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The objective of this research is to apply exploratory analysis and modeling associated with abiotic factors, physiological and behavioral variables of swine in the semi-arid region. The experimental design used was completely randomized, in a 3 × 3 factorial scheme, randomly distributed in nine pens, with three animals. The behavior of the animals was recorded using images and analyzed within 10-min interval. The data analysis used was multivariate, using the clustering method (tree diagram) and principal component analysis (PCA), in order to establish the main predictors of swine ingestive behavior, using multiple linear regression models. The PCA showed satisfactory results, in which the lowest eigenvalue observed was 2.82 and the accumulated variance for the treatments ranged from 69.70 to 94% for the first two principal components. Through exploratory data analysis, it was possible to identify the relationship between biotic and abiotic factors with the ingestive behavior of pigs in the finishing phase. Based on the results of the multivariate analysis, the most promising predictor variables for estimating the regression models were determined. Adiabatic evaporative cooling associated with 18 h of light was the combination of factors with the best results, presenting models for eating and drinking behavior, i.e. a complete ingestive characterization.

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Heat stress is one of the most important environmental challenges faced by dairy cattle, with a deleterious effect on animal production and welfare. This research was conducted to evaluate the effects of the thermal environment on the physiological and behavioral responses of dairy cattle in a rotational picket. The research was conducted on an experimental farm, located in the Agreste region of the state of Pernambuco, Brazil. The animals were managed in a rotational picket system of signal grass, with an occupation and a rest period of 7 and 28 days, respectively, for a stocking rate of 3.2 AU ha-1. The determination of the effect of stressors on the animals was performed by recording the dry bulb temperature (°C), and the relative humidity, which allowed the characterization of the thermal environment by the temperature and humidity index and by the specific enthalpy (kJ kg-1). The physiological variables monitored were respiratory rate (mov. min-1), rectal temperature (°C), and skin temperature (°C). The behavioral responses quantified were activities, walking, ruminating, idling and ingestive behaviors, eating, and drinking, with the percentage of time spent on each activity being recorded. According to the canonical multivariate analysis, the chi-square test, and the variation of physiological patterns, the animals, even in a situation of greater thermal challenge, presented physiological responses within conditions considered normal; however, they reduced grazing activity (eating) during the hottest hours and increased the activities of rumination and idling.

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The Intergovernmental Panel on Climate Change (IPCC) has pointed out the high vulnerability of developing countries to climate change, which is expected to impact food and income security. Sheep farming is one of the main animal productions among the families located in the most vulnerable regions of the semiarid region of Pernambuco state, a Brazilian territory known for its high temperatures, low relative humidity, and high net solar radiation. Therefore, the objective of this study was to identify different regions of Pernambuco that may be more suitable for different breeds of sheep, based on non-parametric statistics and kriging maps of the temperature and humidity index (THI). THI values were determined based on mean annual temperature and wind speed extracted from the TerraClimate remote sensing database. Pernambuco state presented THI values ranging from 66 to 79, with the hair breeds having a high potential for exploitation in almost all territories, including the main meat-producing breeds. The East Friesian breed, a high milk producer, would be well suited to the Agreste mesoregion, a territory that, like the Pajeú and Moxotó microregions, also proved favorable for the introduction of three wool breeds (Suffolk, Poll Dorset, and Texel) known as major meat producers. The kriging maps of the THI values successfully allowed the identification of strategic development regions of Pernambuco state with high potential for sheep breeding.

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The coronavirus pandemic has seriously affected human health, although some improvements on environmental indexes have temporarily occurred, due to changes on socio-cultural and economic standards. The objective of this study was to evaluate the impacts of the coronavirus and the influence of the lockdown associated with rainfall on the water quality of the Capibaribe and Tejipió rivers, Recife, Northeast Brazil, using cloud remote sensing on the Google Earth Engine (GEE) platform. The study was carried out based on eight representative images from Sentinel-2. Among the selected images, two refer to the year 2019 (before the pandemic), three refer to 2020 (during a pandemic), two from the lockdown period (2020), and one for the year 2021. The land use and land cover (LULC) and slope of the study region were determined and classified. Water turbidity data were subjected to descriptive and multivariate statistics. When analyzing the data on LULC for the riparian margin of the Capibaribe and Tejipió rivers, a low permanent preservation area was found, with a predominance of almost 100% of the urban area to which the deposition of soil particles in rivers are minimal. The results indicated that turbidity values in the water bodies varied from 6 mg. L-1 up to 40 mg. L-1. Overall, the reduction in human-based activities generated by the lockdown enabled improvements in water quality of these urban rivers.

