Thermal signature: A method to extract characteristics from infrared thermography data applied to the development of animal heat stress classifier models.

Recent studies have investigated the use of infrared thermography (IRT) to monitor body surface temperature and correlate it with factors related to animal welfare and performance. In this context, this work proposes a new method for extracting characteristics for the temperature matrix obtained using IRT data from regions of the body surface of cows which, if associated with environmental variables through a machine learning algorithm it generates computational classifiers for heat stress condition. IRT data were collected from different parts of the body of 18 lactating cows housed in a free-stall, monitored for 40 non-consecutive days, three times a day (5:00 a.m., 1:00 p.m., and 7:00 p.m.), during summer and winter, along with physiological data (rectal temperature and respiratory rate) and meteorological data for each time. The IRT data is used to create a descriptor vector based on frequency, accounting for temperatures for a pre-defined range, referred to in the study as 'Thermal Signature' (TS). The generated database was used for training and assessing computational models based on Artificial Neural Network (ANN) to classify heat stress conditions. The models were built using the following predictive attributes for each instance: TS, air temperature, black globe temperature and wet bulb temperature. The goal attribute used for supervised training was the heat stress level classification generated from the rectal temperature and respiratory rate values measured. The models based on different ANN architectures were compared through metrics of the confusion matrix between predicted and measured data, obtaining better results with 8 TS ranges. The best accuracy for classification into four heat stress levels (Comfort, Alert, Danger, and Emergency) was 83.29% using the TS of the ocular region. The classifier for two heat levels of stress (Comfort and Danger) obtained accuracy of 90.10% also using the 8 TS bands of the ocular region.

Changes in the pattern of heat waves and the impacts on Holstein cows in a subtropical region.

This study aimed to evaluate the change in the air temperature and the impacts of heat waves using Climate Change Indexes on the physiological and productive responses of lactating Holstein cows. Daily data of maximum and minimum air temperature for 1981-2021 were used. Heat waves were determined using six Climate Change Indexes. Individual data on respiratory rate, rectal temperature, and milk yield were collected in the summers of 2018, 2019, and 2021. The temperature trend analysis showed a significant (p < 0.0001) increase in maximum temperature, minimum temperature, and days in a heat wave. All six indexes increased significantly (p > 0.01). The increase in warm nights (> 20 °C) and the hottest days (> 35 °C) was the highest since 2010. Heat waves were classified into short (< 5 days) and long (> 5 days) of greater (> 36 °C) or lesser (< 36 °C) intensity. During the long and short heat waves of greater intensity, the respiratory rate increased (p < 0.05) until the fourth day. On the other hand, rectal temperature was higher (p < 0.05) from the fourth day until the end of the long heat waves. Therefore, the decrease in milk yield was significantly greater from the fourth or fifth day onwards. Finally, the evaluation method based on indexes was efficient to demonstrate the negative effects on physiological parameters and milk yield and can be indicated to evaluate heat stress in lactating cows.

Welfare traits of Bos indicus cattle castrated immunologically and fed beta-adrenergic agonists.

OBJECTIVE: This work was carried out to evaluate the effects of zilpaterol hydrochloride (ZH) and ractopamine hydrochloride (RH) combined with immunocastration on the welfare traits of feedlot Nellore cattle. METHODS: Ninety-six Nellore males (average body weight [BW] = 409±50 kg; average 20 mo of age) were divided into two groups according to BW; half of the animals in each group received two doses of an immunocastration (ImC) vaccine in a 30 day interval, and the other half did not receive the vaccine (NoC). Afterward, the animals were housed and fed a common diet for 70 days. Then, they were split into three groups and fed one of the following diets for 30 additional days: control (CO) diet, with no ß-AA; ZH diet, containing 80 mg/d ZH; and RH diet, containing 300 mg/d RH. Welfare traits were assessed by monitoring body surface temperature using infrared thermography (IRT) and plasma cortisol and temperament measurements. RESULTS: There was no interaction between sexual condition and diet for any trait. The ImC and NoC groups did not differ in rectal and ocular temperatures. The ImC animals had higher flight speeds (p = 0.022) and tended to have higher cortisol levels (p = 0.059) than the NoC animals. Animals fed ZH and RH did not differ in cortisol levels, respiratory rate, rectal temperature, temperature measured by IRT, or temperament behaviour. CONCLUSION: The ImC animals showed a less stable temperament during handling practices than NoC, whereas ZH and RH supplementation had no adverse effects on animal welfare.