Heat Stress In Cattle Research Articles

The Impact of Climate Variability on Cattle Heat Stress in Vanuatu

Heat stress is a climate extreme that impacts cattle health, fertility, feed intake, production, and well-being. In Vanuatu, the beef industry is crucial to local livelihoods and the nation’s economy, thus the objective of this study was to examine the impact of heat stress on cattle health and production. This study uses the Heat Load Index (HLI) and Accumulated Heat Load (AHL) as proxies to assess the impact of heat stress on cattle in Vanuatu over a 30-year period (1994–2023), using the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5) data. The analysis examines historical patterns of heat stress in cattle across Vanuatu, identifying more instances of heat stress occurring during the wet season due to characteristically elevated temperatures, humidity, and low wind speeds. Findings also suggest that El Niño events may increase the intensity and duration of heat stress events. These insights inform the development of an Early Warning System for heat stress in cattle, establishing a crucial foundation for targeted adaptation strategies aimed at enhancing the resilience and sustainability of Vanuatu’s beef industry to climate variability and change.

Impact of temperature humidity index (THI) on blood gas and electrolytes of dairy cows in late gestation

The study was carried out to assess the impact of heat stress on dairy cows in late gestation and their newborn calves. Study was conducted in two phases in crossbred cattle during last trimester of pregnancy, maintained in University Livestock Farm and Fodder Research Development Scheme, Mannuthy, KVASU. December to February with minimum THI was taken as season 1 and March to May with maximum THI as season 2 of the study. Microclimatic data in the animal shed was recorded three times at three days intervals. The ambient temperature, relative humidity and THI obtained during season 2 was significantly (p<0.01) higher than season 1 in both macro and microclimatic data. Partial pressure of carbon dioxide (pCO2 ) was low in season 2 but there was no significant difference in potassium (K+), sodium (Na+), bicarbonate (HCO3 - ) and partial pressure of oxygen (pO2 ) between the seasons. Keywords: Heat stress in cattle, THI, blood gases, electrolytes, late gestation

Predictive models for heat stress assessment in Holstein dairy heifers using infrared thermography and machine learning.

Heat stress is a condition that impairs the animal's productive and reproductive performance, and can be monitored by physiological and environmental variables, including body surface temperature, through infrared thermography. The objective of this work is to develop computational models for classification of heat stress from respiratory rate variable in dairy cattle using infrared thermography. The database used for the construction of the models was obtained from 10 weaned heifers, housed in a climate chamber with temperature control, and submitted to thermal comfort and heat wave treatments. Physiological and environmental data were collected, as well as thermographic images. The machine learning modeling environment used was IBM Watson, IBM's cognitive computing services platform, which has several data processing and mining tools. Classifier models for heat stress were evaluated using the confusion matrix metrics and compared to the traditional method based on Temperature and Humidity Index. The best accuracy obtained for classification of the heat stress level was 86.8%, which is comparable to previous works. The authors conclude that it was possible to develop accurate and practical models for real-time monitoring of dairy cattle heat stress.

Mask R-CNN and Centroid Tracking Algorithm to Process UAV Based Thermal-RGB Video for Drylot Cattle Heat Stress Monitoring

This study developed and evaluated an algorithm for processing thermal-RGB video feeds captured by an unmanned aerial vehicle (UAV) to automate heat stress monitoring in cattle housed in the drylots. The body surface temperature (BST) of individual cows was used as an indicator of heat stress. UAV data were collected using RGB and thermal infrared imagers, respectively, at 2 and 6.67 cm per pixel spatial resolution in Spring 2023 (dataset-1) and Summer 2024 (dataset-2). Study sites were two commercial drylots in Washington State. The custom algorithms were developed to: (1) detect and localize individual cows using a Mask R-CNN-based instance segmentation model combined with centroid tracking; and (2) extract BST by averaging the thermal-imagery pixels for each of the segmented cows. The algorithm showed higher detection accuracy with RGB images as input (F1 score: 0.89) compared to thermal (F1 score: 0.64). BST extraction with combined RGB and thermal imaging approach required corrections for alignment problems associated with differences in optics, imaging field of view, resolution, and lens properties. Consequently, thermal imaging-only approach was adopted for assessing real-time cow localization and BST estimation. Operating at one frame per second, algorithm successfully detected 72.4% and 81.65% of total cows in video frames from dataset-1 (38 s) and -2 (48 s), respectively. The mean absolute difference between algorithm output and ground truth (BSTGT) was 2.1 °C (dataset-1) and 3.3 °C (dataset-2), demonstrating satisfactory performance. With further refinements, this approach could be a viable tool for real-time heat stress monitoring in large-scale drylot production systems.

