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Predicting the body weight of crossbred Holstein × Zebu dairy cows using multivariate adaptive regression splines algorithm

Published online by Cambridge University Press:  14 November 2024

Ignacio Vázquez-Martínez ,
Cem Tirink Open the ORCID record for Cem Tirink [Opens in a new window] ,
Fernando Casanova-Lugo ,
Dixan Pozo-Leyva ,
Daniel Mota-Rojas ,
Murat Baitugelovich Kalmagambetov ,
Rashit Uskenov ,
Ömer Gülboy ,
Ricardo A. Garcia-Herrera  and
Alfonso J. Chay-Canul Open the ORCID record for Alfonso J. Chay-Canul [Opens in a new window]
Ignacio Vázquez-Martínez
Affiliation:
División Académica de Ciencias Agropecuarias, Universidad Juárez Autónoma de Tabasco, Villaher-mosa, Tabasco, México Benemérita Universidad Autónoma de Puebla, Complejo Regional Norte, Tetela de Ocampo, Puebla, México
Cem Tirink*
Affiliation:
Faculty of Agriculture, Department of Animal Science, Igdir University, TR76000, Igdir, Türkiye
Fernando Casanova-Lugo
Affiliation:
Tecnológico Nacional de México, Instituto Tecnológico de la Zona Maya, Othón P. Blanco, Quintana Roo, México
Dixan Pozo-Leyva
Affiliation:
Tecnológico Nacional de México, Instituto Tecnológico de la Zona Maya, Othón P. Blanco, Quintana Roo, México
Daniel Mota-Rojas
Affiliation:
Neurophysiology, Behavior and Animal Welfare Assessment, Department of Animal Production and Agriculture (DPAA), Universidad Autónoma Metropolitana Xochimilco Campus, Mexico City 04960, Mexico
Murat Baitugelovich Kalmagambetov
Affiliation:
Aktobe Agricultural Experimental Station, Aktobe, Republic of Kazakhstan
Rashit Uskenov
Affiliation:
Agronomic Faculty, S. Seifullin Kazakh Agrotechnical University, Z10P6B8, 62 Zhenis av., Astana, Kazakhstan
Ömer Gülboy
Affiliation:
Faculty of Agriculture, Department of Animals Science, Ondokuz Mayis University, TR55139, Samsun, Türkiye
Ricardo A. Garcia-Herrera
Affiliation:
División Académica de Ciencias Agropecuarias, Universidad Juárez Autónoma de Tabasco, Villaher-mosa, Tabasco, México
Alfonso J. Chay-Canul
Affiliation:
División Académica de Ciencias Agropecuarias, Universidad Juárez Autónoma de Tabasco, Villaher-mosa, Tabasco, México
*
Corresponding author: Cem Tirink; Email: [email protected]
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Abstract

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.

Keywords

Body measurementsbody weightcrossbredmultivariate adaptive regression splines (MARS)tropical cows
Type
Research Article
Information
Journal of Dairy Research , Volume 91 , Issue 3 , August 2024 , pp. 267 - 272
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of Hannah Dairy Research Foundation

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