Document Detail


Artificial intelligence techniques point out differences in classification performance between light and standard bovine carcasses.
MedLine Citation:
PMID:  22063010     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The validity of the official SEUROP bovine carcass classification to grade light carcasses by means of three well reputed Artificial Intelligence algorithms has been tested to assess possible differences in the behavior of the classifiers in affecting the repeatability of grading. We used two training sets consisting of 65 and 162 examples respectively of light and standard carcass classifications, including up to 28 different attributes describing carcass conformation. We found that the behavior of the classifiers is different when they are dealing with a light or a standard carcass. Classifiers follow SEUROP rules more rigorously when they grade standard carcasses using attributes characterizing carcass profiles and muscular development. However, when they grade light carcasses, they include attributes characterizing body size or skeletal development. A reconsideration of the SEUROP classification system for light carcasses may be recommended to clarify and standardize this specific beef market in the European Union. In addition, since conformation of light and standard carcasses can be considered different traits, this could affect sire evaluation programs to improve carcass conformation scores from data from markets presenting a great variety of ages and weights of slaughtered animals.
Authors:
J Dı́ez; A Bahamonde; J Alonso; S López; J J Del Coz; J R Quevedo; J Ranilla; O Luaces; I Alvarez; L J Royo; F Goyache
Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  Meat science     Volume:  64     ISSN:  1873-4138     ISO Abbreviation:  -     Publication Date:  2003 Jul 
Date Detail:
Created Date:  2011-11-8     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101160862     Medline TA:  Meat Sci     Country:  -    
Other Details:
Languages:  ENG     Pagination:  249-258     Citation Subset:  -    
Affiliation:
SERIDA-CENSYRA-Somió, C/Camino de los Claveles 604, E-33203 Gijón (Asturias), Spain.
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