Automated collection of heat stress data in livestock: new technologies and opportunities

A review of on-farm recording tools for smallholder dairy farming in developing countries

The dairy industry has been expanding significantly recently, which has prompted the improvement and adoption of increasingly digital dairy recording tools with cutting-edge technology. The study aimed to identify smallholder dairy farmers' recording tools in developing countries. The study presents the results of an extensive literature review conducted using electronic journal databases. The review involved applying a combination of search terms and Boolean operators. The search found a total of 412 research publications. However, only 21 articles with 24 recording tools were deemed appropriate and were subsequently included in the study. Dairy recording entails gathering and managing data on animal information, traceability, health, and productivity that can be conducted using various methods, from manual record-keeping to digitization. The results show that most studies have endeavoured to develop digital recording tools that focus on production performance (PR), mainly milk production, using the Internet of Things (IoT) and mobile phone applications. Moreover, various technologies, such as networks, desktops, and web apps, have also been invented. Given the widespread ownership of mobile phones among the general population, the use of mobile phones continues to be an appealing choice for recording tools. To enhance the advancement of these tools, it is necessary to address technological obstacles, particularly those associated with access and connectivity. In addition, it is also important to consider the continuity of data input and feedback obtained to the farmers, thus helping them evaluate their farms periodically.

Evaluation of Non-Contact Device to Measure Body Temperature in Sheep

Non-contact devices have been used in the measurement of body temperature in livestock production as a tool for testing disease in different species. However, there are few studies about the variation and correlations in body temperature between rectal temperature (RT) and non-contact devices such as non-contact infrared thermometers (NCIT) and thermal imaging/infrared thermography (IRT). The objective of this work was to evaluate the accuracy of non-contact devices to measure the body temperature in sheep, considering six body regions and the possibility of implementing these systems in herd management. The experiment was carried out at the experimental farm of the Catholic University of Valencia, located in the municipality of Massanassa in July of 2021, with 72 dry manchega ewes, and we compared the rectal temperature with two types of non-contact infrared devices for the assessment of body temperature in healthy sheep. Except for the temperature taken by NCIT at the muzzle, the correlation between RT vs. NCIT or IRT showed a low significance or was difficult to use for practical flock management purposes. In addition, the variability between devices was high, which implies that measurements should be interpreted with caution in warm climates and open pens, such as most sheep farms in the Spanish Mediterranean area. The use of infrared cameras devices to assess body temperature may have a promising future, but in order to be widely applied as a routine management method on farms, the system needs to become cheaper, simpler in terms of measurements and quicker in terms of analyzing results.

Digital infrared thermal imaging of udder skin surface temperature: a novel non-invasive technology to monitor calving process in Murrah buffalo (Bubalus bubalis)

Quantifiable decline in the maternal body temperature during the pre-calving offers the possibilities for predicting the calving that can improve the calving management. As infrared thermography (IRT) is a simple non-contact tool for precise measurement of surface temperature, we investigated the use of IRT to establish thermal signatures around calving in the Murrah buffalo. The IRT of eye, right lateral, left lateral and rear side of udder skin surface temperature (USST) were recorded at 6 h interval from 96 h before the expected date of calving, at the time of calving and 24 h post-calving in Murrah buffaloes (n = 28). In parallel, blood samples were collected for progesterone (P4) assay. The results revealed that the IRT of the eye, right and left lateral and rear side of USST showed a significant decrease in the temperature from 48 h pre-calving till the onset of calving with a ΔT (°C) of 0.56, 0.91, 0.70, and 0.90, respectively. Mean USST significantly declined from 48 h pre-calving with a ΔT of 0.85 °C. The residual temperature of both eye and various ROI of the udder also followed a similar and significant declining trend from 48 to 0 h of calving indicating that circadian influence on the USST was minimum. Plasma P4 concentration significantly decreased from 72 h pre-calving till calving. It is concluded that a marked reduction in the IRT of the USST at 6-12 h pre-calving would be useful in predicting the onset of calving in the Murrah buffalo.

Impact of Heat Stress on Blood, Production, and Physiological Indicators in Heat-Tolerant and Heat-Sensitive Dairy Cows

