Estrus Prediction Models for Dairy Gyr Heifers

Autor: Rogério Ribeiro Vicentini, Lenira El Faro, João Alberto Negrão, Renata Veroneze, Valesca Vilela Andrade, Priscila Arrigucci Bernardes, Aska Ujita, André Penido Oliveira
Rok vydání: 2021
Předmět:
Zdroj: Animals, Vol 11, Iss 3103, p 3103 (2021)
Animals
Volume 11
Issue 11
Animals : an Open Access Journal from MDPI
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
ISSN: 2076-2615
Popis: Technological devices are increasingly present in livestock activities, such as identifying the reproductive status of cows. For this, predictive models must be accurate and usable in the productive context. The aims of this study were to evaluate estrus-associated changes in reticulo-rumen temperature (RRT) and activity (ACT) in Dairy Gyr heifers provided by reticulo-rumen boluses and to test the ability of different models for estrus prediction. The RRT and ACT of 45 heifers submitted to estrus synchronization were recorded using reticulo-rumen boluses. The means of RRT and ACT at different time intervals were compared between the day before and the day of estrus manifestation. An analysis of variance of RRT and ACT was performed using mixed models. A second approach employed logistic regression, random forest, and linear discriminant analysis models using RRT, ACT, time of day, and the temperature-humidity index (THI) as predictors. There was an increase in RRT and ACT at estrus (p <
0.05) compared to the same period on the day before and on the day after estrus. The random forest model provided the best performance values with a sensitivity of 51.69% and specificity of 93.1%. The present results suggest that RRT and ACT contribute to the identification of estrus in Dairy Gyr heifers.
Databáze: OpenAIRE
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