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143 related items for PubMed ID: 27004116
1. Prediction of meat spectral patterns based on optical properties and concentrations of the major constituents. ElMasry G, Nakauchi S. Food Sci Nutr; 2016 Mar; 4(2):269-83. PubMed ID: 27004116 [Abstract] [Full Text] [Related]
2. Application of mid-infrared spectroscopy with multivariate analysis and soft independent modeling of class analogies (SIMCA) for the detection of adulterants in minced beef. Meza-Márquez OG, Gallardo-Velázquez T, Osorio-Revilla G. Meat Sci; 2010 Oct; 86(2):511-9. PubMed ID: 20598447 [Abstract] [Full Text] [Related]
3. Non-destructive determination of chemical composition in intact and minced pork using near-infrared hyperspectral imaging. Barbin DF, ElMasry G, Sun DW, Allen P. Food Chem; 2013 Jun 01; 138(2-3):1162-71. PubMed ID: 23411227 [Abstract] [Full Text] [Related]
4. Detection of adulteration with duck meat in minced lamb meat by using visible near-infrared hyperspectral imaging. Zheng X, Li Y, Wei W, Peng Y. Meat Sci; 2019 Mar 01; 149():55-62. PubMed ID: 30463040 [Abstract] [Full Text] [Related]
7. Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate image analysis. Kamruzzaman M, Sun DW, ElMasry G, Allen P. Talanta; 2013 Jan 15; 103():130-6. PubMed ID: 23200368 [Abstract] [Full Text] [Related]
11. Application of visible and near infrared hyperspectral imaging for non-invasively measuring distribution of water-holding capacity in salmon flesh. Wu D, Sun DW. Talanta; 2013 Nov 15; 116():266-76. PubMed ID: 24148403 [Abstract] [Full Text] [Related]
12. Rapid Identification and Visualization of Jowl Meat Adulteration in Pork Using Hyperspectral Imaging. Jiang H, Cheng F, Shi M. Foods; 2020 Feb 06; 9(2):. PubMed ID: 32041126 [Abstract] [Full Text] [Related]
13. Challenges in Model Development for Meat Composition Using Multipoint NIR Spectroscopy from At-Line to In-Line Monitoring. Dixit Y, Casado-Gavalda MP, Cama-Moncunill R, Cullen PJ, Sullivan C. J Food Sci; 2017 Jul 06; 82(7):1557-1562. PubMed ID: 28598587 [Abstract] [Full Text] [Related]
14. Development of near infrared reflectance spectroscopy to predict chemical composition with a wide range of variability in beef. Su H, Sha K, Zhang L, Zhang Q, Xu Y, Zhang R, Li H, Sun B. Meat Sci; 2014 Oct 06; 98(2):110-4. PubMed ID: 24927045 [Abstract] [Full Text] [Related]
17. [Study on the Rapid Evaluation of Total Volatile Basic Nitrogen (TVB-N) of Mutton by Hyperspectral Imaging Technique]. Zhu RG, Yao XD, Duan HW, Ma BX, Tang MX. Guang Pu Xue Yu Guang Pu Fen Xi; 2016 Mar 06; 36(3):806-10. PubMed ID: 27400528 [Abstract] [Full Text] [Related]
19. Genetic analysis of beef fatty acid composition predicted by near-infrared spectroscopy. Cecchinato A, De Marchi M, Penasa M, Casellas J, Schiavon S, Bittante G. J Anim Sci; 2012 Feb 06; 90(2):429-38. PubMed ID: 21948610 [Abstract] [Full Text] [Related]
20. Visible and near-infrared bulk optical properties of raw milk. Aernouts B, Van Beers R, Watté R, Huybrechts T, Lammertyn J, Saeys W. J Dairy Sci; 2015 Oct 06; 98(10):6727-38. PubMed ID: 26210269 [Abstract] [Full Text] [Related] Page: [Next] [New Search]