Heat stress affects production and health in cows severely. Since it is difficult to define heat-tolerant animals, studies of response to heat stress are important for understanding dairy cows' health and production. However, information on the impact of heat stress on various indicators in heat-tolerant and heat-sensitive cows is sparse. This study aimed to investigate the effects of heat stress (HS) on blood, production, and physiological indicators in heat-tolerant and heat-sensitive cows. A total of 43 dairy cows were used from 9 May to 7 August 2021, under Temperature-Humidity Index (THI) measurements that ranged from 65.9 to 86.7. We identified cows that were tolerant or sensitive to HS based on the slope of the response of physiological and production traits against THI during the HS period by using a clustering method. After HS, serum glucose (Glu), cortisol (COR), 5-hydroxytryptamine (5-HT), and interleukin-6 (IL-6) levels of cows in the heat-tolerant group were lower than in the heat-sensitive group (p < 0.05). With THI as the predictor, the R2 for predicting respiration rate (RR) and body surface temperature (BT) in heat-tolerant cows was 0.15 and 0.16, respectively, whereas the R2 for predicting RR and BT in heat-sensitive cows was 0.19 and 0.18, respectively. There were low to moderate, positive correlations between RR, BT, and MY with THI, with Pearson correlation coefficients ranging from r = 0.11 to 0.4 in the heat-tolerant group, and from r = 0.24 to 0.43 in the heat-sensitive group. There was a low positive correlation between VT and THI, with a Spearman correlation coefficient of r = 0.07 in the heat-sensitive group. The heat-tolerant dairy cows had lower MY losses and had lower MY (p = 0.0007) in mixed models. Heat-tolerant cows with low-stress levels, through upregulating RR rapidly, increased their adaptability to thermal environments. They have better thermoregulation capability; the hypothalamic-pituitary-adrenal (HPA) axis regulated the thermoregulatory in animals by releasing a variety of neurotransmitters and hormones.

Effect of live yeast supplementation on energy partitioning and ruminal fermentation characteristics of steers fed a grower-type diet in heat-stress conditions

The objective of this trial was to determine the influence of live yeast supplementation (LY), environmental condition (ENV), and their interaction (TRT) on energy partitioning, nitrogen metabolism, and ruminal fermentation dynamics of steers receiving a grower-type diet. The effects of LY and ENV were investigated using a 2 × 2 crossover design that spanned five periods. Eight Angus-crossbred steers were randomly split into pairs and housed in four outdoor pens outfitted with an individualized feeding system. Animals were limit-fed a grower diet (DIET) at 1.2% shrunk body weight (SBW) with no live yeast supplementation (NOY) or a grower diet top-dressed with 10 g LY/d for 14 d (1.2 × 1012 CFU/d). On days 13 and 14, animals were subjected to one of two ENV conditions, thermoneutral (TN; 18.4 ± 1.1 °C, 57.6 ± 2.8% relative humidity [RH]) or heat stress (HS; 33.8 ± 0.6 °C, 55.7 ± 2.7% RH), in two side-by-side, single-stall open-circuit, indirect respiration calorimetry chambers. Data were analyzed using a random coefficients model. Carryover effects were examined and removed from the model if not significant. Gross (GE), digestible, metabolizable, heat, and retained energies were not influenced by DIET, ENV, or TRT (P ≥ 0.202). Gaseous energy, as a percentage of GE, tended to increase during HS (P = 0.097). The only carryover effect in the study was for oxygen consumption (P = 0.031), which could be attributed to the tendency of NOY (P = 0.068) to have greater oxygen consumption. DIET, ENV, or TRT (P ≥ 0.154) had no effects on total animal methane or carbon dioxide emissions. Similarly, DIET, ENV, or TRT (P ≥ 0.157) did not affect ruminal pH, redox, protozoa enumeration, ruminal ammonia concentrations, and acetate-to-propionate ratio. Propionate concentrations were the greatest in animals in TN conditions receiving LY (P = 0.034) compared to the other TRT. This effect is mirrored by TN-LY tending to have greater acetate concentrations (P = 0.076) and total VFA concentrations (P = 0.065). Butyrate concentrations tended to be greater for animals fed LY (P = 0.09). There was a tendency for LY to have elevated numbers of Fusobacterium necrophorum (P = 0.053). Although this study lacked effects of LY on energy partitioning, nitrogen metabolism, and some ruminal parameters during HS, further research should be completed to understand if LY is a plausible mitigation technique to enhance beef animals' performance in tropical and sub-tropical regions of the world.

Predictive Models of Dairy Cow Thermal State: A Review from a Technological Perspective

Simple Summary

Heat stress in cattle is broadly defined as a physiological condition in which body temperature rises, and the animals are no longer able to adequately dissipate body heat to maintain thermal equilibrium due to environmental factors. Dairy cattle are particularly sensitive to heat stress because of the higher metabolic rate needed for milk production. Due to global warming and the expected growth of milk production in warmer regions, an increase in the occurrence of heat stress can only be avoided with the use of environmental control systems. However, most available systems were developed to take corrective measures or are not accurate enough to effectively prevent heat stress, as there is not yet an automated technological solution that considers all the environmental and animal variables that determine the occurrence of this condition. Further, these systems must be connected in time to prevent this condition in cattle but also disconnected when they are no longer needed, as their use raises major economic and environmental concerns regarding energy and water consumption. This review describes and discusses three types of predictive models that can make these systems more effective in preventing heat stress and more efficient in the use of energy and water.

