AUTHOR=Herbster Caio Julio Lima , Brito Neto Antonio de Sousa , Chagas Juana Catarina Cariri , Marcondes Marcos Inácio , Justino Evandra da Silva , Rocha Amanda Cardoso , Silva Luciano Pinheiro da , Bezerra Leilson Rocha , Chay-Canul Alfonso Juventino , Santos Stefanie Alvarenga , Oliveira Ronaldo Lopes , Pereira Elzania Sales 

TITLE=Prediction of water intake in hair sheep: development of a new model

JOURNAL=Frontiers in Animal Science

VOLUME=Volume 6 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/animal-science/articles/10.3389/fanim.2025.1694789

DOI=10.3389/fanim.2025.1694789

ISSN=2673-6225

ABSTRACT=The objective of this study was to establish equations for the prediction of the water intake (WI) of hair sheep. The data set used was derived from eight studies containing 185 individual observations of hair sheep:120 non-castrated males, 22 castrated males, and 43 females in a feedlot. A stepwise procedure was used, with a significance level of P < 0.05, to determine which variables would be included in the prediction model. Then, a random coefficient model was used, considering the random study effect and including the possibility of covariance between the intercept and slope. Furthermore, sex classes were considered a fixed effect and tested in the model parameters. To validate the model, the comparison between predicted and measured values was performed using the Model Evaluation System. The correlation between WI and metabolizable energy intake (MEI), body weight (BW), dry matter (DM), dry matter intake (DMI), and temperature-humidity index (THI) was significant (P<0.001), assuming values of 0.35, 0.37, 0.43, 0.54, and 0.57, respectively. The stepwise analysis indicated that DM and DMI were significant variables (P<0.001) for predicting WI in hair sheep. Sex classes did not affect (P = 0.3340) the model predicting WI in hair sheep; therefore, a single equation was generated: WI (kg/day) = 0.1282 (± 0.5861) + 2.4186 (± 0.5842) x DMI (R2 = 0.70, MSE = 0.1631, AIC = 297.6). The validation suggests that the model accurately predicts the water intake of sheep. In conclusion, the proposed model should be used to more accurately predict WI in hair sheep and contribute significantly to improving the rational use of water.