Effect of heat stress on follicular dynamics, developmental competence of oocyte and strategies to combat heat stress in cattle: A review

Effect of heat stress on follicular dynamics, developmental competence of oocyte and strategies to combat heat stress in cattle: A review

142 Programming effects of early-life exposure to heat stress in cattle

142 Programming effects of early-life exposure to heat stress in cattle

Digitalisation opportunities for livestock welfare monitoring with a focus on heat stress

Rising global temperatures due to climate change pose an increased risk of heat stress (HS) in livestock, which requires accurate prediction methods to improve animal welfare and mitigate heat-related economic losses. In this literature review, we aimed to critically examine the potential of digitalisation in precision livestock farming from the perspective of assessing heat stress in cattle. Particular attention was paid to the possibility of using sensors to record changes in behaviour, physiological parameters, and feed and water consumption as predictors for detecting and preventing heat stress and its consequences in animals. The use of already proven sensors, such as those that record animal behaviour, to assess physiological parameters related to heat stress may be promising, using innovative data processing technologies, which requires additional investigation in future studies. Precision livestock farming (PLF) technologies that enable real-time monitoring of herds under specific conditions, such as disease or stress, play a key role in increasing the efficiency of herd management. Sensors, cameras, microphones, GPS, accelerometers and RFID tags are commonly used to collect data on animal behaviour and physiological parameters, helping to detect stress. Machine learning algorithms applied to sensor data can distinguish between different states of declining cow welfare, helping farmers make quick decisions. In summary, the integration of sensors, artificial intelligence and precision devices can help prevent heat stress in farm animals, improving animal welfare and productivity, while mitigating the negative effects of heat stress caused by climate change.

Tree contributions to climate change adaptation through reduced cattle heat stress and benefits to milk and beef production.

Cattle heat stress causes billions of dollars' worth of losses to meat and milk production globally, and is projected to become more severe in the future due to climate change. Tree establishment in pastoral livestock systems holds potential to reduce cattle heat stress and thus provide nature-based adaptation. We developed a general model for the impact of trees on cattle heat stress, which can project milk and meat production under future climate scenarios at varying spatial scales. The model incorporates the key microclimate mechanisms influenced by trees, including shade, air temperature, humidity, and wind speed. We conducted sensitivity analyses to demonstrate the relative influence of different mechanisms through which trees can impact cattle heat stress, and how tree impacts are influenced by climatic context globally. Trees hold the greatest potential to reduce cattle heat stress in higher latitudes and altitudes, with minor benefits in the lowland tropics. We projected the future contributions of current trees in mitigating climate change impacts on the dairy and beef herds of Aotearoa-New Zealand (A-NZ) in 2070-2080. Trees were simulated to contribute to A-NZ milk yields by over 491 million liters (lower CI = 112 million liters, upper CI = 850 million liters), and meat yields by over 8316 tonnes (lower CI = 2431 tonnes, upper CI = 13,668 tonnes) annually. The total economic contribution of existing trees in mitigating future cattle heat stress was valued at $US 244 million (lower CI = $US 58 million, upper CI = $US 419 million). Our findings demonstrate the importance of existing trees in pastoral landscapes and suggest that strategic tree establishment can be a valuable adaptation option for reducing cattle heat stress under climate change. Tree establishment in the next few years is critical to provide adaptation capacity and economic benefit in future decades.