Abstract

Dairy cattle are particularly sensitive to heat stress due to the higher metabolic rate needed for milk production. In recent decades, global warming and the increase in dairy production in warmer countries have stimulated the development of a wide range of environmental control systems for dairy farms. Despite their proven effectiveness, the associated energy and water consumption can compromise the viability of dairy farms in many regions, due to the cost and scarcity of these resources. To make these systems more efficient, they should be activated in time to prevent thermal stress and switched off when that risk no longer exists, which must consider environmental variables as well as the variables of the animals themselves. Nowadays, there is a wide range of sensors and equipment that support farm routine procedures, and it is possible to measure several variables that, with the aid of algorithms based on predictive models, would allow anticipating animals’ thermal states. This review summarizes three types of approaches as predictive models: bioclimatic indexes, machine learning, and mechanistic models. It also focuses on the application of the current knowledge as algorithms to be used in the management of diverse types of environmental control systems.

Improving Genomic Selection for Heat Tolerance in Dairy Cattle: Current Opportunities and Future Directions

Heat tolerance is the ability of an animal to maintain production and reproduction levels under hot and humid conditions and is now a trait of economic relevance in dairy systems worldwide because of an escalating warming climate. The Australian dairy population is one of the excellent study models for enhancing our understanding of the biology of heat tolerance because they are predominantly kept outdoors on pastures where they experience direct effects of weather elements (e.g., solar radiation). In this article, we focus on evidence from recent studies in Australia that leveraged large a dataset [∼40,000 animals with phenotypes and 15 million whole-genome sequence variants] to elucidate the genetic basis of thermal stress as a critical part of the strategy to breed cattle adapted to warmer environments. Genotype-by-environment interaction (i.e., G × E) due to temperature and humidity variation is increasing, meaning animals are becoming less adapted (i.e., more sensitive) to changing environments. There are opportunities to reverse this trend and accelerate adaptation to warming climate by 1) selecting robust or heat-resilient animals and 2) including resilience indicators in breeding goals. Candidate causal variants related to the nervous system and metabolic functions are relevant for heat tolerance and, therefore, key for improving this trait. This could include adding these variants in the custom SNP panels used for routine genomic evaluations or as the basis to design specific agonist or antagonist compounds for lowering core body temperature under heat stress conditions. Indeed, it was encouraging to see that adding prioritized functionally relevant variants into the 50k SNP panel (i.e., the industry panel used for genomic evaluation in Australia) increased the prediction accuracy of heat tolerance by up to 10% units. This gain in accuracy is critical because genetic improvement has a linear relationship with prediction accuracy. Overall, while this article used data mainly from Australia, this could benefit other countries that aim to develop breeding values for heat tolerance, considering that the warming climate is becoming a topical issue worldwide.

Novel insights into heat tolerance using metabolomic and high-throughput sequencing analysis in dairy cows rumen fluid

Heat stress influences rumen fermentative processes with effects on the physiology and production of dairy cows. However, the underlying relationship between rumen microbiota and its associated metabolism with heat tolerance in cows have not been extensively described yet. Therefore, the main objective of this study was to investigate differential heat resistance in Holstein cows using rumen bacterial and metabolome analyses. We performed both principal component analysis and membership function analysis to select seven heat-tolerant (HT) and seven heat-sensitive (HS) cows. Under heat stress conditions, the HT cows had a significantly (P < 0.05) higher propionic acid content than the HS cows; while measures of the respiratory rate, acetic, and butyric acid in the HT cows were significantly (P < 0.05) lower compared with the HS cows. Also, the HT cows showed lower (P < 0.01) rectal temperature and acetic acid to propionic acid ratio than the HS group of cows. Omics sequencing revealed that the relative abundances of Muribaculaceae, Rikenellaceae, Acidaminococcaceae, Christensenellaceae, Rikenellaceae_RC9_gut_group, Succiniclasticum, Ruminococcaceae_NK4A214_group and Christensenellaceae_R-7_group were significantly (P < 0.01) higher in the HT cows; whereas Prevotellaceae, Prevotella_1, Ruminococcaceae_UCG-014, and Shuttleworthia were significantly (P < 0.01) lower in HT cows compared to HS cows. Substances mainly involved in carbohydrate metabolism, including glycerol, mannitol, and maltose, showed significantly higher content in the HT cows (P < 0.05) compared to that in the HS cows. Simultaneously, distinct metabolites were significantly correlated with differential bacteria, suggesting that glycerol, mannitol, and maltose could serve as potential biomarkers for determining heat resistance that require further study. Overall, distinct changes in the rumen microbiota and metabolomics in the HT cows may be associated with a better adaptability to heat stress. These findings suggest their use as diagnostic tools of heat tolerance in dairy cattle breeding schemes.

Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle

Simple Summary

Sensors, routinely collected on-farm tests, and other repeatable, high-throughput measurements can provide novel phenotype information on a frequent basis. Information from these sensors and high-throughput measurements could be harnessed to monitor or predict individual dairy cow feed intake. Predictive algorithms would allow for genetic selection of animals that consume less feed while producing the same amount of milk. Improved monitoring of feed intake could reduce the cost of milk production, improve animal health, and reduce the environmental impact of the dairy industry. Moreover, data from these information sources could aid in animal management (e.g., precision feeding and health detection). In order to implement tools, the relationship of measurements with feed intake needs to be established and prediction equations developed. Lastly, consideration should be given to the frequency of data collection, the need for standardization of data and other potential limitations of tools in the prediction of feed intake. This review summarizes measurements of feed efficiency, factors that may impact the efficiency and feed consumption of an animal, tools that have been researched and new traits that could be utilized for the prediction of feed intake and efficiency, and prediction equations for feed intake and efficiency presented in the literature to date.

Abstract

Feed for dairy cattle has a major impact on profitability and the environmental impact of farms. Sustainable dairy production relies on continued improvement in feed efficiency as a way to reduce costs and nutrient loss from feed. Advances in breeding, feeding and management have led to the dilution of maintenance energy and thus more efficient dairy cattle. Still, many additional opportunities are available to improve individual animal feed efficiency. Sensing technologies such as wearable sensors, image-based and high-throughput phenotyping technologies (e.g., milk testing) are becoming more available on commercial farm. The application of these technologies as indicator traits for feed intake and efficiency related traits would be advantageous to provide additional information to predict and manage feed efficiency. This review focuses on precision livestock technologies and high-throughput phenotyping in use today as well as those that could be developed in the future as possible indicators of feed intake. Several technologies such as milk spectral data, activity, rumen measures, and image-based phenotypes have been associated with feed intake. Future applications will depend on the ability to repeatably measure and calibrate these data across locations, so that they can be integrated for use in predicting and managing feed intake and efficiency on farm.

Automated Monitoring of Cattle Heat Stress and Its Mitigation

Climate change related global warming is likely to continue, despite all mitigation measures taken by humans, due to the lag effect of long-term anthropogenic activities. Warming of the atmosphere can impact worldwide cattle production directly by compromising health, welfare and productivity, and indirectly by reducing the quality and quantity of animal feed. Under warm thermal conditions, cattle adjust their physiological and behavioural responses as an integral part of thermoregulation to maintain internal body temperature within a safe range. However, a greater intensity and duration of heat exposure can exceed thermoregulatory capacity leading to an increase in internal body temperature beyond the normal limit that ultimately evokes different animal responses to heat. In cattle, response to heat stress can be visually observed as elevated respiration rate or panting, but continuous visual monitoring is labour intensive, time consuming and subjective. Therefore, different weather-based indices have been developed such as the temperature humidity index (THI) and heat load index (HLI) which are commonly used weather-based indices for monitoring cattle heat stress at commercial level. However, the thermal comfort level of cattle based on weather-based indices has limited use at a microclimatic and individual animal level. Varying sensor-based approaches have shown promise to shift the focus of heat stress management to the individual level. Monitoring individual animal response and mitigation strategies for isolated heat-susceptible cattle could save on heat management costs whilst improving animal welfare and productivity. Here we review the technologies that enable automatic, continuous, and real-time cattle heat stress monitoring and mitigation under commercial conditions. Future platforms for autonomous monitoring and mitigation of heat stress in cattle are likely to be based on minimally-invasive smart technologies either singly, or in an integrated system, enabling real-time solutions to animal responses under various production systems and environmental conditions.

Bottlenose dolphin habitat and management factors related to activity and distance traveled in zoos and aquariums

High-resolution non-invasive cetacean tagging systems can be used to investigate the influence of habitat characteristics and management factors on behavior by quantifying activity levels and distance traveled by bottlenose dolphins (Tursiops truncatus and Tursiops aduncus) in accredited zoos and aquariums. Movement Tags (MTags), a bio-logging device, were used to record a suite of kinematic and environmental information outside of formal training sessions as part of a larger study titled "Towards understanding the welfare of cetaceans in zoos and aquariums" (colloquially called the Cetacean Welfare Study). The purpose of the present study was to explore if and how habitat characteristics, environmental enrichment programs, and training programs were related to the distance traveled and energy expenditure of dolphins in accredited zoos and aquariums. Bottlenose dolphins in accredited zoos and aquariums wore MTags one day per week for two five-week data collection periods. Overall dynamic body acceleration (ODBA), a proxy for energy expenditure, and average distance traveled per hour (ADT) of 60 dolphins in 31 habitats were examined in relation to demographic, habitat, and management factors. Participating facilities were accredited by the Alliance for Marine Mammal Parks and/or Aquariums and the Association of Zoos & Aquariums. Two factors were found to be related to ADT while six factors were associated with ODBA. The results showed that enrichment programs were strongly related to both ODBA and ADT. Scheduling predictable training session times was also positively associated with ADT. The findings suggested that habitat characteristics had a relatively weak association with ODBA and were not related to ADT. In combination, the results suggested that management practices were more strongly related to activity levels than habitat characteristics.

