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Predicting lamb carcase composition from tissue depth measured at a single point with an ultrawide-band microwave scanner.
Marimuthu, J; Loudon, K M W; Karayakallile Abraham, R; Pamarla, V; Gardner, G E.
Afiliación
  • Marimuthu J; School of Agricultural Sciences, Centre for Animal Production and Health, Food Futures Institute, Murdoch University, WA 6150, Australia; Advanced Livestock Measurement Technologies Project, Meat and Livestock Australia, NSW 2060, Australia.
  • Loudon KMW; School of Agricultural Sciences, Centre for Animal Production and Health, Food Futures Institute, Murdoch University, WA 6150, Australia; Advanced Livestock Measurement Technologies Project, Meat and Livestock Australia, NSW 2060, Australia. Electronic address: K.Loudon@murdoch.edu.au.
  • Karayakallile Abraham R; School of Agricultural Sciences, Centre for Animal Production and Health, Food Futures Institute, Murdoch University, WA 6150, Australia; Advanced Livestock Measurement Technologies Project, Meat and Livestock Australia, NSW 2060, Australia.
  • Pamarla V; School of Agricultural Sciences, Centre for Animal Production and Health, Food Futures Institute, Murdoch University, WA 6150, Australia; Advanced Livestock Measurement Technologies Project, Meat and Livestock Australia, NSW 2060, Australia.
  • Gardner GE; School of Agricultural Sciences, Centre for Animal Production and Health, Food Futures Institute, Murdoch University, WA 6150, Australia; Advanced Livestock Measurement Technologies Project, Meat and Livestock Australia, NSW 2060, Australia.
Meat Sci ; 213: 109509, 2024 Jul.
Article en En | MEDLINE | ID: mdl-38642510
ABSTRACT
This study evaluated the ability of portable ultra-wide band microwave system (MiS) to predict lamb carcase computed tomography (CT) determined composition % of fat, lean muscle and bone. Lamb carcases (n = 343) from 6 slaughter groups were MiS scanned at the C-site (45 mm from spine midline at the 12th /13th rib) prior to CT scanning to determine the proportion of fat, muscle and bone. A machine learning ensemble stacking technique was used to construct the MiS prediction equations. Predictions were pooled and divided in 5 groups stratified for each CT composition trait (fat, lean or bone%) and a k-fold cross validation (k = 5) technique was used to test the predictions. MiS predicted CT fat% with an average RMSEP of 2.385, R2 0.78, bias 0.156 and slope 0.095. The prediction of CT lean% had an average RMSEP of 2.146, R2 0.64, bias 0.172 and slope 0.117. CT bone% prediction had an average RMSEP of 0.990, R2 0.75, bias 0.051 and slope 0.090. Predictions for CT bone% met AUS-MEAT device accreditation error tolerances on the whole range of the dataset. Predictions for CT lean% and fat% met AUS-MEAT error tolerances on a constrained dataset.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Composición Corporal / Músculo Esquelético / Oveja Doméstica / Carne Roja / Microondas Límite: Animals Idioma: En Revista: Meat Sci Asunto de la revista: CIENCIAS DA NUTRICAO Año: 2024 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Composición Corporal / Músculo Esquelético / Oveja Doméstica / Carne Roja / Microondas Límite: Animals Idioma: En Revista: Meat Sci Asunto de la revista: CIENCIAS DA NUTRICAO Año: 2024 Tipo del documento: Article País de afiliación: Australia