ABSTRACT Ventilation systems are incorporated at intensive poultry farms to control environment conditions and thermal comfort of broilers. The ventilation system operates based on environmental data, particularly measured by sensors of temperature and relative humidity. Sensors are placed at different positions of the facility. Quality, number and positioning of the sensors are critical factors to achieve an efficient performance of the system. For this reason, a strategic positioning of the sensors associated to controllers could support the maintenance and management of the microclimate inside the facility. This research aims to identify the three most representative points for the positioning of sensors in order to support the ventilation system during the critical period from 12h00 to 15h00 on summer days. Temperature, relative humidity and wind speed were measured in four different tunnel ventilated barns at the final stage of the production cycle. The descriptive analysis was performed on these data. The Temperature and Humidity Index (THI) was also calculated. Then, the geostatistical analysis of THI was performed by GS+ and the position of sensors was determined by ordinary kriging. The methodology was able to detect the most representative points for the positioning of sensors in a case study (southeastern Brazil). The results suggested that this strategic positioning would help controllers to obtain a better inference of the microclimate during the studied period (the hottest microclimate), considered critical in Brazil. In addition, these results allow developing a future road map for a decision support system based on 24 h monitoring of the ventilation systems in broiler houses.

Thermal comfort is of great importance in preserving body temperature homeostasis during thermal stress conditions. Although the thermal comfort of horses has been widely studied, there is no report of its relationship with surface temperature (T S). This study aimed to assess the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. T S was obtained using infrared thermography image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The variables of armpit, croup, breast and groin T S of horses and the predicted classes were then subjected to a machine learning process. All variables in the dataset were considered relevant for the classification problem and the decision-tree model yielded an accuracy rate of 74 %. The feature selection methods used to reduce computational cost and simplify predictive learning decreased model accuracy to 70 %; however, the model became simpler with easily interpretable rules. For both these selection methods and for the classification using all attributes, armpit and breast T S had a higher power rating for predicting thermal comfort. Data mining techniques show promise in the discovery of new variables associated with the thermal comfort of horses.

No Brasil frangos de corte são normalmente alojados de 1 até 42 dias, quando são expostos a procedimentos como: jejum, apanha, colocação em caixas e transporte até o abate. Manter a homeostase do corpo é de grande importância para a sobrevivência de frangos de corte sob ambiente quente, especialmente na 7ª semana de crescimento. A perda de calor varia nas partes do corpo e está relacionada à temperatura do ar e à cobertura de penas. Avaliou-se a distribuição da temperatura superficial usando o processamento de imagens de câmera termográfica infravermelho, para caracterizar a temperatura superficial de frangos de corte de 42 dias de idade, no período anterior à apanha para o abate. Os frangos foram alojados de 1 a 42 dias e, antes de serem apanhados e transportados para o abate, foram registradas temperaturas superficiais infravermelho durante o dia.. Os resultados dos termogramas das regiões com penas e sem penas foram comparados, durante o 42º dia. Alta correlação entre regiões sem penas e a temperatura ambiente foi encontrada, mostrando que estas áreas respondem rapidamente a alterações no ambiente do alojamento. Duas funções foram desenvolvidas para predizer a temperatura superficial das regiões com e sem penas, do corpo de frangos com 42 dias, sendo conhecida a temperatura do ar do ambiente.

Broiler chickens in Brazil are generally reared from 1 to 42 days when they are exposed to procedures such as fasting, harvesting, crating and transport to slaughter. Maintaining homeostasis is of great importance for broiler survival under harsh environment especially prior to slaughter. Heat loss varies in the distinct parts of the body during the growth period, and it is related to the air temperature of the environment and to the amount of feather covering. This research aimed to study the surface temperature distribution using infrared thermographic image processing to characterize 42 day old broiler chicken surface temperature prior to slaughter. Broilers were reared for 42 days and prior to harvest and transport to slaughter the infrared surface temperature was recorded along the day. Data from the thermograms taken in feather and featherless regions were compared during the 42nd day of growth. High correlation between featherless regions and air temperature was found showing that these areas respond fast to changes in the rearing environment. Two functions were developed for predicting both surface temperature for featherless and feather covered areas of the broiler body parts.