Prediction of beef carcass composition using linear measurements obtained by DXA scan.

The third most popular meat in the world, behind chicken and veal, is beef. This emphasizes how important it is to precisely determine your market value to ensure that producers are paid fairly. There is a need for more precise methodologies to analyze the composition of the carcass because the USDA...

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Detalles Bibliográficos
Autor principal:	Lopez G., Ariel A.
Otros Autores:	Acosta, Adela
Formato:	Tesis
Lenguaje:	Inglés
Publicado:	Zamorano: Escuela Agrícola Panamericana 2024
Materias:	USDA DXA (dual energy X ray absorptiometry) sub primal performance fat percentage bone percentage
Acceso en línea:	https://bdigital.zamorano.edu/handle/11036/7745

id	ZAMORANO7745
record_format	dspace
spelling	ZAMORANO77452024-01-11T10:59:24Z Prediction of beef carcass composition using linear measurements obtained by DXA scan. Lopez G., Ariel A. Acosta, Adela Woerner, Dale Mendizabal, Andres USDA DXA (dual energy X ray absorptiometry) sub primal performance fat percentage bone percentage The third most popular meat in the world, behind chicken and veal, is beef. This emphasizes how important it is to precisely determine your market value to ensure that producers are paid fairly. There is a need for more precise methodologies to analyze the composition of the carcass because the USDA's current method for determining yield has its limitations. In this study, lineal measurements were taken using DXA scans, and models were developed to predict sub primal performance as well as fat and bone percentage. The highlighted model for subprime yield achieved an R2 of 0.97 using just five predictors. Using three predictors, the model for fat content recorded an R2 of 0.94, whilst the prediction for bone content was established at an R2 of 0.81. Although 11 potential predictors were identified, the models were refined to only use the five most significant predictors. The study indicates a promising path for improving the assessment of the carcass composition by multiple linear regression in order to obtain more accurate valuations in the beef industry. 2024-01-11T16:55:45Z 2024-01-11T16:55:45Z 2023 Thesis https://hdl.handle.net/11036/7745 eng Copyright Escuela Agrícola Panamericana, Zamorano https://creativecommons.org/licenses/by-nc-nd/3.0/es/ application/pdf Zamorano: Escuela Agrícola Panamericana
institution	Universidad Zamorano
collection	Biblioteca Digital Zamorano
language	Inglés
topic	USDA DXA (dual energy X ray absorptiometry) sub primal performance fat percentage bone percentage
spellingShingle	USDA DXA (dual energy X ray absorptiometry) sub primal performance fat percentage bone percentage Lopez G., Ariel A. Prediction of beef carcass composition using linear measurements obtained by DXA scan.
description	The third most popular meat in the world, behind chicken and veal, is beef. This emphasizes how important it is to precisely determine your market value to ensure that producers are paid fairly. There is a need for more precise methodologies to analyze the composition of the carcass because the USDA's current method for determining yield has its limitations. In this study, lineal measurements were taken using DXA scans, and models were developed to predict sub primal performance as well as fat and bone percentage. The highlighted model for subprime yield achieved an R2 of 0.97 using just five predictors. Using three predictors, the model for fat content recorded an R2 of 0.94, whilst the prediction for bone content was established at an R2 of 0.81. Although 11 potential predictors were identified, the models were refined to only use the five most significant predictors. The study indicates a promising path for improving the assessment of the carcass composition by multiple linear regression in order to obtain more accurate valuations in the beef industry.
author2	Acosta, Adela
author_facet	Acosta, Adela Lopez G., Ariel A.
format	Tesis
author	Lopez G., Ariel A.
author_sort	Lopez G., Ariel A.
title	Prediction of beef carcass composition using linear measurements obtained by DXA scan.
title_short	Prediction of beef carcass composition using linear measurements obtained by DXA scan.
title_full	Prediction of beef carcass composition using linear measurements obtained by DXA scan.
title_fullStr	Prediction of beef carcass composition using linear measurements obtained by DXA scan.
title_full_unstemmed	Prediction of beef carcass composition using linear measurements obtained by DXA scan.
title_sort	prediction of beef carcass composition using linear measurements obtained by dxa scan.
publisher	Zamorano: Escuela Agrícola Panamericana
publishDate	2024
url	https://bdigital.zamorano.edu/handle/11036/7745
work_keys_str_mv	AT lopezgariela predictionofbeefcarcasscompositionusinglinearmeasurementsobtainedbydxascan
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Prediction of beef carcass composition using linear measurements obtained by DXA scan.

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