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Effective planning animal transport is essential to safeguard animal welfare and reduce production losses. Environmental conditions, specifically extreme temperatures in combination with ranges of relative humidity are highlighted as one of the main risk factors for production losses during transport (e.g., fatalities). The majority of research evaluating both welfare and production impacts of pig transport have been primarily undertaken in Europe and North America, which cover a relatively limited range of distinct climates (e.g., temperate, sub-arctic, etc.). As a result, research on pig transport in semi-arid conditions is lacking. In this study, we evaluated the effects of both distance (short, 30 km; and long, 170 km) and transport daily periods (morning, (05:00-11:00); afternoon (12:00-17:00); and night, (23:00-04:00)) on the preslaughter losses and heat stress of pigs in commercial transport in a semiarid region. Across 19 journeys of standard slaughter-weight pig loads (124.0 ± 2.8 kg), 684 focal animals (36 per journey) were evaluated. For each journey, the load's thermal profile (THIadj and enthalpy) and physiological responses of individual pigs were recorded. On arrival at designated slaughterhouses, the percentage pig of non-ambulatory non-injured (NANI), non-ambulatory injured (NAI), death on arrival (DOA), and total losses were recorded. Short journeys in the afternoon were shown to be more detrimental to the thermal comfort of pigs, with higher rectal temperatures recorded. The highest percentage of total losses and DOA occurred in afternoon journeys, irrespective of distance, followed by the morning, with the lowest losses observed in pigs transported at night. Additionally, total losses and DOA were further exacerbated by journey distance, with higher rates observed in short journeys. Higher percentage averages of NANI and NAI were observed in shorter journeys, but daily periods effects were only observed for NANI. These results further demonstrate the welfare and production loss risks associated with journey distance and time of day (representing varying environmental conditions) during road transport of pigs, whilst providing novel data in semiarid conditions. Careful and effective planning for pig transportation is essential to minimize heat stress and production losses. Consideration of the thermal environment on the day of travel, as well as providing flexibility to adjust travel times (e.g., early morning or evening), should help to mitigate risks of heat stress and production losses during pig transport.

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This study aimed to analyze the principal componentsof the meteorological variables, physiological and behavioral response of cowssubjected to different coolingtimes and their influence on milk quality, in the dryand rainfallperiods, and to establish multiple regression models for milk quality. The data used in the study came from an experiment conducted in the Agreste Region of Pernambuco.The pre-milking coolingtime was 10, 20, 30 min.and the control (without cooling). Sixteen multiparous lactating Gir cows were selected. Data were analyzed by principal component analysis and a multiple regression analysis was applied to determine milk quality. There was a strong relationship between somatic cell count (SCC) and activity of the animal in the shade for dry,and lying for rainfall, with increased SCC in cow milk. It was possible to establish two multiple regression models to determine milk quality in dryand rainfall periods. According to the principal component analysis, the coolingtime tomeet the thermal requirement of the animals was 20 min., regardless of the season and milking shift.(AU)

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This study aimed to analyze the principal componentsof the meteorological variables, physiological and behavioral response of cowssubjected to different coolingtimes and their influence on milk quality, in the dryand rainfallperiods, and to establish multiple regression models for milk quality. The data used in the study came from an experiment conducted in the Agreste Region of Pernambuco.The pre-milking coolingtime was 10, 20, 30 min.and the control (without cooling). Sixteen multiparous lactating Gir cows were selected. Data were analyzed by principal component analysis and a multiple regression analysis was applied to determine milk quality. There was a strong relationship between somatic cell count (SCC) and activity of the animal in the shade for dry,and lying for rainfall, with increased SCC in cow milk. It was possible to establish two multiple regression models to determine milk quality in dryand rainfall periods. According to the principal component analysis, the coolingtime tomeet the thermal requirement of the animals was 20 min., regardless of the season and milking shift.

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The aim of this study was to employ the principal component technique to physiological data and environmental thermohygrometric variables correlated with detection of clinical and subclinical mastitis in dairy cattle. A total of 24 lactating Girolando cows with different clinical conditions were selected (healthy, and with clinical or subclinical mastitis). The following physiological variables were recorded: udder surface temperature, ST (°C); eyeball temperature, ET (°C); rectum temperature, RT (°C); respiratory frequency, RF (mov. min-1). Thermohygrometric variables included air temperature, AirT (°C), and relative humidity, RU (%). ST was determined by means of thermal images, with four images per animal, on these quarters: front left side (FL), front right side (FR), rear right side (RR) and rear left side (RL), totaling 96 images. Exploratory data analysis was run through multivariate statistical technique with the employment of principal components, comprehending nine variables: ST on the FL, FR, RL and RR quarters; ET, RT; RF, AirT and RU. The representative quarters of the animals with clinical and subclinical mastitis showed udder temperatures 8.55 and 2.46° C higher than those of healthy animals, respectively. The ETs of the animals with subclinical and clinical mastitis were, respectively, 7.9 and 8.0% higher than those of healthy animals. Rectum temperatures were 2.9% (subclinical mastitis) and 5.5% (clinical mastitis) higher compared to those of healthy animals. Respiratory frequencies were 40.3% (subclinical mastitis) and 61.6% (clinical mastitis) higher compared to those of healthy animals. The first component explained 91% of the total variance for the variables analyzed. The principal component technique allowed verifying the variables correlated with the animals' clinical condition and the degree of dependence between the study variables.