Using unmanned aerial vehicles to record behavioral and physiological indicators of heat stress in cattle on feedlot and pasture

Physiological and behavioral indicators of heat stress in cattle are time- and labor-intensive to measure, and difficult to observe in extensive feedlot and pasture settings. We proposed to record respiration rate and standing behavior using unmanned aerial vehicles. Videos were recorded above steers on feedlot in the morning (0830–1130) and afternoon (1400–1700) over 10 d between 25 July and 10 August and cows on pasture over 9 d between 19 and 29 August In the feedlot, video recordings on 925 individuals (264 black coated, 413 red, and 248 white) were obtained, varying in breed which included Black Angus, Hereford, Charolais, Canadian Speckle Park, and Simmental. On pasture, video recordings on 267 individuals (116 Black Angus and 151 Hereford) were obtained. Observer software was used to analyze videos. Respiration rate in feedlot cattle was the highest in black cattle, followed by red cattle, then white cattle. Coat color did not affect respiration rate in cows on pasture; temperatures on pasture were lower than in feedlots and the effect of coat color may not manifest until a certain heat load threshold. The probability that cattle would be standing increased with heat load index in feedlot and pasture settings.

A LoRa sensor network for monitoring pastured livestock location and activity

Precision technologies for confinement animal agricultural systems have increased rapidly over the past decade, though precision technology solutions for pastured livestock remain limited. There are a number of reasons for this limited expansion of technologies for pastured animals, including networking availability and reliability, power requirements, and expense, among others. The objective of this work was to demonstrate a rapidly deployable long-range radio (LoRa) based, low-cost sensor suite that can be used to track location and activity of pastured livestock. The sensor is comprised of an inexpensive Arduino-compatible microprocessor, a generic MPU-9250 motion sensor which contains a 3-axis accelerometer, 3-axis magnetometer, and a 3-axis gyroscope, a generic GPS receiver, and a RFM95W generic LoRa radio. The microprocessor can be programmed flexibly using the open source Arduino IDE software to adjust the frequency of sampling, the data packet to send, and what conditions are needed to operate. The LoRa radio transmits to a Dragino LoRa gateway which can also be flexibly programmed through the Arduino IDE software to send data to local storage or, in cases where a web or cellular connection is available, to cloud storage. The sensor was powered using a USB cord connected to a 3,350 mAh lithium-ion battery pack. The Dragino gateway was programmed to upload data to the ThingSpeak IoT application programming interface for data storage, handling, and visualization. Evaluations showed minimal benefit associated with reducing sampling frequency as a strategy to preserve battery life. Packet loss ranged from 40% to 60%. In a 3 d evaluation on pastured sheep, the sensor suite was able to report GPS locations, inertial sensor readings, and temperature. Preliminary demonstrations of our system are satisfactory to detect animal location based on GPS data in real-time. This system has clear utility as a lower-cost strategy to deploy flexible, useful precision technologies for pasture-based livestock species.

Recent Advances on Early Detection of Heat Strain in Dairy Cows Using Animal-Based Indicators: A Review

In pursuit of precision livestock farming, the real-time measurement for heat strain-related data has been more and more valued. Efforts have been made recently to use more sensitive physiological indicators with the hope to better inform decision-making in heat abatement in dairy farms. To get an insight into the early detection of heat strain in dairy cows, the present review focuses on the recent efforts developing early detection methods of heat strain in dairy cows based on body temperatures and respiratory dynamics. For every candidate animal-based indicator, state-of-the-art measurement methods and existing thresholds were summarized. Body surface temperature and respiration rate were concluded to be the best early indicators of heat strain due to their high feasibility of measurement and sensitivity to heat stress. Future studies should customize heat strain thresholds according to different internal and external factors that have an impact on the sensitivity to heat stress. Wearable devices are most promising to achieve real-time measurement in practical dairy farms. Combined with internet of things technologies, a comprehensive strategy based on both animal- and environment-based indicators is expected to increase the precision of early detection of heat strain in dairy cows.

Animal Welfare Implications of Digital Tools for Monitoring and Management of Cattle and Sheep on Pasture

Simple Summary

Monitoring the welfare of cattle and sheep in large pastures can be time-consuming, especially if the animals are scattered over large areas in semi-natural pastures. There are several technologies for monitoring animals with wearable or remote equipment for recording physiological or behavioural parameters and trigger alarms when the acquired information deviates from the normal. Automatic equipment allows continuous monitoring and may give more information than manual monitoring. Ear tags with electronic identification can detect visits to specific points. Collars with positioning (GPS) units can assess the animals’ movements and habitat selection and, to some extent, their health and welfare. Digitally determined virtual fences, instead of the traditional physical ones, have the potential to keep livestock within a predefined area using audio signals in combination with weak electric shocks, although some individuals may have difficulties in responding as intended, potentially resulting in reduced animal welfare. Remote technology such as drones equipped with cameras can be used to count animals, determine their position and study their behaviour. Drones can also herd and move animals. However, the knowledge of the potential effects on animal welfare of digital technology for monitoring and managing grazing livestock is limited, especially regarding drones and virtual fences.

