Abstract
Forecasts for comfort index to dairy cattle are unavailable in Brazil and the extraction rules on weather behavior can assist in predicting the animal's comfort, especially for those who are in unprotected places. This study aims to develop a methodology for extracting predictive rules from heat stress conditions in dairy cattle. The analysis was performed using the database of the National Institute of Meteorology (INMET), referring to the hourly averages for the period between September 15th to November 13th of 2013 in Santa Maria - RS, Brazil. The input variables were time of day, air temperature, dew point temperature, relative humidity and the temperature and humidity index. The extraction of the rules was done by the technique of Data Mining and the classification task by building the J48 decision tree algorithm. The classification of the Temperature and Humidity Index (THI) was based on two classes, being NORMAL for THI values less than or equal to 74, and ALERT to values above 74, considered as a promoter of stress. Data mining has resulted in the description of 11 rules of the relationship between temperature, relative humidity and time of day with the THI. Data mining has enabled the understanding of the variables analyzed and the generated rules can help in forecasts based on meteorological forecasts and environmental temperature controllers and relative humidity schedule.
Highlights
Great economic losses in livestock production are related to the thermal environment, associated to the reduction in food consumption and weight gain (NARDONE et al, 2006)
The temperature is not the only factor of the physical environment that influences the animal comfort, because it is directly related to the relative humidity
The determination of the temperature and humidity index (THI), an animal comfort index calculated from temperature and humidity can help to express adequately the degree of heat stress experienced by the animal
Summary
Great economic losses in livestock production are related to the thermal environment, associated to the reduction in food consumption and weight gain (NARDONE et al, 2006). There are few estimates of losses caused by heat, in the United States are estimated about 900 million dollars a year due to effects of heat stress in livestock (ST-PIERRE et al, 2003). When the ambient temperature is above the thermal comfort range of the animal, environmental adjustments are needed to maintain productivity standards (SOUSA et al, 2004). The temperature is not the only factor of the physical environment that influences the animal comfort, because it is directly related to the relative humidity. Moist areas present problems for animal performance when the air temperature is above 21°C and associated with higher relative humidity to 60% (CAMPOS & PIRES, 2001). The determination of the temperature and humidity index (THI), an animal comfort index calculated from temperature and humidity can help to express adequately the degree of heat stress experienced by the animal
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