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The aim of this study was to employ the principal component technique to physiological data and environmental thermohygrometric variables correlated with detection of clinical and subclinical mastitis in dairy cattle. A total of 24 lactating Girolando cows with different clinical conditions were selected (healthy, and with clinical or subclinical mastitis). The following physiological variables were recorded: udder surface temperature, ST (°C); eyeball temperature, ET (°C); rectum temperature, RT (°C); respiratory frequency, RF (mov. min-1). Thermohygrometric variables included air temperature, AirT (°C), and relative humidity, RU (%). ST was determined by means of thermal images, with four images per animal, on these quarters: front left side (FL), front right side (FR), rear right side (RR) and rear left side (RL), totaling 96 images. Exploratory data analysis was run through multivariate statistical technique with the employment of principal components, comprehending nine variables: ST on the FL, FR, RL and RR quarters; ET, RT; RF, AirT and RU. The representative quarters of the animals with clinical and subclinical mastitis showed udder temperatures 8.55 and 2.46° C higher than those of healthy animals, respectively. The ETs of the animals with subclinical and clinical mastitis were, respectively, 7.9 and 8.0% higher than those of healthy animals. Rectum temperatures were 2.9% (subclinical mastitis) and 5.5% (clinical mastitis) higher compared to those of healthy animals. Respiratory frequencies were 40.3% (subclinical mastitis) and 61.6% (clinical mastitis) higher compared to those of healthy animals. The first component explained 91% of the total variance for the variables analyzed. The principal component technique allowed verifying the variables correlated with the animals' clinical condition and the degree of dependence between the study variables.(AU)

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The objective of this research was to assess the spatial variability pattern concerning udder surface temperature in dairy cows that were healthy and in those with mastitis. A total of 24 animals were selected - eight healthy, eight with subclinical mastitis, and eight with clinical mastitis. Images were taken with a Flir i60 thermographic camera - resolution of 0.01°C, focal length of 1.0 m, and emissivity adjusted to 0.98 - between 05:00 and 07:00, totaling 96 images, three per animal, of the front and rear, right and left mammary quarters. Analyses were run through geostatistics, with semivariogram adjustment to validate the theoretical model and build kriging maps. The average surface temperature of the mammary quarters with positive classification for subclinical mastitis stood between 33.2 ± 0.67ºC and 34.64± 1.07ºC; for negative quarters, values ranged from 29.3 ± 1.78ºC to 32.24 ± 0.62ºC. The udder surface temperatures of healthy animals were lower than those of animals with subclinical mastitis (29.3ºC ± 1.78 and 31.58ºC ± 0.62). The udder surface temperature of animals with clinical mastitis was higher, between 34.0 and 37.5°C, compared to the other clinical statuses. The scale adopted for image pattern analysis successfully identified the spatial dependence of udder surface temperature, which helped standardize diagnostic procedures for healthy animals, and for those with subclinical and clinical mastitis, by means of geostatistics.(AU)

Objetivou-se com essa pesquisa avaliar o padrão de variabilidade espacial da temperatura de superfície do úbere de vacas leiteiras saudáveis e com mastite. Foram selecionados 24 animais, oito saudáveis, oito com mastite subclínica e oito com mastite clínica. As imagens foram obtidas a partir de uma câmera termográfica Flir i60, resolução de 0,01 °C, 1,0 m de distância focal e emissividade ajustada para 0,98. O horário de realização das imagens foi entre às 05 e 07h00, que totalizaram 96 imagens, três por animal, nos enquadramentos anterolateral direito, anterolateral esquerdo, posterior e inferior. As análises foram realizadas pela geoestatística, com ajuste do semivariograma para validação do modelo teórico e construção dos mapas de krigagem. A temperatura média de superfície dos quartos mamários com classificação positiva para mastite subclínica apresentou valores entre 33,2 ± 0,67ºC e 34,64± 1,07ºC; para os quartos negativos entre 29,3 ± 1,78ºC e 32,24 ± 0,62ºC. Os animais saudáveis apresentaram temperatura de superfície de úbere inferior àqueles com mastite subclínica (29,3ºC ± 1,78 e 31,58ºC ± 0,62). A temperatura da superfície do úbere dos animais com mastite clínica foi mais elevada, entre 34,0 e 37,5°C, comparativamente aos demais quadros clínicos. A escala adotada para análise do padrão das imagens identificou com sucesso a dependência espacial da temperatura de superfície do úbere, o que contribuiu para padronização dos procedimentos de diagnóstico para animais saudáveis, com mastite subclínica e clínica, por meio da geoestatística.(AU)

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