Observed Climatology and Variability of Cattle Heat Stress in Australia

Abstract Exposure to weather extremes, such as heatwaves, can cause discomfort, harm, or death in grazing cattle in pastures. While the Australian Bureau of Meteorology issues sheep graziers alerts when there is an exposure risk to chill for livestock, there is no equivalent alert for heat stress for Australian cattle. Before any such alert system can be developed, a robust assessment and comparison of relevant cattle thermal stress indices is required. This study evaluates and compares the multiyear climatology of three cattle thermal heat stress indices across Australia in the warm season months (October–March). The same indices are then used to assess historical Australian heat events where cattle died from heat exposure. These events are based off official records and survey responses from northern Australian graziers. In the seven historical heat events studied, high relative humidity combined with low wind speeds, or high solar exposure combined with high surface temperatures, exacerbated the impact of heat stress on cattle. In the two historic events where multiple compounding weather factors combined (e.g., high humidity, low winds, and high solar exposure), the cattle mortality levels were significantly high. These events were characterized by rainy conditions followed by a rapid warming, meaning cattle were likely unable to acclimatize to such dramatic temperature changes. This study highlights the need for using more than one thermal stress index when verifying cattle heat stress events and, importantly, calls for further research on standardizing the risk classifications of these thermal indices for cattle in Australia’s variable climate. Significance Statement Cattle across Australia’s northern tropical and semiarid regions often experience extreme hot and humid conditions in the summer months, which increases the risk of heat stress. This is the first study of its kind to evaluate observations of cattle heat stress across Australia using indices that describe the combined effects of solar exposure, wind speed, relative humidity, and surface temperatures. These cattle heat stress indices can be used to evaluate historical cattle mortality events in feedlots and in grazed pastures. This study lays the groundwork for the development of Australian-wide cattle heat stress forecast products on the 7-day to multiweek time scales.

Heat-Stress Impacts on Developing Bovine Oocytes: Unraveling Epigenetic Changes, Oxidative Stress, and Developmental Resilience.

Extreme temperature during summer may lead to heat stress in cattle and compromise their productivity. It also poses detrimental impacts on the developmental capacity of bovine budding oocytes, which halt their fertility. To mitigate the adverse effects of heat stress, it is necessary to investigate the mechanisms through which it affects the developmental capacity of oocytes. The primary goal of this study was to investigate the impact of heat stress on the epigenetic modifications in bovine oocytes and embryos, as well as on oocyte developmental capacity, reactive oxygen species, mitochondrial membrane potential, apoptosis, transzonal projections, and gene expression levels. Our results showed that heat stress significantly reduced the expression levels of the epigenetic modifications from histone H1, histone H2A, histone H2B, histone H4, DNA methylation, and DNA hydroxymethylation at all stages of the oocyte and embryo. Similarly, heat stress significantly reduced cleavage rate, blastocyst rate, oocyte mitochondrial-membrane potential level, adenosine-triphosphate (ATP) level, mitochondrial DNA copy number, and transzonal projection level. It was also found that heat stress affected mitochondrial distribution in oocytes and significantly increased reactive oxygen species, apoptosis levels and mitochondrial autophagy levels. Our findings suggest that heat stress significantly impacts the expression levels of genes related to oocyte developmental ability, the cytoskeleton, mitochondrial function, and epigenetic modification, lowering their competence during the summer season.

