Can equations for Black Belly lambs be used to predict the carcass tissue composition of Dorper lambs?

Objective: This study aimed to evaluate the applicability of equations developed in Black Belly lambs for predicting carcass tissue composition in Dorper lambs. Design/methodology/approach: This study was conducted using twenty 6-month-old ewe lambs (30.53±3.62 kg). Animals were slaughtered, and the carcass was chilled at 1°C for 24 hours. The carcass was then split along the dorsal midline, and sections 9-11 were removed from the left half of the carcass. The remainder of the left half of the carcass was dissected into muscle (TMC), fat (TCF), and bone (TCB), and the weight of each was adjusted to the total carcass weight. The equations were assessed for their adequacy. The accuracy and precision of the models were assessed by simple linear regression analysis, graphical analysis, mean square error of prediction (MSEP) and its components, and sources of error. Results: The regression analysis indicated that in equations for TCM and TCF, the slope was not different from unity (P >0.05), but the intercept was different from zero (P <0.05). Nonetheless, all equations showed low to moderate precision (0.20 ≤ r2 ≤ 0.65), moderate accuracy (bias correction factor <0.65), and low to moderate reproducibility index and agreement with observed data (concordance correlation coefficient of 0.30 ≤ CCC ≤ 0.48) for predicting carcass tissues in Dorper lambs. In equations for TCM and TCF, the main component of the MSEP was the means bias (> 73.29%). In the TCB equation, the main component of the MSEP was random error (> 69.82%). This result indicates that further evaluation is required to ensure that there is no lack of fit, i.e., simply random variation that cannot be accounted for by the model in its current form. Study limitations/implications: The study highlights significant limitations in the equations used to estimate the carcass composition of Dorper lambs, showing poor agreement between observed and predicted weights. This highlights the need for more accurate models that consider breed, sex, and local rearing conditions. Findings/Conclusions: Based on these findings, we suggest that the equations tested in this study are not effective in predicting carcass tissue composition in Dorper lambs.

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Publication Details

Journal
Agro Productividad
Published
2025-05-22
DOI
https://doi.org/10.32854/1653s096
Citations
1
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
1.82
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article

Can equations for Black Belly lambs be used to predict the carcass tissue composition of Dorper lambs?

Alfonso Juventino Chay‐Canul, Miguel Á. Gastélum-Delgado, José Felipe Orzuna‐Orzuna, Víctor Manuel Meza-Villalvazo et al.
1 citations
Agro Productividad
Genetic and phenotypic traits in livestock
1.82
article

Can equations for Black Belly lambs be used to predict the carcass tissue composition of Dorper lambs?

Alfonso Juventino Chay‐Canul, Miguel Á. Gastélum-Delgado, José Felipe Orzuna‐Orzuna, Víctor Manuel Meza-Villalvazo, Marcos Inácio Marcondes, Germani Adrián Muñoz-Osorio, Iñigo Martínez, Emmanuel Jesús Quijano-Gallegos
article en
1 citations

Abstract

Objective: This study aimed to evaluate the applicability of equations developed in Black Belly lambs for predicting carcass tissue composition in Dorper lambs. Design/methodology/approach: This study was conducted using twenty 6-month-old ewe lambs (30.53±3.62 kg). Animals were slaughtered, and the carcass was chilled at 1°C for 24 hours. The carcass was then split along the dorsal midline, and sections 9-11 were removed from the left half of the carcass. The remainder of the left half of the carcass was dissected into muscle (TMC), fat (TCF), and bone (TCB), and the weight of each was adjusted to the total carcass weight. The equations were assessed for their adequacy. The accuracy and precision of the models were assessed by simple linear regression analysis, graphical analysis, mean square error of prediction (MSEP) and its components, and sources of error. Results: The regression analysis indicated that in equations for TCM and TCF, the slope was not different from unity (P >0.05), but the intercept was different from zero (P <0.05). Nonetheless, all equations showed low to moderate precision (0.20 ≤ r2 ≤ 0.65), moderate accuracy (bias correction factor <0.65), and low to moderate reproducibility index and agreement with observed data (concordance correlation coefficient of 0.30 ≤ CCC ≤ 0.48) for predicting carcass tissues in Dorper lambs. In equations for TCM and TCF, the main component of the MSEP was the means bias (> 73.29%). In the TCB equation, the main component of the MSEP was random error (> 69.82%). This result indicates that further evaluation is required to ensure that there is no lack of fit, i.e., simply random variation that cannot be accounted for by the model in its current form. Study limitations/implications: The study highlights significant limitations in the equations used to estimate the carcass composition of Dorper lambs, showing poor agreement between observed and predicted weights. This highlights the need for more accurate models that consider breed, sex, and local rearing conditions. Findings/Conclusions: Based on these findings, we suggest that the equations tested in this study are not effective in predicting carcass tissue composition in Dorper lambs.

Agro Productividad
Chapingo Autonomous University (MX), Washington State University (US), Universidad Juárez Autónoma de Tabasco (MX)
Openalex Percentile: Top 16%
Genetic and phenotypic traits in livestock
1.82
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