imaging systems and their applications in detecting quality attributes of red meats: A review
暂无分享,去创建一个
Da-Wen Sun | Xin-An Zeng | Zhenjie Xiong | Anguo Xie | Z. Xiong | Xin‐an Zeng | Anguo Xie | Da‐Wen Sun
[1] Wei Wang,et al. Prediction of Pork Meat Total Viable Bacteria Count Using Hyperspectral Imaging System and Support Vector Machines , 2008 .
[2] Liyun Zheng,et al. Influence of Ultrasound on Freezing Rate of Immersion-frozen Apples , 2009 .
[3] Joaquim Salvi,et al. Review of CMOS image sensors , 2006, Microelectron. J..
[4] Tadhg Brosnan,et al. Extension of the vase life of cut daffodil flowers by rapid vacuum cooling , 1999 .
[5] Gamal ElMasry,et al. Predicting quality and sensory attributes of pork using near-infrared hyperspectral imaging. , 2012, Analytica chimica acta.
[6] Renfu Lu,et al. Detection of bruises on apples using near-infrared hyperspectral imaging , 2003 .
[7] Shigeki Nakauchi,et al. Near Infrared Spectroscopy and Hyperspectral Imaging for Prediction and Visualisation of Fat and Fatty Acid Content in Intact Raw Beef Cuts , 2010 .
[8] Da-Wen Sun,et al. Meat Quality Evaluation by Hyperspectral Imaging Technique: An Overview , 2012, Critical reviews in food science and nutrition.
[9] Noel D.G. White,et al. Wheat Class Identification Using Thermal Imaging , 2010 .
[10] A. Peirs,et al. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review , 2007 .
[11] A. J. McAfee,et al. Red meat consumption: an overview of the risks and benefits. , 2010, Meat science.
[12] Michael Ngadi,et al. Prediction of Egg Freshness and Albumen Quality Using Visible/Near Infrared Spectroscopy , 2011 .
[13] Ning Wang,et al. Determination of pork quality attributes using hyperspectral imaging technique , 2005, SPIE Optics East.
[14] Caesar Kueh,et al. CCD vs CMOS , 2008 .
[15] D. S. Hale,et al. National Beef Tenderness Survey-1998. , 2000, Journal of animal science.
[16] S. Sanjeevi,et al. An Improved Band Selection Technique for Hyperspectral Data Using Factor Analysis , 2013, Journal of the Indian Society of Remote Sensing.
[17] K. Kvaal,et al. Prediction of fat, muscle and value in Norwegian lamb carcasses using EUROP classification, carcass shape and length measurements, visible light reflectance and computer tomography (CT). , 2009, Meat science.
[18] S. Prasher,et al. Prediction of drip-loss, pH, and color for pork using a hyperspectral imaging technique. , 2007, Meat science.
[19] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[20] Da-Wen Sun,et al. CFD simulation of coupled heat and mass transfer through porous foods during vacuum cooling process , 2003 .
[21] Jing Zhang,et al. Hyperspectral scattering profiles for prediction of the microbial spoilage of beef , 2009, Defense + Commercial Sensing.
[22] A. Méndez,et al. Overview of Fiber Optic Sensors for NDT Applications , 2013 .
[23] Cheng-Jin Du,et al. Prediction of beef eating quality from colour, marbling and wavelet texture features. , 2008, Meat science.
[24] J. L. Woods,et al. SIMULATION OF THE HEAT AND MOISTURE TRANSFER PROCESS DURING DRYING IN DEEP GRAIN BEDS , 1997 .
[25] Da-Wen Sun,et al. Innovative applications of power ultrasound during food freezing processes—a review , 2006 .
[26] Gamal ElMasry,et al. Non-destructive prediction and visualization of chemical composition in lamb meat using NIR hyperspectral imaging and multivariate regression , 2012 .
[27] J. L. Woods,et al. Low temperature moisture transfer characteristics of Barley: thin-layer models and equilibrium isotherms , 1994 .
[28] G. Geesink,et al. Prediction of pork quality attributes from near infrared reflectance spectra. , 2003, Meat science.
[29] Ashok Samal,et al. Visible/near-infrared hyperspectral imaging for beef tenderness prediction , 2008 .
