Artículo

Predictive biometrics of hair sheep through digital imaging

Chay Canul, Alfonso J.; Tapia González, Jorge; Canul Solís, Jorge; Casanova Lugo, Fernando; Piñeiro Vázquez, Ángel T.; Portillo Salgado, Rodrigo; García Herrera, Ricardo; Vargas Bello Pérez, Einar

Facultad de Medicina Veterinaria y Zootecnia, UNAM, publicado en Veterinaria México OA y cosechado de y cosechado de Revistas UNAM

Licencia de uso

La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY 4.0 Internacional, https://creativecommons.org/licenses/by/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico vetmexicooa@fmvz.unam.mx. Ver términos de la licencia

Procedencia del contenido

Entidad o dependencia
Facultad de Medicina Veterinaria y Zootecnia, UNAM
Revista
Repositorio
Contacto
Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

Cita

Chay Canul, Alfonso J., et al. (2023). Predictive biometrics of hair sheep through digital imaging. Veterinaria México OA; Vol. 10, 2023. Recuperado de https://repositorio.unam.mx/contenidos/4149877

Descripción del recurso

Autor(es)
Chay Canul, Alfonso J.; Tapia González, Jorge; Canul Solís, Jorge; Casanova Lugo, Fernando; Piñeiro Vázquez, Ángel T.; Portillo Salgado, Rodrigo; García Herrera, Ricardo; Vargas Bello Pérez, Einar
Tipo
Artículo de Investigación
Área del conocimiento
Biotecnología y Ciencias Agropecuarias
Título
Predictive biometrics of hair sheep through digital imaging
Fecha
2023-09-06
Resumen
Direct collection of biometric measurements (BM) from sheep is an expensive and stressful procedure for animals; instead, indirect and novel methods have recently been used. The objective of this study was to use digital image analysis (DIA) to predict biometric measurements of Pelibuey sheep as a non-invasive approach under on-farm conditions. Withers height (WH), body length (BL), body diagonal length (BDL), and rib depth (RD) were predicted in Pelibuey ewes using DIA. Images were taken from the left flank of 65 nonpregnant and nonlactating Pelibuey ewes using a digital camera and analyzed by DIA. The BM determined from both in vivo and by DIA presented positive and moderate (P < 0.05) correlation coefficients (r) of 0.43, 0.66, 0.73, and 0.75 for BL, BDL, WH, and RD, respectively. Regression equations from BM by DIA had determination coefficients (r2) of 0.19, 0.44, 0.54, and 0.56 for BL, BDL, WH, and RD, respectively. The equations developed were from low to moderate precision (r2 = 0.18 to 55), moderate to high accuracy with a bias correction factor (Cb > 0.69), and low to moderate reproducibility index (> 0.30). Overall, the use of DIA was able to predict the BM in Pelibuey ewes with low to moderate precision and accuracy. Factors affecting the accuracy and precision of this relationship should be further investigated.
Tema
Body Measurements; Image Analysis; Linear Regression Equations; Image-processing; Tropical Conditions; Body Weight
Idioma
eng
ISSN
ISSN electrónico: 2448-6760

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