Abstract

The opportunities for natural animal behaviours in pastures imply animal welfare benefits. Nevertheless, monitoring the animals can be challenging. The use of sensors, cameras, positioning equipment and unmanned aerial vehicles in large pastures has the potential to improve animal welfare surveillance. Directly or indirectly, sensors measure environmental factors together with the behaviour and physiological state of the animal, and deviations can trigger alarms for, e.g., disease, heat stress and imminent calving. Electronic positioning includes Radio Frequency Identification (RFID) for the recording of animals at fixed points. Positioning units (GPS) mounted on collars can determine animal movements over large areas, determine their habitat and, somewhat, health and welfare. In combination with other sensors, such units can give information that helps to evaluate the welfare of free-ranging animals. Drones equipped with cameras can also locate and count the animals, as well as herd them. Digitally defined virtual fences can keep animals within a predefined area without the use of physical barriers, relying on acoustic signals and weak electric shocks. Due to individual variations in learning ability, some individuals may be exposed to numerous electric shocks, which might compromise their welfare. More research and development are required, especially regarding the use of drones and virtual fences.

Genetic parameters for rectal temperature, respiration rate, and drooling score in Holstein cattle and their relationships with various fertility, production, body conformation, and health traits

Genetic selection for improved climatic resilience is paramount to increase the long-term sustainability of high-producing dairy cattle, especially in face of climate change. Various physiological indicators, such as rectal temperature (RT), respiration rate score (RR), and drooling score (DS), can be used to genetically identify animals with more effective coping mechanisms in response to heat stress events. In this study, we investigated genetic parameters for RT, RR (score from 1-3), and DS (score from 1-3). Furthermore, we assessed the genetic relationship among these indicators and other economically important traits for the dairy cattle industry. After data editing, 59,265 (RT), 30,290 (RR), and 30,421 (DS) records from 13,592 lactating Holstein cows were used for the analyses. Variance components were estimated based on a multiple-trait repeatability animal model. The heritability ± standard error estimate for RT, RR, and DS was 0.06 ± 0.01, 0.04 ± 0.01, and 0.02 ± 0.01, respectively, whereas their repeatability was 0.19, 0.14, and 0.14, respectively. Moderate genetic correlations of RR with RT and DS (0.26 ± 0.11 and 0.25 ± 0.16) and nonsignificant correlation between RT and DS (-0.11 ± 0.14) were observed. Furthermore, the approximate genetic correlations between RT, RR, and DS with 12 production, 29 conformation, 5 fertility and reproduction, 5 health, and 9 longevity-indicator traits were assessed. In general, the approximate genetic correlations calculated were low to moderate. In summary, 3 physiological indicators of heat stress response were measured in a large number of animals and shown to be lowly heritable. There is a value in developing a selection index including all the 3 indicators to improve heat tolerance in dairy cattle. All the unfavorable genetic relationships observed between heat tolerance and other economically important traits can be accounted for in a selection index to enable improved climatic resilience while also maintaining or increasing productivity in Holstein cattle.

Development of a genetic evaluation for hair shedding in American Angus cattle to improve thermotolerance

BACKGROUND

Heat stress and fescue toxicosis caused by ingesting tall fescue infected with the endophytic fungus Epichloë coenophiala represent two of the most prevalent stressors to beef cattle in the United States and cost the beef industry millions of dollars each year. The rate at which a beef cow sheds her winter coat early in the summer is an indicator of adaptation to heat and an economically relevant trait in temperate or subtropical parts of the world. Furthermore, research suggests that early-summer hair shedding may reflect tolerance to fescue toxicosis, since vasoconstriction induced by fescue toxicosis limits the ability of an animal to shed its winter coat. Both heat stress and fescue toxicosis reduce profitability partly via indirect maternal effects on calf weaning weight. Here, we developed parameters for routine genetic evaluation of hair shedding score in American Angus cattle, and identified genomic loci associated with variation in hair shedding score via genome-wide association analysis (GWAA).

RESULTS

Hair shedding score was moderately heritable (h2 = 0.34 to 0.40), with different repeatability estimates between cattle grazing versus not grazing endophyte-infected tall fescue. Our results suggest modestly negative genetic and phenotypic correlations between a dam's hair shedding score (lower score is earlier shedding) and the weaning weight of her calf, which is one metric of performance. Together, these results indicate that economic gains can be made by using hair shedding score breeding values to select for heat-tolerant cattle. GWAA identified 176 variants significant at FDR < 0.05. Functional enrichment analyses using genes that were located within 50 kb of these variants identified pathways involved in keratin formation, prolactin signalling, host-virus interaction, and other biological processes.

