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Journal Abstract Search

164 related items for PubMed ID: 27888774

  • 1.
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  • 2. Feasibility of near infrared transmittance spectroscopy to predict fatty acid composition of commercial processed meat.
    De Marchi M, Manuelian CL, Ton S, Cassandro M, Penasa M.
    J Sci Food Agric; 2018 Jan; 98(1):64-73. PubMed ID: 28523863
    [Abstract] [Full Text] [Related]

  • 3. On-line prediction of sodium content in vacuum packed dry-cured ham slices by non-invasive near infrared spectroscopy.
    Campos MI, Mussons ML, Antolin G, Debán L, Pardo R.
    Meat Sci; 2017 Apr; 126():29-35. PubMed ID: 28002759
    [Abstract] [Full Text] [Related]

  • 4. The relevance of different near infrared technologies and sample treatments for predicting meat quality traits in commercial beef cuts.
    De Marchi M, Penasa M, Cecchinato A, Bittante G.
    Meat Sci; 2013 Feb; 93(2):329-35. PubMed ID: 23098602
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  • 5. [Application of near infrared reflectance spectroscopy to predict meat chemical compositions: a review].
    Tao LL, Yang XJ, Deng JM, Zhang X.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2013 Nov; 33(11):3002-9. PubMed ID: 24555369
    [Abstract] [Full Text] [Related]

  • 6. Near-infrared reflectance spectroscopy for predicting amino acids content in intact processed animal proteins.
    De la Haba MJ, Garrido-Varo A, Guerrero-Ginel JE, Pérez-Marín DC.
    J Agric Food Chem; 2006 Oct 04; 54(20):7703-9. PubMed ID: 17002442
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  • 7. On-line prediction of fresh pork quality using visible/near-infrared reflectance spectroscopy.
    Liao YT, Fan YX, Cheng F.
    Meat Sci; 2010 Dec 04; 86(4):901-7. PubMed ID: 20728281
    [Abstract] [Full Text] [Related]

  • 8. 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 04; 98(2):110-4. PubMed ID: 24927045
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  • 9. Technical note: At-line prediction of mineral composition of fresh cheeses using near-infrared technologies.
    Manuelian CL, Currò S, Visentin G, Penasa M, Cassandro M, Dellea C, Bernardi M, De Marchi M.
    J Dairy Sci; 2017 Aug 04; 100(8):6084-6089. PubMed ID: 28624277
    [Abstract] [Full Text] [Related]

  • 10. 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 04; 82(7):1557-1562. PubMed ID: 28598587
    [Abstract] [Full Text] [Related]

  • 11. Determination of fat, moisture, and protein in meat and meat products by using the FOSS FoodScan Near-Infrared Spectrophotometer with FOSS Artificial Neural Network Calibration Model and Associated Database: collaborative study.
    Anderson S.
    J AOAC Int; 2007 Jul 04; 90(4):1073-83. PubMed ID: 17760345
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  • 14. A correlative study on data from pork carcass and processed meat (Bauernspeck) for automatic estimation of chemical parameters by means of near-infrared spectroscopy.
    Boschetti L, Ottavian M, Facco P, Barolo M, Serva L, Balzan S, Novelli E.
    Meat Sci; 2013 Nov 04; 95(3):621-8. PubMed ID: 23811103
    [Abstract] [Full Text] [Related]

  • 15. Assessing the influence of temperature on NIRS prediction models for the determination of sodium content in dry-cured ham slices.
    Campos MI, Antolin G, Debán L, Pardo R.
    Food Chem; 2018 Aug 15; 257():237-242. PubMed ID: 29622205
    [Abstract] [Full Text] [Related]

  • 16. Rapid and non-invasive quantification of intramuscular fat content of intact pork cuts.
    Huang H, Liu L, Ngadi MO, Gariépy C.
    Talanta; 2014 Feb 15; 119():385-95. PubMed ID: 24401429
    [Abstract] [Full Text] [Related]

  • 17. A Review of the Principles and Applications of Near-Infrared Spectroscopy to Characterize Meat, Fat, and Meat Products.
    Prieto N, Pawluczyk O, Dugan MER, Aalhus JL.
    Appl Spectrosc; 2017 Jul 15; 71(7):1403-1426. PubMed ID: 28534672
    [Abstract] [Full Text] [Related]

  • 18. Prediction of the fatty acid composition of beef by near infrared transmittance spectroscopy.
    Sierra V, Aldai N, Castro P, Osoro K, Coto-Montes A, Oliván M.
    Meat Sci; 2008 Mar 15; 78(3):248-55. PubMed ID: 22062277
    [Abstract] [Full Text] [Related]

  • 19. Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy.
    Magalhães AFB, Teixeira GHA, Ríos ACH, Silva DBDS, Mota LFM, Muniz MMM, de Morais CLM, de Lima KMG, Cunha Júnior LC, Baldi F, Carvalheiro R, Oliveira HN, Chardulo LAL, Albuquerque LG.
    J Anim Sci; 2018 Sep 29; 96(10):4229-4237. PubMed ID: 30010881
    [Abstract] [Full Text] [Related]

  • 20. [Prediction of water holding capacity of fresh pork using near infrared spectroscopy].
    Hu YH, Guo KQ, Noguchi G, Kawano S, Satake T.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2009 Dec 29; 29(12):3259-62. PubMed ID: 20210145
    [Abstract] [Full Text] [Related]

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