Datos del Documento

Por favor, use este identificador para citar o enlazar este documento: https://ria.asturias.es/RIA/handle/123456789/7266
Título : Using artificial intelligence to design and implement a morphological assessment system in beef cattle
Autor : Goyache, Félix
Coz, J. J. del
Quevedo, J. R.
Palabras clave : Inteligencia artificial
Ganado vacuno
Aprendizaje automático
Fecha de publicación : 2001
Editorial : Cambridge University Press
Citación : Goyache, F... [et al.]. Using artificial intelligence to design and implement a morphological assessment system in beef cattle. Animal Science. 2001 ; 73 : 49-60
Resumen : In this paper a methodology is developed to improve the design and implementation of a linear morphological system in beef cattle using artificial intelligence. The proposed process involves an iterative mechanism where type traits are successively defined and computationally represented using knowledge engineering methodologies, scored by a set of trained human experts and finally, analysed by means of four reputed machine learning algorithms. The results thus achieved serve as feed back to the next iteration in order to improve the accuracy and efficacy of the proposed assessment system. A sample of 260 conformation records of the Asturiana de los Valles beef cattle breed is shown to illustrate the methodology. Three sources of inconsistency were detected: (a) the existence of different interpretations of the trait’s definition, increasing the subjectivity of the assessment; (b) the narrow range of variation of some of the anatomical traits assessed; (c) the inclusion of some complex traits in the assessment system. In this sense, the reopening of the evaluated Asturiana de los Valles assessment system is recommended. In spite of the difficulty of collecting data from live animals, further implications of the artificial intelligence systems on morphological assessment are pointed out.
URI : http://ria.asturias.es/RIA/handle/123456789/7266
ISSN : 1357-7298
Aparece en las colecciones: Agroalimentación y Ganadería
Open Access DRIVERset

Archivos en este documento:
Fichero Tamaño Formato  
Archivo.pdf72.53 kBAdobe PDFVer/Abrir
Mostrar el registro Completo

Ver estadísticas del documento

Este documento está sujeto a una licencia Creative Commons: Licencia Creative Commons Creative Commons