Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography

Abstract

ABSTRACT:The objective of this study was to evaluate the thermoregulatory response of dairy buffaloes in pre-milking and post-milking. To identify animal thermoregulatory capacity, skin surface temperatures were taken by an infrared thermometer (SST), a thermographic camera (MTBP) as well as respiratory rate records (RR). Black Globe and Humidity Index (BGHI), radiating thermal load (RTL) and enthalpy (H) were used to characterize the thermal environment. Artificial Neural Networks analyzed those indices as well as animal physiological data, using a single layer trained with the least mean square (LMS) algorithm. The results indicated that pre-milking and post-milking environments reached BGHI, RR, SST and MTBP values above thermal neutrality zone for buffaloes. In addition, limits of surface skin temperatures were mostly influenced by changing ambient conditions to the detriment of respiratory rates. It follows that buffaloes are sensitive to environmental changes and their skin temperatures are the best indicators of thermal comfort in relation to respiratory rate.KEYWORDS: buffalo, heat stress, respiratory rate, surface temperature. AVALIAÇÃO DA CAPACIDADE TERMORREGULATÓRIA DE BÚFALAS LEITEIRAS UTILIZANDO TERMOGRAFIA DE INFRAVERMELHORESUMO: O objetivo deste trabalho foi avaliar a resposta termorregulatória de búfalas leiteiras nos ambientes de pré-ordenha (sala de espera) e pós-ordenha. Para identificar a capacidade termorregulatória dos animais, coletou-se a temperatura de superfície da pele, utilizando um termômetro de infravermelho (TMPT) e uma câmera termográfica (TMPC), e a frequência respiratória (FR) dos animais. Para a caracterização do ambiente térmico, foram calculados o índice de temperatura de globo e umidade (ITGU), a carga térmica radiante (CTR) e a entalpia (H). Os índices e os dados fisiológicos dos animais foram analisados utilizando-se de Redes Neurais Artificiais com uma única camada, treinadas com o algoritmo mínimo quadrado médio (LMS -Least mean square). Os resultados indicaram que os ambientes de pré e pós-ordenha alcançaram valores de ITGU, FR, TMPT e TMPC acima dos limites relacionados à zona de termoneutralidade dos bubalinos, sendo a temperatura superficial da pele influenciada mais intensamente pela variação das condições ambientais em detrimento da frequência respiratória. Conclui-se que os bubalinos são sensíveis às variações ambientais, sendo o s valores de temperatura de superfície da pele melhores indicadores de conforto térmico em relação à frequência respiratória.

Effect of estrous cycle phase on vulvar, orbital area and muzzle surface temperatures as determined using digital infrared thermography in buffalo

“…The vulva, muffle and orbital area surface temperatures (measured by IDT) and the rectal temperatures obtained in the present study are similar to previous studies in dairy cows (Talukder et al, 2014;Chacur et al, 2016b) and dairy buffalo (Barros et al, 2016;Sevegnani et al, 2016). Thus, the IDT technique is of potential applicability in the study of the physiological modifications of body temperature in buffalo.…”

“…The applicability of IDT in buffalo has recently been demonstrated. It was verified that the skin temperatures of the orbital area, flank and ears are subject to weather variations and correlated with rectal temperature and can be used in studies of thermal comfort in these animals (Barros et al, 2016;Sevegnani et al, 2016).…”

Infrared thermography: A potential noninvasive tool to monitor udder health status in dairy cows

“…IRT is widely used to identify localized areas of inflammation, such as mastitis in lactating cows [17-19], foot and mouth disease [20], assessment of tissue damage and healing due to hot versus cold branding in cattle [21], Laminitis [7,8], detection of bovine viral diarrhea in calves [22], monitoring respiratory disorders [23], Actinobacillus pleuropneumoniae infection in pigs [24], detection of estrus and prediction of ovulation in cattle and gilts [5,6,25,26], to assess the effect of scrotal temperature on sperm production in bulls [27-29], assessing meat quality in pigs [30], for identification of stress [31], measurement of feather cover [32], effects of machine milking on teat and udder [33], surface temperature, estimation of heat and methane production in dairy cattle [34], screening of cattle for feed utilization efficiency [9,35], pregnancy diagnosis in mare and wild animals [36,37], evaluation of thermal status of neonatal pigs [38], monitoring stress during animal transit and welfare in wild animals [39], assessment of surface temperature of buffaloe bulls and its correlation with rectal temperature [40] and for the evaluation of thermoregulatory capacity of dairy buffaloes [41]. …”

Prediction of mean surface temperature of broiler chicks and load microclimate during transport

“…The results were obtained using the 10-fold cross validation, according to the methodology used by MITCHELL (1997), SILVA et al (2008aSILVA et al ( , 2008b, ATA (2015) and SEVEGNANI et al (2016). The sampling method 10-fold cross validation partitions the total data set into 10 equal parts, using nine parts to train and one to test.…”

“…The selection of these equations was based on the highest values of the correlation coefficient and R 2 , as MITCHELL (1997), SILVA et al (2008aSILVA et al ( , 2008b, ATA (2015) and SEVEGNANI et al (2016). These models showed a positive correlation coefficient, which according to AYDIN et al (2015) it means that the studied variables are mutually dependents to each other and tend to increase or decrease simultaneously.…”