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Predicting beef tenderness using color and multispectral image texture features

  • Published:2012-12 Issue:4 Volume:92 Page:386-393
  • ISSN:0309-1740
  • Container-title:Meat Science
  • language:en
  • Short-container-title:Meat Science

Author:

Sun X.,Chen K.J.,Maddock-Carlin K.R.,Anderson V.L.,Lepper A.N.,Schwartz C.A.,Keller W.L.,Ilse B.R.,Magolski J.D.,Berg E.P.

Funder

NSF-MRI-R2

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Food Science

Reference28 articles.

1. Research guidelines for cookery, sensory evaluation, and instrumental tenderness measurements of fresh meat;AMSA,1995

2. Characterizing beef muscles with optical scattering and absorption coefficients in VIS-NIR region;Berg;Meat Science,2007

3. A tutorial on support vector machines for pattern recognition;Burges;Data Mining and Knowledge Discovery,1998

4. Non-destructive prediction of selected quality attributes of beef by near-infrared reflectance spectroscopy between 750 and 1098nm;Byrne;Meat Science,1998

5. An analysis of co-occurrence texture statistics as a function of grey level quantization;Clausi;Canadian Journal of Remote Sensing,2002
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