Remote noninvasive assessment of pain and health status in cattle

Development and validation of machine-learning models for monitoring individual behaviors in group-housed broiler chickens

Animals' individual behavior is commonly monitored by live or video observation by a person. This can be labor intensive and inconsistent. An alternative is the use of machine learning-based computer vision systems. The objectives of this study were to 1) develop and optimize machine learning model frameworks for detecting, tracking and classifying individual behaviors of group-housed broiler chickens in continuous video recordings; and 2) use an independent dataset to evaluate the performance of the developed machine leaning model framework for individual poultry behaviors differentiation. Forty-two video recordings from 4 different pens (total video duration = 1,620 min) were used to develop and train multiple models for detecting and tracking individual birds and classifying 4 behaviors: feeding, drinking, active, and inactive. The optimal model framework was used to continuously analyze an external set of 11 videos (duration = 326 min), and the second-by-second behavior of each individual broiler was extracted for the comparison of human observation. After comparison of model performance, the YOLOv5l, out of 5 detection models, was selected for detecting individual broilers in a pen; the osnet_x0_25_msmt17, out of 4 tracking algorithms, was selected to track each detected bird in continuous frames; and the Gradient Boosting Classifier, out of 12 machine learning classifiers, was selected to classify the 4 behaviors. Most of the models were able to keep previously assigned individual identifications of the chickens in limited amounts of time, but lost the identities throughout an examination period (≥4 min). The final framework was able to accurately predict feeding (accuracy = 0.895) and drinking time (accuracy = 0.9) but subpar for active (accuracy = 0.545) and inactive time (accuracy = 0.505). The algorithms employed by the machine learning models were able to accurately detect feeding and drinking behavior but still need to be improved for maintaining individual identities of the chickens and identifying active and inactive behaviors.

Comparison of physiological markers, behavior monitoring, and clinical illness scoring as indicators of an inflammatory response in beef cattle

Clinical illness (CI) scoring using visual observation is the most widely applied method of detecting respiratory disease in cattle but has limited effectiveness in practice. In contrast, body-mounted sensor technology effectively facilitates disease detection. To evaluate whether a combination of movement behavior and CI scoring is effective for disease detection, cattle were vaccinated to induce a temporary inflammatory immune response. Cattle were evaluated before and after vaccination to identify the CI variables that are most indicative of sick cattle. Respiratory rate (H2 = 43.08, P < 0.0001), nasal discharge (H2 = 8.35, P = 0.015), and ocular discharge (H2 = 16.38, P = 0.0003) increased after vaccination, and rumen fill decreased (H2 = 20.10, P < 0.0001). Locomotor activity was measured via leg-mounted sensors for the four days preceding and seven days following vaccination. A statistical model that included temperature, steps, lying time, respiratory rate, rumen fill, head position, and excess saliva was developed to distinguish between scores from before and after vaccination with a sensitivity of 0.898 and specificity of 0.915. Several clinical illness signs were difficult to measure in practice. Binoculars were required for scoring respiratory rate and eye-related metrics, and cattle had to be fitted with colored collars for individual identification. Scoring each animal took up to three minutes in a small research pen; therefore, technologies that can automate both behavior monitoring and identification of clinical illness signs are key to improving capacity for BRD detection and treatment.

Strategies for Bovine Respiratory Disease (BRD) Diagnosis and Prognosis: A Comprehensive Overview

Despite significant advances in vaccination strategies and antibiotic therapy, bovine respiratory disease (BRD) continues to be the leading disease affecting the global cattle industry. The etiology of BRD is complex, often involving multiple microbial agents, which lead to intricate interactions between the host immune system and pathogens during various beef production stages. These interactions present environmental, social, and geographical challenges. Accurate diagnosis is essential for effective disease management. Nevertheless, correct identification of BRD cases remains a daunting challenge for animal health technicians in feedlots. In response to current regulations, there is a growing interest in refining clinical diagnoses of BRD to curb the overuse of antimicrobials. This shift marks a pivotal first step toward establishing a structured diagnostic framework for this disease. This review article provides an update on recent developments and future perspectives in clinical diagnostics and prognostic techniques for BRD, assessing their benefits and limitations. The methods discussed include the evaluation of clinical signs and animal behavior, biomarker analysis, molecular diagnostics, ultrasound imaging, and prognostic modeling. While some techniques show promise as standalone diagnostics, it is likely that a multifaceted approach-leveraging a combination of these methods-will yield the most accurate diagnosis of BRD.

Technological Tools for the Early Detection of Bovine Respiratory Disease in Farms

Simple Summary

The inclusion of remote automatic systems that use continuous learning technology are of great interest in precision livestock cattle farming, since the average size of farms is increasing while time for individual observation is decreasing. Bovine respiratory disease is a main concern in both fattening and heifer rearing farms due to its impact on antibiotic use, loss of performance, mortality, and animal welfare. Much scientific literature has been published regarding technologies for continuous learning and monitoring of cattle’s behavior and accurate correlation with health status, including early detection of bovine respiratory disease. This review summarizes the up-to-date technologies for early diagnosis of bovine respiratory disease and discusses their advantages and disadvantages under practical conditions.