66 Emerging Precision Ranching Technology Is Enabling the Development of a “smart” Biome

Abstract Precision ranching technology is revolutionizing remote data collection from livestock and the land base they depend on, greatly improving our ability to assess the entire biome. Remotely Piloted Aircraft System (RPAS or drone) based remote sensing to date has been used primarily to assess intensive cropping; but RPAS systems equipped with interchangeable cameras: high-resolution visual, thermal, LiDAR, and multi/hyperspectral imagers are now being deployed on rangelands, to monitor subtle changes in the visible, near infrared and infrared spectrums (radiation) that both plants and animals reflect. A single RPAS system can now be used simultaneously for high-quality vegetation mapping and behavioral analysis of animals, providing a suite of comprehensive data-collection tools for studying livestock in a variety of landscapes and rugged terrain. For example, we have used RPAS systems to measure behavioral and physiological indicators of cattle heat stress in feedlots and on pasture (Mufford et al., 2021). These same drones can be utilized for RPAS collection of high-resolution imagery (using multi/hyperspectral imagers and LiDAR) for vegetative and topographical mapping, greatly improving our ability to visualize and characterize habitat attributes such as forage availability, quality (stage of growth) and accessibility. Equipping cattle with new tracking technology, including "smart" GPS ear tags, rumen boluses, and wireless fencing collars (based on low-earth orbit satellites and cellular networks) enable animals to be readily identified and tracked on the landscape, while providing invaluable physiological data, such as internal body temperature to monitor estrous, heat stress, or the onset of disease (Figure 1). Additionally, rapid advances in wireless fencing systems have the potential to improve livestock management through autonomous mustering or the implementation of advanced rotational grazing for use in regenerative agriculture efforts. Wireless fencing may decrease production (infrastructure) costs, while also providing a strategy to better align forage demands with use, and thereby enhance pasture condition at the habitat and landscape level. Finally, non-invasive pasture weighing systems, enabled with or without RPAS technologies, are capable of monitoring key livestock production metrics year-round. Together, these technological advances enabled by this new "smart biome" will improve animal health and welfare while ultimately enhancing the sustainability of extensive livestock production systems.

Temperate silvopastures provide greater ecosystem services than conventional pasture systems

Management and design affect systems’ ability to deliver ecosystem services and meet sustainable intensification needs for a growing population. Soil–plant–animal health evaluations at the systems level for conventional and silvopastoral environments are lacking and challenge adoption across temperate regions. Impacts of silvopasture on soil quality, microclimate, cattle heat stress, forage quality and yield, and cattle weight gain were compared to a conventional pasture in the mid-southern US. Here, we illustrate silvopastures have greater soil organic carbon, water content, and overall quality, with lower temperatures (soil and cattle) than conventional pastures. Forage production and cattle weight gains were similar across systems; yet, conventional pasture systems would need approximately four times more land area to yield equivalent net productivity (tree, nuts, forage, and animal weight) of one ha of silvopasture. Temperate silvopastures enhanced delivery of ecosystem services by improving soil quality and promoting animal welfare without productivity losses, thus allowing sustainable production under a changing climate.

A deep learning model to forecast cattle heat stress

The accurate forecasting of feedlot cattle heat stress is pivotal to improving animal welfare and reducing the economic losses associated with heat events. This study investigated how autonomously recorded cattle behaviour datasets can be leveraged to propose new approaches to cattle heat stress forecasting. Behaviour data acquired by accelerometer sensors in two experiments using mixed breed feedlot cattle were utilised, with duration of heavy breathing used to quantify heat stress. Two time-forecasting methods were proposed for predicting the average panting duration of a herd of cattle 24-hours into the future using meteorological data, animal characteristics and treatment factors as input. The first method utilised a simple deep learning framework based on Long-Short Term Memory networks, while the second applied traditional statistical methods to HLI, AHL and animal characteristic data. An optimisation algorithm was used to select which meteorological factors and how much historic data should be considered by the deep learning model. The experiments conducted emphasise that the deep learning approach was able to effectively model the lagged effect of weather on cattle heat stress. Consequently, it was found to be more accurate than traditional statistical methods and climate indices at forecasting the cattle heat response recorded in this study. A final experiment investigated the potential for using these time forecasting models to provide decision support to producers. This preliminary study thus emphasises that autonomously derived behaviour datasets and deep learning have the potential to improve animal welfare and productivity.

