Using biometric analysis to estimate body weight in Creole goats
Background: Creole goat husbandry for milk and meat improves food security in rural areas in Perú. Body weight (BW) is a key trait for selecting breeding stock, and it is estimated to be using algorithms. Likewise, BW is common in livestock farming. Aim: This study aimed to compare BW prediction mod...
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| Format: | Artículo |
| Language: | Inglés |
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Eldaghayes Publisher
2025
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| Online Access: | http://hdl.handle.net/20.500.12955/2910 https://doi.org/10.5455/OVJ.2025.v15.i9.55 |
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| author | Trillo Zárate, Fritz Carlos Paredes Chocce, Miguel Enrique Salinas Marcos, Jorge Temoche Socola, Víctor Alexander Tafur Gutiérrez, Lucinda Sessarego Dávila, Emmanuel Alexander Acosta Granados, Irene Carol Palomino Guerrera, Walter Cruz Luis, Juancarlos Alejandro Ruiz Chamorro, Jose Antonio |
| author_browse | Acosta Granados, Irene Carol Cruz Luis, Juancarlos Alejandro Palomino Guerrera, Walter Paredes Chocce, Miguel Enrique Ruiz Chamorro, Jose Antonio Salinas Marcos, Jorge Sessarego Dávila, Emmanuel Alexander Tafur Gutiérrez, Lucinda Temoche Socola, Víctor Alexander Trillo Zárate, Fritz Carlos |
| author_facet | Trillo Zárate, Fritz Carlos Paredes Chocce, Miguel Enrique Salinas Marcos, Jorge Temoche Socola, Víctor Alexander Tafur Gutiérrez, Lucinda Sessarego Dávila, Emmanuel Alexander Acosta Granados, Irene Carol Palomino Guerrera, Walter Cruz Luis, Juancarlos Alejandro Ruiz Chamorro, Jose Antonio |
| author_sort | Trillo Zárate, Fritz Carlos |
| collection | Repositorio INIA |
| description | Background: Creole goat husbandry for milk and meat improves food security in rural areas in Perú. Body weight (BW) is a key trait for selecting breeding stock, and it is estimated to be using algorithms. Likewise, BW is common in livestock farming.
Aim: This study aimed to compare BW prediction models using a data mining algorithm in Creole goats, considering their biometric measurements.
Methods: Data from 1,075 females aged between 1 and 4 years were used. Measurements of chest width, thoracic perimeter, wither height, sacrum height, rump width and length, body length, cannon bone perimeter, age, and region of the herd were recorded. The regression trees (classification and regression tree), support vector regression (SVR), and random forest regression (RFR) algorithms were used.
Results: The SVR was better at predicting BWs in Creole goat herds. Similarly, the results were stable during training (R² = 0.765) and testing (R² = 0.707). However, it should be noted that RFR performed better with training data (R² = 0.942).
Conclusion: The proposed predictive models have demonstrated significant potential for accurately predicting BW based on biometric data. Finally, it contributes to better selection, feeding, and sanitary management of Creole goats. |
| format | Artículo |
| id | INIA2910 |
| institution | Institucional Nacional de Innovación Agraria |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Eldaghayes Publisher |
| publisherStr | Eldaghayes Publisher |
| record_format | dspace |
| spelling | INIA29102025-10-28T21:22:00Z Using biometric analysis to estimate body weight in Creole goats Trillo Zárate, Fritz Carlos Paredes Chocce, Miguel Enrique Salinas Marcos, Jorge Temoche Socola, Víctor Alexander Tafur Gutiérrez, Lucinda Sessarego Dávila, Emmanuel Alexander Acosta Granados, Irene Carol Palomino Guerrera, Walter Cruz Luis, Juancarlos Alejandro Ruiz Chamorro, Jose Antonio Algorithms Creole Machine learning Predictive models Morphometrics goats Algoritmos Criollo Aprendizaje automático Modelos predictivos Morfometría de cabras https://purl.org/pe-repo/ocde/ford#4.03.01 Body weight; Peso corporal; Animal morphology; Morfología animal; Body measurements; Morfología animal Background: Creole goat husbandry for milk