[30] Da-Wen Sun,et al. Principles and Applications of Hyperspectral Imaging in Quality Evaluation of Agro-Food Products: A Review , 2012, Critical reviews in food science and nutrition.
[31] Johan A. K. Suykens,et al. Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.
[32] Dejan Škorjanc,et al. Predicting pork water-holding capacity with NIR spectroscopy in relation to different reference methods , 2010 .
[33] E. Baéza,et al. Harmonization of methodologies for the assessment of poultry meat quality features , 2011 .
[34] Aiguo Ouyang,et al. Nondestructive measurement of soluble solid content of navel orange fruit by visible-NIR spectrometric technique with PLSR and PCA-BPNN. , 2010 .
[35] Gamal ElMasry,et al. Prediction of some quality attributes of lamb meat using near-infrared hyperspectral imaging and multivariate analysis. , 2012, Analytica chimica acta.
[36] E A Navajas,et al. Predicting beef cuts composition, fatty acids and meat quality characteristics by spiral computed tomography. , 2010, Meat science.
[37] Geoff Simm,et al. The prediction of carcass composition and tissue distribution in beef cattle using ultrasound scanning at the start and/or end of the finishing period. , 2010 .
[38] R. G. Kauffman,et al. Muscle protein changes post mortem in relation to pork quality traits. , 1997, Meat science.
[39] S. De Smet,et al. Meat, poultry, and fish composition: Strategies for optimizing human intake of essential nutrients , 2012 .
[40] Yankun Peng,et al. Prediction of beef quality attributes using VIS/NIR hyperspectral scattering imaging technique , 2012 .
[41] G Monin,et al. Influence of intramuscular fat content on the quality of pig meat - 2. Consumer acceptability of m. longissimus lumborum. , 1999, Meat science.
[42] Yankun Peng,et al. Simultaneous determination of tenderness and Escherichia coli contamination of pork using hyperspectral scattering technique. , 2012, Meat science.
[43] Gilles Trystram,et al. On-line assessment of brightness and surface kinetics during coffee roasting , 2008 .
[44] Shan Suthaharan,et al. Support Vector Machine , 2016 .
[45] Francis T. S. Yu,et al. Fiber Optic Sensors , 2002 .
[46] Alan Edelman,et al. Parallel MATLAB: Doing it Right , 2005, Proceedings of the IEEE.
[47] Wei Wang,et al. [Study on modeling method of total viable count of fresh pork meat based on hyperspectral imaging system]. , 2010, Guang pu xue yu guang pu fen xi = Guang pu.
[48] Song Aiqun,et al. Applied Technique and Development Trend of CCD Image Sensor , 2007, 2007 8th International Conference on Electronic Measurement and Instruments.
[49] Gilles Trystram,et al. Prediction of brightness and surface area kinetics during coffee roasting , 2008 .
[50] Da-Wen Sun,et al. Preservation of kiwifruit coated with an edible film at ambient temperature , 2001 .
[51] Da-Wen Sun,et al. Effect of Microwave-Vacuum Drying on the Carotenoids Retention of Carrot Slices and Chlorophyll Retention of Chinese Chive Leaves , 2004 .
[52] Leilei Zhang,et al. Hyperspectral imaging technique for determination of pork freshness attributes , 2011, Defense + Commercial Sensing.
[53] Gamal ElMasry,et al. Near-infrared hyperspectral imaging for predicting colour, pH and tenderness of fresh beef , 2012 .
[54] J. L. Woods,et al. Low temperature moisture transfer characteristics of wheat in thin layers , 1994 .
[55] I. Murray,et al. The use of visible and near infrared reflectance spectroscopy to predict beef M. longissimus thoracis et lumborum quality attributes. , 2008, Meat science.
[56] S. Engelsen,et al. Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .
[57] E. Agulló,et al. Determination of Total Pigments in Red Meats , 1990 .
[58] E Kalm,et al. Comparison of different methods for determination of drip loss and their relationships to meat quality and carcass characteristics in pigs. , 2004, Meat science.
[59] Marina Gispert,et al. Use of linear regression and partial least square regression to predict intramuscular fat of pig loin computed tomography images , 2013 .
[60] W. M. Robertson,et al. The eating quality of Canadian pork and its relationship with intramuscular fat. , 2005, Meat science.