CONCLUSIONS

This work contributes to a continuing trend in the development of genetic evaluations for environmental adaptation. Our results will aid beef cattle producers in selecting more sustainable and climate-adapted cattle, as well as enable the development of similar routine genetic evaluations in other breeds.

Biomarkers in bivalve mollusks and amphipods for assessment of effects linked to cyanobacteria and elodea: Mesocosm study

The effects of cyanobacteria (Aphanizomenon flos-aquae (90%), Microcystis aeruginosa) and dense Elodea canadensis beds on the health endpoints of the amphipod Gmelinoides fasciatus and bivalve mollusc Unio pictorum were examined in mesocosms with simulated summer conditions (July-August 2018) in the environment of the Rybinsk Reservoir (Volga River Basin, Russia). Four treatments were conducted, including one control and three treatments with influencing factors, cyanobacteria and dense elodea beds (separately and combined). After 20 days of exposure, we evaluated the frequency of malformed and dead embryos in amphipods, heart rate (HR) and its recovery (HRR) after stress tests in molluscs as well as heat tolerance (critical thermal maximum or CTMax) in both amphipods and molluscs. The significant effect, such as elevated number of malformed embryos, was recorded after exposure with cyanobacteria (separately and combined with elodea) and presence of microcystins (MC) in water (0.17 μg/l, 40% of the most toxic MC-LR contribution). This study provided evidence that an elevated number (>5% of the total number per female) of malformed embryos in amphipods showed noticeable toxicity effects in the presence of cyanobacteria. The decreased oxygen under the influence of dense elodea beds led to a decrease in HR (and an increase in HRR) in molluscs. The notable effects on all studied biomarkers, embryo malformation frequency and heat tolerance in the amphipod G. fasciatus, as well as the heat tolerance and heart rate in the mollusc U. pictorum, were found when both factors (elodea and cyanobacteria) were combined. The applied endpoints could be further developed for environmental monitoring, but the obtained results support the importance of the combined use of several biomarkers and species, especially in the case of multi-factor environmental stress.

Methods to quantify heat stress in ruminants: Current status and future prospects

The physiology of hyperthermia or heat stress in mammals is complex. It is a totally systemic condition that in varying degrees involves all organs, tissues and body fluid compartments. The nature and magnitude of the response is influenced by animal specific characteristics (e.g. age, diet, body condition, gender, reproductive stage), environment and animal management. Given the multifaceted nature of heat stress, and the varied ruminant production systems based in varied geoclimatic zones, it has been difficult to find appropriate measures of heat stress for production ruminants. This has become an urgent challenge as production systems intensify globally in a warming climate. Bioclimatic indices such as the Temperature-Humidity Index (THI) have evolved to incorporate some measure of animal physiology. However, these indices do not have strong relationships with core temperature trajectories and altered respiratory dynamics of animals with excessive heat load. In recent decades, the careful physiology studies of the 1950-80s, have given way to numerous studies trialling a plethora of new technologies and computational approached to measure heat stress. Infrared thermography of body surface temperatures, automated measures of respiration rate and radiotelemetry of internal body temperatures are the most intensively researched. The common goal has been to find the 'holy grail' decision-making threshold or timepoint as to the animal's wellbeing. Are we making any progress?

Heat stress in dairy calves from birth to weaning

This Research Reflection collects current knowledge on the effects of heat stress in dairy calves. Chapters cover the concept of foetal programming, animal-based and environmental indicators of heat stress in the postnatal period, and methods of heat stress abatement. Conclusions for further research about economic efficiency, research methodology and an integrated approach of pre- and postnatal heat stress are also proposed.

Invited review: Physiological and behavioral effects of heat stress in dairy cows

Animal welfare can be negatively affected when dairy cattle experience heat stress. Managing heat stress has become more of a challenge than ever before, due to the increasing number of production animals with increased milk yield, and therefore greater metabolic activity. Environmental temperatures have increased by 1.0°C since the 1800s and are expected to continue to increase by another 1.5°C between 2030 and 2052. Heat stress affects production, reproduction, nutrition, health, and welfare. Means exist to monitor and evaluate heat stress in dairy cattle, as well as different ways to abate heat, all with varying levels of effectiveness. This paper is a summary and compilation of information on dairy cattle heat stress over the years.

