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Relationship between porcine carcass grades and estimated traits based on conventional and non-destructive inspection methods.
Lim, Seok-Won; Hwang, Doyon; Kim, Sangwook; Kim, Jun-Mo.
Afiliación
  • Lim SW; Functional Genomics & Bioinformatics Laboratory, Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Korea.
  • Hwang D; Korea Institute for Animal Products Quality Evaluation, Sejong 30100, Korea.
  • Kim S; Functional Genomics & Bioinformatics Laboratory, Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Korea.
  • Kim JM; Functional Genomics & Bioinformatics Laboratory, Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Korea.
J Anim Sci Technol ; 64(1): 155-165, 2022 Jan.
Article en En | MEDLINE | ID: mdl-35174350
As pork consumption increases, rapid and accurate determination of porcine carcass grades at abattoirs has become important. Non-destructive, automated inspection methods have improved slaughter efficiency in abattoirs. Furthermore, the development of a calibration equation suitable for non-destructive inspection of domestic pig breeds may lead to rapid determination of pig carcass and more objective pork grading judgement. In order to increase the efficiency of pig slaughter, the correct estimation of the automated-method that can accommodate the existing pig carcass judgement should be made. In this study, the previously developed calibration equation was verified to confirm whether the estimated traits accord with the actual measured traits of pig carcass. A total of 1,069,019 pigs, to which the developed calibration equation, was applied were used in the study and the optimal estimated regression equation for actual measured two traits (backfat thickness and hot carcass weight) was proposed using the estimated traits. The accuracy of backfat thickness and hot carcass weight traits in the estimated regression models through stepwise regression analysis was 0.840 (R 2) and 0.980 (R 2), respectively. By comparing the actually measured traits with the estimated traits, we proposed optimal estimated regression equation for the two measured traits, which we expect will be a cornerstone for the Korean porcine carcass grading system.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Anim Sci Technol Año: 2022 Tipo del documento: Article Pais de publicación: Corea del Sur

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Anim Sci Technol Año: 2022 Tipo del documento: Article Pais de publicación: Corea del Sur