[61] M. Hunt,et al. Current research in meat color. , 2005, Meat science.
[62] Da-Wen Sun,et al. Vacuum cooling technology for the agri-food industry: Past, present and future , 2006 .
[63] Cheng-Jin Du,et al. Comparison of three methods for classification of pizza topping using different colour space transformations , 2005 .
[64] Josse De Baerdemaeker,et al. Front-Face Fluorescence Spectroscopy as a Rapid and Non-Destructive Tool for Differentiating Between Sicilo–Sarde and Comisana Ewe’s Milk During Lactation Period: A Preliminary Study , 2008 .
[65] Gamal ElMasry,et al. Non-destructive determination of chemical composition in intact and minced pork using near-infrared hyperspectral imaging. , 2013, Food chemistry.
[66] Di Wu,et al. Application of long-wave near infrared hyperspectral imaging for measurement of color distribution in salmon fillet , 2012 .
[67] J D Gresham,et al. Commercial adaptation of ultrasonography to predict pork carcass composition from live animal and carcass measurements. , 1992, Journal of animal science.
[68] Da-Wen Sun,et al. Emerging non-contact imaging, spectroscopic and colorimetric technologies for quality evaluation and control of hams: a review , 2010 .
[69] Wei Wang,et al. [Study of spatially resolved hyperspectral scattering images for assessing beef quality characteristics]. , 2010, Guang pu xue yu guang pu fen xi = Guang pu.
[70] Da-Wen Sun,et al. Recent advances in the use of computer vision technology in the quality assessment of fresh meats , 2011 .
[71] Gamal Elmasry,et al. Near-infrared hyperspectral imaging for grading and classification of pork. , 2012, Meat science.
[72] J. Blasco,et al. Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment , 2012, Food and Bioprocess Technology.
[73] Gamal ElMasry,et al. Application of NIR hyperspectral imaging for discrimination of lamb muscles , 2011 .
[74] Dominique Derome,et al. Novel Application of Neutron Radiography to Forced Convective Drying of Fruit Tissue , 2013, Food and Bioprocess Technology.
[75] D. E. Goll. Role of proteinases and protein turnover in muscle growth and meat quality , 1992 .
[76] Wouter Saeys,et al. NIR Spectroscopy Applications for Internal and External Quality Analysis of Citrus Fruit—A Review , 2012, Food and Bioprocess Technology.
[77] S. Dikmen,et al. The assessment of carcass composition of Awassi male lambs by real-time ultrasound at two different live weights. , 2008, Meat science.
[78] A. El Gamal,et al. A 0.5 μm pixel frame-transfer CCD image sensor in 110 nm CMOS , 2007, 2007 IEEE International Electron Devices Meeting.
[79] Pankaj B. Pathare,et al. Colour Measurement and Analysis in Fresh and Processed Foods: A Review , 2012, Food and Bioprocess Technology.
[80] E. Huff-Lonergan,et al. Progress in reducing the pale, soft and exudative (PSE) problem in pork and poultry meat. , 2008, Meat science.
[81] Yankun Peng,et al. Application of Hyper-Spectral Imaging Technique for the Detection of Total Viable Bacteria Count in Pork , 2011 .
[82] I K Fodor,et al. A Survey of Dimension Reduction Techniques , 2002 .
[83] Kay Sowoidnich,et al. Application of Diode-Laser Raman Spectroscopy for In situ Investigation of Meat Spoilage , 2010 .
[84] E. Wierbicki,et al. Water Content of Meats, Determination of Water-Holding Capacity of Fresh Meats , 1958 .
[85] Frans van den Berg,et al. Review of the most common pre-processing techniques for near-infrared spectra , 2009 .
[86] Da-Wen Sun,et al. Colour calibration of a laboratory computer vision system for quality evaluation of pre-sliced hams. , 2009, Meat science.
[87] Kurt C. Lawrence,et al. Performance of hyperspectral imaging system for poultry surface fecal contaminant detection. , 2006 .
[88] X. Fernandez,et al. Effect of ultimate pH on the physicochemical and biochemical characteristics of turkey breast muscle showing normal rate of postmortem pH fall. , 2004, Poultry science.
[89] J. L. Woods,et al. The Moisture Content/Relative Humidity Equilibrium Relationship Of Wheat - A Review , 1993 .
