Predicting Heat Stress in Dairy Cattle Using Temperature-Humidity Index
Author Information
Author(s): Herrera-González José Luis, Rodríguez-Venegas Rafael, Legarreta-González Martín Alfredo, Robles-Trillo Pedro Antonio, De-Santiago-Miramontes Ángeles, Loya-González Darithsa, Rodríguez-Martínez Rafael
Primary Institution: Universidad Autónoma Agraria Antonio Narro
Hypothesis
Can the temperature-humidity index (THI) be effectively predicted using time series analysis in the dairy region of northern Mexico?
Conclusion
The study found that the temperature-humidity index can be predicted based on previous days' values, indicating an increase in heat stress risk for dairy cattle.
Supporting Evidence
- The model predicts an increase in the number of days with heat stress risk for dairy cattle.
- The THI values can be estimated based on the previous four days' THI.
- The study utilized a comprehensive dataset spanning four years.
Takeaway
This study shows how scientists can use past weather data to predict when cows might get too hot, helping farmers take better care of them.
Methodology
A seasonal autoregressive integrated moving average (SARIMA) model was used to analyze daily temperature-humidity index data over four years.
Limitations
The study is limited to a specific geographic region and may not be generalizable to other areas with different climatic conditions.
Participant Demographics
The study focused on dairy cattle in the Comarca Lagunera region of northern Mexico.
Statistical Information
P-Value
2.407×10−16
Confidence Interval
[0.01026692, 0.01629877]
Statistical Significance
p<0.001
Digital Object Identifier (DOI)
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