Predicting the body weight of crossbred Holstein × Zebu dairy cows using multivariate adaptive regression splines algorithm
Vázquez-Martínez I. Tirink C. Casanova-Lugo F. Pozo-Leyva D. Mota-Rojas D. Kalmagambetov M.B. Uskenov R. Gülboy Ö. Garcia-Herrera R.A. Chay-Canul A.J.
1 August 2024Cambridge University Press
Journal of Dairy Research
2024#91Issue 3267 - 272 pp.
This study aimed to estimate live body weight from body measurements for Holstein × Zebu dairy cows (n = 156) reared under conditions of humid tropics in Mexico using multivariate adaptive regression splines algorithm (MARS) with several train-test proportions. The body measurements included withers height, rump height, hip width, heart girth, body length and diagonal body length. The data were divided into 65:35, 70:30 and 80:20 split data for training and testing sets, respectively. The MARS algorithm was used to construct a prediction model, which predicted the body weight from the body measurements of the test dataset. The results emphasized that the MARS algorithm had an explanation rate for 80:20 train and test set of 0.836 and 0.711, respectively, with minimum Akaike information criterion values. This indicates that it is a reliable way of predicting body weight from body measurements. The results suggest that body weight prediction can be performed with the MARS algorithm in a reliable way, therefore, this algorithm may be a useful tool for animal breeders and researchers in the development of feeding and selection-aimed approaches. Copyright
Body measurements , body weight , crossbred , multivariate adaptive regression splines (MARS) , tropical cows
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División Académica de Ciencias Agropecuarias, Universidad Juárez Autónoma de Tabasco, Villaher-mosa, Tabasco, Mexico
Benemérita Universidad Autónoma de Puebla, Complejo Regional Norte, Puebla, Tetela de Ocampo, Mexico
Faculty of Agriculture, Department of Animal Science, Igdir University, Igdir, TR76000, Turkey
Tecnológico Nacional de México, Instituto Tecnológico de la Zona Maya, Othón P. Blanco, Quintana Roo, Mexico
Department of Animal Production and Agriculture (DPAA), Universidad Autónoma Metropolitana Xochimilco Campus, Mexico City, 04960, Mexico
Aktobe Agricultural Experimental Station, Aktobe, Kazakhstan
Agronomic Faculty, S. Seifullin Kazakh Agrotechnical University, Z10P6B8, 62 Zhenis av., Astana, Kazakhstan
Faculty of Agriculture, Department of Animals Science, Ondokuz Mayis University, Samsun, TR55139, Turkey
División Académica de Ciencias Agropecuarias
Benemérita Universidad Autónoma de Puebla
Faculty of Agriculture
Tecnológico Nacional de México
Department of Animal Production and Agriculture (DPAA)
Aktobe Agricultural Experimental Station
Agronomic Faculty
Faculty of Agriculture
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