| Revista: | Revista Brasileira de Zootecnia |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000445590 |
| ISSN: | 1516-3598 |
| Autores: | Weber, Vanessa Aparecida de Moraes1 Weber, Fabricio de Lima2 Gomes, Rodrigo da Costa3 Oliveira-Junior, Adair da Silva2 Menezes, Geazy Vilharva2 Abreu, Urbano Gomes Pinto de1 Belete, Nícolas Alessandro de Souza1 Pistori, Hemerson1 |
| Instituciones: | 1Universidade Catolica Dom Bosco, Campo Grande, Mato Grosso do Sul. Brasil 2Universidade Federal de Mato Grosso do Sul, Faculdade de Computacao, Campo Grande, Mato Grosso do Sul. Brasil 3Empresa Brasileira de Pesquisa Agropecuaria, Gado de Corte, Campo Grande, Mato Grosso do Sul. Brasil |
| Año: | 2020 |
| Volumen: | 49 |
| País: | Brasil |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Descriptivo |
| Resumen en inglés | The objective with this study was to analyze the body measurements of Girolando cattle, as well as measurements extracted from their images, to generate a model to understand which measures further explain the cattle body weight. Therefore, the experiment physically measured 34 Girolando cattle (two males and 32 females), for the following traits: heart girth (HGP), circumference of the abdomen, body length, occipito-ischial length, wither height, and hip height. In addition, images of the dorsum and the body lateral area of these animals allowed measurements of hip width (HWI), body length, tail distance to the neck, dorsum area (DAI), dorsum perimeter, wither height, hip height, body lateral area, perimeter of the lateral area, and rib height. The measurements extracted from the images were subjected to the stepwise regression method and regression-based machine learning algorithms. The HGp was the physical measure with stronger positive correlation with respect to body weight. In the stepwise method, the final model generated R² of 0.70 and RMSE of 42.52 kg and the equation: WEIGHT ( kg ) = 6.15421 * HW I ( cm ) + 0.01929 * DA I ( cm 2 ) + 70.8388. The linear regression and SVM algorithms obtained the best results, followed by discretization regression with random forests. The set of rules presented in this study can be recommended for estimating body weight in Girolando cattle, at a correlation coefficient of 0.71, by measurements of hip width and dorsum area, both extracted from cattle images |
| Disciplinas: | Medicina veterinaria y zootecnia, Ciencias de la computación |
| Palabras clave: | Bovinos, Procesamiento de datos, Predicción, Ganancia de peso, Girolando, Imágenes, Morfometría |
| Keyword: | Bovines, Data processing, Prediction, Weight gain, Girolando, Images, Morphometry |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
