Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef
暂无分享,去创建一个
[1] Carmen Gallo,et al. Identification of cattle, llama and horse meat by near infrared reflectance or transflectance spectroscopy. , 2012, Meat science.
[2] Ding Hb,et al. Near-infrared spectroscopic technique for detection of beef hamburger adulteration. , 2000 .
[3] R. Wightman,et al. Multivariate concentration determination using principal component regression with residual analysis. , 2009, Trends in analytical chemistry : TRAC.
[4] Da-Wen Sun,et al. Potential of hyperspectral imaging and pattern recognition for categorization and authentication of red meat , 2012 .
[5] Gamal ElMasry,et al. Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging , 2011 .
[6] Gamal ElMasry,et al. Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate image analysis. , 2013, Talanta.
[7] Yidan Bao,et al. Rapid prediction of moisture content of dehydrated prawns using online hyperspectral imaging system. , 2012, Analytica chimica acta.
[8] Gamal ElMasry,et al. Application of NIR hyperspectral imaging for discrimination of lamb muscles , 2011 .
[9] Da-Wen Sun,et al. Selection of feature wavelengths for developing multispectral imaging systems for quality, safety and authenticity of muscle foods-a review , 2015 .
[10] S. Prasher,et al. Prediction of drip-loss, pH, and color for pork using a hyperspectral imaging technique. , 2007, Meat science.
[11] Cameron Faustman,et al. Krzywicki Revisited: Equations for Spectrophotometric Determination of Myoglobin Redox Forms in Aqueous Meat Extracts , 2006 .
[12] Gamal ElMasry,et al. Predicting quality and sensory attributes of pork using near-infrared hyperspectral imaging. , 2012, Analytica chimica acta.
[13] Ashok Samal,et al. Visible/near-infrared hyperspectral imaging for beef tenderness prediction , 2008 .
[14] Gamal ElMasry,et al. Prediction of some quality attributes of lamb meat using near-infrared hyperspectral imaging and multivariate analysis. , 2012, Analytica chimica acta.
[15] Gamal ElMasry,et al. Non-destructive assessment of instrumental and sensory tenderness of lamb meat using NIR hyperspectral imaging. , 2013, Food chemistry.
[16] Jens Petter Wold,et al. Atlantic Salmon Average Fat Content Estimated by Near‐Infrared Transmittance Spectroscopy , 1996 .
[17] A. Peirs,et al. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review , 2007 .
[18] Christian W. Huck,et al. Methods for detection of pork adulteration in veal product based on FT-NIR spectroscopy for laboratory, industrial and on-site analysis , 2015 .
[19] Havva Tümay Temiz,et al. A novel method for discrimination of beef and horsemeat using Raman spectroscopy. , 2014, Food chemistry.
[20] Gamal ElMasry,et al. Non-destructive prediction and visualization of chemical composition in lamb meat using NIR hyperspectral imaging and multivariate regression , 2012 .
[21] Ashok Samal,et al. Partial least squares analysis of near-infrared hyperspectral images for beef tenderness prediction , 2008 .
[22] S. Oshita,et al. Rapid detection of Escherichia coli contamination in packaged fresh spinach using hyperspectral imaging. , 2011, Talanta.
[23] 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.
[24] Hongbin Pu,et al. Hierarchical variable selection for predicting chemical constituents in lamb meats using hyperspectral imaging , 2014 .
[25] S. Lanteri,et al. Detection of minced beef adulteration with turkey meat by UV-vis, NIR and MIR spectroscopy , 2013 .
[26] Paul Allen,et al. Prediction of moisture, color and pH in cooked, pre-sliced turkey hams by NIR hyperspectral imaging system , 2013 .
[27] Yoshio Makino,et al. Assessment of Visible Near-Infrared Hyperspectral Imaging as a Tool for Detection of Horsemeat Adulteration in Minced Beef , 2015, Food and Bioprocess Technology.
[28] Yao-Ze Feng,et al. Near-infrared hyperspectral imaging in tandem with partial least squares regression and genetic algorithm for non-destructive determination and visualization of Pseudomonas loads in chicken fillets. , 2013, Talanta.
[29] O. G. Meza-Márquez,et al. Application of mid-infrared spectroscopy with multivariate analysis and soft independent modeling of class analogies (SIMCA) for the detection of adulterants in minced beef. , 2010, Meat science.
[30] J. Coello,et al. Effect of Data Preprocessing Methods in Near-Infrared Diffuse Reflectance Spectroscopy for the Determination of the Active Compound in a Pharmaceutical Preparation , 1997 .
[31] Daniel Cozzolino,et al. Identification of animal meat muscles by visible and near infrared reflectance spectroscopy , 2004 .
[32] 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.
[33] S. Oshita,et al. Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: a review. , 2015, Analytica chimica acta.
[34] Noha Morsy,et al. Robust linear and non-linear models of NIR spectroscopy for detection and quantification of adulterants in fresh and frozen-thawed minced beef. , 2013, Meat science.
[35] Ming Zhao,et al. Dispersive Raman spectroscopy and multivariate data analysis to detect offal adulteration of thawed beefburgers. , 2015, Journal of agricultural and food chemistry.
[36] Hongbin Pu,et al. Application of Wavelet Analysis to Spectral Data for Categorization of Lamb Muscles , 2014, Food and Bioprocess Technology.
[37] N. Z. Ballin. Authentication of meat and meat products. , 2010, Meat science.