Heat Stress Impacts on Lactating Cows Grazing Australian Summer Pastures on an Automatic Robotic Dairy

The objective of this study was to measure the impacts of summer heat events on physiological parameters (body temperature, respiratory rate and panting scores), grazing behaviour and production parameters of lactating Holstein Friesian cows managed on an Automated Robotic Dairy during Australian summer. The severity of heat stress was measured using Temperature-Humidity Index (THI) and impacts of different THIs-low (≤72), moderate (73-82) and high (≥83)-on physiological responses and production performance were measured. There was a highly significant (p ≤ 0.01) effect of THI on respiratory rate (66.7, 84.7 and 109.1/min), panting scores (1.4, 1.9 and 2.3) and average body temperature of cows (38.4, 39.4 and 41.5 °C), which increased as THI increased from low to moderate to high over the summer. Average milk production parameters were also significantly (p ≤ 0.01) affected by THI, such that daily milk production dropped by 14% from low to high THI, milk temperature and fat% increased by 3%, whilst protein% increased by 2%. The lactation stage of cow had no significant effect on physiological parameters but affected (p ≤ 0.05) average daily milk yield and milk solids. Highly significant (p ≤ 0.01) positive correlations were obtained between THI and milk temperature, fat% and protein% whilst the reverse was observed between THI and milk yield, feed intake and rumination time. Under moderate and high THI, most cows sought shade, spent more time around watering points and showed signs of distress (excessive salivation and open mouth panting). In view of the expected future increase in the frequency and severity of heat events, additional strategies including selection and breeding for thermotolerance and dietary interventions to improve resilience of cows need to be pursued.

Developing and evaluating threshold-based algorithms to detect drinking behavior in dairy cows using reticulorumen temperature

In this study, we assessed for the first time the use of a reticuloruminal temperature bolus and a thresholding method to detect drinking events and investigated different factors that can affect drinking behavior. First, we validated the detection of drinking events using 16 cows that received a reticuloruminal bolus. For this, we collected continuous drinking behavior data for 4 d using video recordings and ambient and water temperature for the same 4 d. After all the data were synchronized, we performed 2 threshold algorithms: a general-fixed threshold and a cow-day specific threshold algorithm. In the general-fixed threshold, a positive test was considered if the temperature of any cow fell below a fixed threshold; in the cow-day specific threshold, a positive test was considered when the temperature of specific cows fell below the threshold value deviations around the mean temperature of the cow for that day. The former was evaluated using a threshold varying between 35.7 and 39.5°C, and the latter using the formula μ-n10σ, where µ = mean of the temperature of each cow for one day, n = 1, 2, …, 20, and σ = standard deviation of the temperature of each cow on that day. The performance of the validation of detection using each of the threshold types was computed using different metrics, including overall accuracy, precision, recall (also known as sensitivity), F-score, positive predictive value, negative predictive value, false discovery rate, false omission rate, and Cohen's kappa statistic. The findings of the first study showed that the cow-day specific threshold of n = 10 performed better (true positives = 466; false positives = 167; false negatives = 165; true negatives = 8,416) than using a general-fixed threshold of 38.1°C (true positives = 449; false positives = 181; false negatives = 182; true negatives = 8,402). With the information gained in this first study, we investigated the different factors associated with temperature drop characteristics per cow: number of drops, mean amplitude of the drop, and mean recovery time. For this, we used data from 54 cows collected for almost 1 yr to build a mixed-effect multilevel model that included days in milk, parity, average monthly milk production, and ambient temperature as explanatory variables. Cow characteristics and ambient temperature had significant effects on drinking events. Our results provide a platform for automated monitoring of drinking behavior, which has potential value in prediction of health and welfare in dairy cattle.

Thermotolerance indicators related to production and physiological responses to heat stress of holstein cows

Heat stress (HS) adversely influences dairy cattle welfare and productivity. This study aimed to investigate the effects of HS on production and physiological parameters of Holstein cows. Two experiments each lasted 6 weeks were conducted in four Tunisian farms, firstly during summer under HS (n = 80, THI = 77) and later during autumn under thermo-neutral (n = 80, THI = 54) conditions. Respiration rate (RR), skin temperature (ST), rectal temperature (RT) and milk yield were measured, and milk samples were collected on 2 days every week during each experimental period. Temperature and relative humidity were measured inside the barn to calculate the temperature-humidity index (THI). Mixed models were used to evaluate the effects of period and the relationships between THI and physiological and production traits. Reaction norm models were applied to quantify the individual responses of cows across the trajectory of THI during the HS period. A clustering methodology was developed to identify tolerant and sensitive cows to HS based on their slope for response of physiological and production traits during HS period. In summer, RR (61 breaths/min) and ST (37.7 °C) were 2.3- and 1.3-fold higher, whereas milk yield per milking was 24% lower compared with thermo-neutral conditions. Linear relationship between THI and RR, ST and RT was observed and showed increases by 2 breaths/min, 0.5 °C and 0.04 °C per increase in one THI unit, respectively. Inversely, milk, fat and protein yields showed a drop of 0.13 kg, 0.4 g and 0.3 g per milking per increase in one THI unit, respectively. Cows qualified to be heat tolerant by our work tended to have higher RR, ST, and RT and lower to almost no decay in milk yield compared to cows qualified to be heat sensitive. Specifically, RR could be used as a reliable indicator for thermotolerance. The results of this study deepen our understanding of different aspects of HS resilience.