and meat improves food security in rural areas in Perú. Body weight (BW) is a key trait for selecting breeding stock, and it is estimated to be using algorithms. Likewise, BW is common in livestock farming. Aim: This study aimed to compare BW prediction models using a data mining algorithm in Creole goats, considering their biometric measurements. Methods: Data from 1,075 females aged between 1 and 4 years were used. Measurements of chest width, thoracic perimeter, wither height, sacrum height, rump width and length, body length, cannon bone perimeter, age, and region of the herd were recorded. The regression trees (classification and regression tree), support vector regression (SVR), and random forest regression (RFR) algorithms were used. Results: The SVR was better at predicting BWs in Creole goat herds. Similarly, the results were stable during training (R² = 0.765) and testing (R² = 0.707). However, it should be noted that RFR performed better with training data (R² = 0.942). Conclusion: The proposed predictive models have demonstrated significant potential for accurately predicting BW based on biometric data. Finally, it contributes to better selection, feeding, and sanitary management of Creole goats. This study received financial support from the project entitled "Improvement of Research and Technology Transfer" Services for the Sustainable Management of Goat Livestock in Dry Forests and the Central Coast across the following departments: Tumbes, Piura, Lambayeque, Amazonas, La Libertad, Ancash, Ayacucho, Ica, and Lima, with CUI 2506684, facilitated by the National Institute of Agrarian Innovation. 2025-10-20T16:13:17Z 2025-10-20T16:13:17Z 2025-09-30 info:eu-repo/semantics/article Trillo-Zárate, F., Paredes-Chocce, M. E., Salinas, J., Temoche-Socola, V. A., Tafur Gutiérrez, L., Sessarego, E. A., Acosta, I., Palomino-Guerrera, W., Cruz-Luis, J. A., & Ruiz-Chamorro, J. A. (2025). Using biometric analysis to estimate body weight in Creole goats. Open Veterinary Journal, 15(9), 4496-4504. https://doi.org/10.5455/OVJ.2025.v15.i9.55 http://hdl.handle.net/20.500.12955/2910 https://doi.org/10.5455/OVJ.2025.v15.i9.55 eng urn:issn:2226-4485 Open Veterinary Journal info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/nc/4.0/ application/pdf application/pdf Eldaghayes Publisher LY Instituto Nacional de Innovación Agraria Repositorio Institucional - INIA |
| spellingShingle | Algorithms Creole Machine learning Predictive models Morphometrics goats Algoritmos Criollo Aprendizaje automático Modelos predictivos Morfometría de cabras https://purl.org/pe-repo/ocde/ford#4.03.01 Body weight; Peso corporal; Animal morphology; Morfología animal; Body measurements; Morfología animal Trillo Zárate, Fritz Carlos Paredes Chocce, Miguel Enrique Salinas Marcos, Jorge Temoche Socola, Víctor Alexander Tafur Gutiérrez, Lucinda Sessarego Dávila, Emmanuel Alexander Acosta Granados, Irene Carol Palomino Guerrera, Walter Cruz Luis, Juancarlos Alejandro Ruiz Chamorro, Jose Antonio Using biometric analysis to estimate body weight in Creole goats |
| title | Using biometric analysis to estimate body weight in Creole goats |
| title_full | Using biometric analysis to estimate body weight in Creole goats |
| title_fullStr | Using biometric analysis to estimate body weight in Creole goats |
| title_full_unstemmed | Using biometric analysis to estimate body weight in Creole goats |
| title_short | Using biometric analysis to estimate body weight in Creole goats |
| title_sort | using biometric analysis to estimate body weight in creole goats |
| topic | Algorithms Creole Machine learning Predictive models Morphometrics goats Algoritmos Criollo Aprendizaje automático Modelos predictivos Morfometría de cabras https://purl.org/pe-repo/ocde/ford#4.03.01 Body weight; Peso corporal; Animal morphology; Morfología animal; Body measurements; Morfología animal |
| url | http://hdl.handle.net/20.500.12955/2910 https://doi.org/10.5455/OVJ.2025.v15.i9.55 |
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