Sensor-based behavioral patterns can identify heat-sensitive lactating dairy cows.
Int J Biometeorol
; 67(12): 2047-2054, 2023 Dec.
Article
en En
| MEDLINE
| ID: mdl-37783954
ABSTRACT
Heat stress impairs the health and performance of dairy cows, yet only a few studies have investigated the diversity of cattle behavioral responses to heat waves. This research was conducted on an Italian Holstein dairy farm equipped with precision livestock farming sensors to assess potential different behavioral patterns of the animals. Three heat waves, defined as at least five consecutive days with mean daily temperature-humidity index higher than 72, were recorded in the farm area during the summer of 2021. Individual daily milk yield data of 102 cows were used to identify "heat-sensitive" animals, meaning the cows that, under a given heat wave, experienced a milk yield drop that was not linked with other health events (e.g., mastitis). Milk yield drops were detected as perturbations of the lactation curve estimated by iteratively using Wood's equation. Individual daily minutes of lying, chewing, and activity were retrieved from ear-tag-based accelerometer sensors. Semi-parametric generalized estimating equations models were used to assess behavioral deviations of heat-sensitive cows from the herd means under heat stress conditions. Heat waves were associated with an overall increase in the herd's chewing and activity times, along with an overall decrease of lying time. Heat-sensitive cows spent approximately 15 min/days more chewing and performing activities (p < 0.05). The findings of this research suggest that the information provided by high-frequency sensor data could assist farmers in identifying cows for which personalized interventions to alleviate heat stress are needed.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Lactancia
/
Trastornos de Estrés por Calor
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Animals
Idioma:
En
Revista:
Int J Biometeorol
Año:
2023
Tipo del documento:
Article
País de afiliación:
Italia
Pais de publicación:
EEUU
/
ESTADOS UNIDOS
/
ESTADOS UNIDOS DA AMERICA
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EUA
/
UNITED STATES
/
UNITED STATES OF AMERICA
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US
/
USA