Heat stress of cattle from embryonic phase until culling

Heat stress becomes a serious problem in the livestock sector as it affects cows' performance negatively. The objective of this paper review is to investigate the effects of heat stress during the different phases of the life cycle of cows; embryos, calves, heifers, and cows. Heat stress during early maternal gestation affects the ability of embryos to develop increasing the risk of abortion and early embryonic death. Heat stress during late maternal gestation affects the performance of calves and heifers later in their life, as it reduces growth performance, conducts physiological changes, impaired immunity, changes the behavior, and reduces the length and intensity of the estrus in heifers with decreasing in milk production in the first lactation. On the level of cows, milk quality and production, meat quality, and the final body weight decrease under hot temperatures. Heat stress decreases the conception rate, alters follicle growth, and estrous symptoms. Hormones secretion and physiological changes because of the heat stress conduct to impair the immunity system, and in oxidative stress and death in some cases. Same as for calves and heifers a change in the behavior of cows was detected in order to decrease their temperature.

A review of dairy cattle heat stress mitigation in Indonesia.

Indonesia is a tropical country with a hot climate. In tropical nations such as Indonesia, heat stress is a key reason for the reduced productivity of dairy cattle. Heat stress is a combination of internal and external stimuli that affects an animal, raises its body temperature, and causes it to react physiologically. Most Indonesian dairy cattle are Friesian Holstein (FH), imported from European nations with a temperate environment with low temperatures in the range of 5°C-25°C. Indonesia has a tropical climate with a high ambient temperature that can reach 34°C during the day and the local relative humidity varies between 70% and 90%. Temperature and humidity are two microenvironment factors that may impact the production and heat release in FH cattle. More than 98% of the entire dairy cattle population in Indonesia is found on Java Island. On Java Island, there are between 534.22 and 543.55 thousand heads of cattle, while the dairy cattle population outside Java Island is just 6.59 thousand heads of cattle. The milk output climbs by an average of 3.34% per year, or approximately 909.64 thousand tons and the average annual growth in whole milk consumption was 0.19 L/capita. Indonesian cow milk output has been unable to keep pace with the country's increasing demand. This study aimed to review the strategies to mitigate heat stress in FH dairy cattle in Indonesia.

Heat tolerance in Mashona beef cows in semi-arid rangelands: does conformation matter?

High temperatures and frequent heat waves raise concerns about heat stress in cattle in grass-based systems, especially in arid and semiarid areas. This study analysed the relationship between conformation traits and physiological parameters associated with heat stress in Mashona cattle. A total of 200 records from fifty cows were used to study the relationships between seven conformation traits and physiological parameters associated with heat stress. Body conformation traits were categorised into three principal components related to body capacity (body depth, flank circumference, chest girth), frame size (stature and body length), and loose skin fold (navel height and dewlap size). As the size of abdominopelvic and thoracic cavities increased, respiratory rate, heart rate, and rectal temperature decreased significantly, while blood triiodothyronine concentration increased. Cattle with deeper bodies, larger flanks, and larger chest girths had significantly lower heart rate, respiratory rate, and rectal temperature but higher blood triiodothyronine concentration than cattle with shallower bodies, smaller flanks, and smaller chest girths. Respiratory rate increased with increasing frame size. Large-framed cattle had significantly higher respiratory rate and lower blood thyroxine concentration. Small-framed cattle with larger chest girth, larger dewlap, and navel farther from the ground surface are better adapted to higher ambient temperatures.

Effect of Deep Bedded Pack System in Manure Management for Reducing Heat Stress of Cattle in Bangladesh

Background: Heat stress has a considerable effect both on animal welfare and production. Animals in heat stressreduceproductivity and reproductive performances and in extreme cases, it causes death. Methods: The experiment was carried out in Satkhira, a South-Western part of Bangladesh from July 2019 to June 2020 for12 monthsperiod to investigate the year-round heat stress experienced by cattle raised in a Deep Bedded Pack System (DBP) compared to that raised on a concrete floor (CF) system in an open barn. A total of six dry cows (2.5 to 3 yearsold, Holstein-Friesian crossbred) were allotted into two groups with three replications. The deep bedded pack was prepared with rice husk. The heat stress was calculated by following an equation using temperature and humidity data. Result: Animals raised on a concrete floor were suffered moderate to severe heat stress for eight months in a year from March to October. Otherwise, animals on the DBP floor were suffered from moderate heat stress only for five months, from June to October in a year. No severe case was found on the DBP floor but severe heat stress was shown by animals on the concrete floor from July to September. Therefore, animals feel more comfortable in the DBP management system.