[90] Moon S. Kim,et al. Development of hyperspectral imaging technique for the detection of apple surface defects and contaminations , 2004 .
[91] Heqiang Lou,et al. Nondestructive Evaluation of Quality Changes and the Optimum Time for Harvesting During Jujube (Zizyphus jujuba Mill. cv. Changhong) Fruits Development , 2012, Food and Bioprocess Technology.
[92] I. Bayram,et al. The use of ultrasound to predict the carcass composition of live Akkaraman lambs. , 2008, Meat science.
[93] Da-Wen Sun,et al. Potential of hyperspectral imaging and pattern recognition for categorization and authentication of red meat , 2012 .
[94] E S Lee,et al. Effects of quality grade on the chemical, physical and sensory characteristics of Hanwoo (Korean native cattle) beef. , 2003, Meat science.
[95] R. Rødbotten,et al. Prediction of beef quality attributes from early post mortem near infrared reflectance spectra , 2000 .
[96] Da-Wen Sun,et al. Comparison and selection of EMC/ERH isotherm equations for rice , 1999 .
[97] Q. Shen,et al. Discrimination of Edible Vegetable Oil Adulteration with Used Frying Oil by Low Field Nuclear Magnetic Resonance , 2013, Food and Bioprocess Technology.
[98] Benoit Rivard,et al. The Successive Projection Algorithm (SPA), an Algorithm with a Spatial Constraint for the Automatic Search of Endmembers in Hyperspectral Data , 2008, Sensors.
[99] Gamal ElMasry,et al. Chemical-free assessment and mapping of major constituents in beef using hyperspectral imaging , 2013 .
[100] S. Rabe,et al. Monolithic 3.3 V CCD/SOI-CMOS imager technology , 2000, International Electron Devices Meeting 2000. Technical Digest. IEDM (Cat. No.00CH37138).
[101] H. J. Andersen,et al. Factors of significance for pork quality-a review. , 2003, Meat science.
[102] Gamal ElMasry,et al. Non-destructive assessment of instrumental and sensory tenderness of lamb meat using NIR hyperspectral imaging. , 2013, Food chemistry.
[103] Anna Grazia Mignani,et al. Optical Sensors and Microsystems , 2000 .
[104] Jiang Li,et al. Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction , 2002, IEEE Trans. Geosci. Remote. Sens..
[105] Wei Wang,et al. Rapid detection of total viable count of chilled pork using hyperspectral scattering technique , 2010, Defense + Commercial Sensing.
[106] Da-Wen Sun,et al. Rapid cooling of porous and moisture foods by using vacuum cooling technology , 2001 .
[107] Da-Wen Sun,et al. Selection of EMC/ERH Isotherm Equations for Rapeseed , 1998 .
[108] K. J. Chen,et al. Segmentation of beef marbling based on vision threshold , 2008 .
[109] Yankun Peng,et al. Nondestructive assessment of beef-marbling grade using hyperspectral imaging technology , 2011, 2011 International Conference on New Technology of Agricultural.
[110] Wei Wang,et al. [A rapid nondestructive measurement method for assessing the total plate count on chilled pork surface]. , 2010, Guang pu xue yu guang pu fen xi = Guang pu.
[111] Da-Wen Sun,et al. Recent Advances in Wavelength Selection Techniques for Hyperspectral Image Processing in the Food Industry , 2014, Food and Bioprocess Technology.
[112] Christine Fischer,et al. A RAPID METHOD FOR THE DETECTION OF PSE AND DFD PORCINE MUSCLES , 1977 .
[113] Da-Wen Sun,et al. Application of Hyperspectral Imaging in Food Safety Inspection and Control: A Review , 2012, Critical reviews in food science and nutrition.
[114] Gregory J. E. Rawlins,et al. Reverse HillclimbingGenetic Algorithms and the Busy Beaver Problem , 1993, ICGA.
[115] S. Prasher,et al. Pork quality and marbling level assessment using a hyperspectral imaging system , 2007 .
[116] Gamal ElMasry,et al. Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging , 2011 .
[117] Ashok Samal,et al. Optical scattering in beef steak to predict tenderness using hyperspectral imaging in the VIS-NIR region , 2008 .