Heat Stress in Cattle

The breeding and production of cattle have been part of the history of the human being through the centuries, taking place with a diversity of breeds in different regions worldwide, from the coldest climates in Canada, to the warmest climates in the African continent. For that reason, cows, bulls, steers, heifers and calves have had to adapt their bodies to survive in different climates and systems used for breeding. Cattle are exposed to heat, cold, rainy and windy conditions which may cause discomfort and stress in cattle.Of all these weather events, heat remains underestimated, despite affecting most livestock in the world. Heat stress can, directly or indirectly, cause reduced performance, morbidity and even mortality producing significant economic losses and animal welfare concerns.© The Authors 2023

Heat shock protein 90 alpha family class B member 1 (HSP90AB1) gene polymorphism and its effect on milk production traits in friesian holstein cattle

Increasing temperature caused by climate change is main contributor of heat stress in dairy cattle. Heat stress has a major impact on the milk production efficiency in dairy cattle. The HSP90AB1 gene is involved in overcoming heat stress response in cattle. The purpose of this study is to find single-nucleotide polymorphism (SNP) of HSP90AB1 gene and its relationship to milk production traits in Friesian Holstein (FH) cattle. In this study, 50 FH blood samples were used. Allele Specific Polymerase Chain Reaction (AS-PCR) method was used to successfully identify three genotypes: CC, CT, and TT. The CT genotype is the most common in the sample population. When compared to the C-allele, the T-allele is more common. Hardy-Weinberg (HW) analysis using Chi-Square method revealed that the population was not equilibrium (P<0.05). Association study between genotypes and milk production trait was not significant (P>0.05), but the CC genotype had a trend of higher mean milk yield in the first and second lactation. It was determined that the HSP90AB1 gene could be used as molecular marker for FH cattle heat stress response, in order to increase milk production capacity.

Host transcriptome and microbiome interactions in Holstein cattle under heat stress condition.

Climate change affects animal physiology. In particular, rising ambient temperatures reduce animal vitality due to heat stress and this can be observed at various levels which included genome, transcriptome, and microbiome. In a previous study, microbiota highly associated with changes in cattle physiology, which included rectal temperature, drooling score and respiratory score, were identified under heat stress conditions. In the present study, genes differentially expressed between individuals were selected representing different additive genetic effects toward the heat stress response in cattle in their production condition. Moreover, a correlation network analysis was performed to identify interactions between the transcriptome and microbiome for 71 Chinese Holstein cows sequenced for mRNA from blood samples and for 16S rRNA genes from fecal samples. Bioinformatics analysis was performed comprising: i) clustering and classification of 16S rRNA sequence reads, ii) mapping cows' transcripts to the reference genome and their expression quantification, and iii) statistical analysis of both data types-including differential gene expression analysis and gene set enrichment analysis. A weighted co-expression network analysis was carried out to assess changes in the association between gene expression and microbiota abundance as well as to find hub genes/microbiota responsible for the regulation of gene expression under heat stress. Results showed 1,851 differentially expressed genes were found that were shared by three heat stress phenotypes. These genes were predominantly associated with the cytokine-cytokine receptor interaction pathway. The interaction analysis revealed three modules of genes and microbiota associated with rectal temperature with which two hubs of those modules were bacterial species, demonstrating the importance of the microbiome in the regulation of gene expression during heat stress. Genes and microbiota from the significant modules can be used as biomarkers of heat stress in cattle.