Abstract

Classically, the diagnosis of respiratory disease in cattle has been based on observation of clinical signs and the behavior of the animals, but this technique can be subjective, time-consuming and labor intensive. It also requires proper training of staff and lacks sensitivity (Se) and specificity (Sp). Furthermore, respiratory disease is diagnosed too late, when the animal already has severe lesions. A total of 104 papers were included in this review. The use of new advanced technologies that allow early diagnosis of diseases using real-time data analysis may be the future of cattle farms. These technologies allow continuous, remote, and objective assessment of animal behavior and diagnosis of bovine respiratory disease with improved Se and Sp. The most commonly used behavioral variables are eating behavior and physical activity. Diagnosis of bovine respiratory disease may experience a significant change with the help of big data combined with machine learning, and may even integrate metabolomics as disease markers. Advanced technologies should not be a substitute for practitioners, farmers or technicians, but could help achieve a much more accurate and earlier diagnosis of respiratory disease and, therefore, reduce the use of antibiotics, increase animal welfare and sustainability of livestock farms. This review aims to familiarize practitioners and farmers with the advantages and disadvantages of the advanced technological diagnostic tools for bovine respiratory disease and introduce recent clinical applications.

Extensive Sheep and Goat Production: The Role of Novel Technologies towards Sustainability and Animal Welfare

Simple Summary

New technologies have been recognized as valuable in controlling, monitoring, and managing farm animal activities. It makes it possible to deepen the knowledge of animal behavior and improve animal welfare and health, which has positive implications for the sustainability of animal production. In recent years, successful technological developments have been applied in intensive farming systems; however, due to challenging conditions that extensive pasture-based systems show, technology has been more limited. Nevertheless, awareness of the available technological solutions for extensive conditions can increase the implementation of their adoption among farmers and researchers. In this context, this review addresses the role of different technologies applied to sheep and goat production in extensive systems. Examples related to precision livestock farming, omics, thermal stress, colostrum intake, passive immunity, and newborn survival are presented; biomarkers of metabolic diseases and parasite resistance breeding are discussed.

Abstract

Sheep and goat extensive production systems are very important in the context of global food security and the use of rangelands that have no alternative agricultural use. In such systems, there are enormous challenges to address. These include, for instance, classical production issues, such as nutrition or reproduction, as well as carbon-efficient systems within the climate-change context. An adequate response to these issues is determinant to economic and environmental sustainability. The answers to such problems need to combine efficiently not only the classical production aspects, but also the increasingly important health, welfare, and environmental aspects in an integrated fashion. The purpose of the study was to review the application of technological developments, in addition to remote-sensing in tandem with other state-of-the-art techniques that could be used within the framework of extensive production systems of sheep and goats and their impact on nutrition, production, and ultimately, the welfare of these species. In addition to precision livestock farming (PLF), these include other relevant technologies, namely omics and other areas of relevance in small-ruminant extensive production: heat stress, colostrum intake, passive immunity, newborn survival, biomarkers of metabolic disease diagnosis, and parasite resistance breeding. This work shows the substantial, dynamic nature of the scientific community to contribute to solutions that make extensive production systems of sheep and goats more sustainable, efficient, and aligned with current concerns with the environment and welfare.

Behavioral and performance response associated with administration of intravenous flunixin meglumine or oral meloxicam immediately prior to surgical castration in bull calves

The objective of this study was to determine the effects of flunixin meglumine or meloxicam on behavioral response and performance characteristics associated with surgical castration in crossbred bulls. Intact male Bos taurus calves (n = 252; averaging 176 kg) were randomly allocated into one of three treatment groups within pen: control (CON), flunixin meglumine (FLU; 2.2 mg/kg intravenous injection), or meloxicam (MEL; 2.0 mg/kg per os). The individual animal was the experimental unit. Calves were individually weighed on days 0 and 14 of the trial to evaluate performance outcomes. On study day 0, treatments were administered, according to their random allocation, immediately prior to surgical castration using the Henderson tool method. Visual analog scale (VAS) assessment and categorical attitude score (CAS) were collected on days −1, 0 (6 h post-castration), 1, 2, 3, and 4 in the study. The VAS was assigned using a 100 mm horizontal line with “normal” labeled at one end of the line and “moribund” at the other end of the horizontal line. The masked observer assigned a mark on the horizontal line based upon the observed severity of pain exhibited by that individual animal. The CAS was assigned by the same observer using five different categories with a score of 0 being “normal”. Average daily gain tended (P = 0.09) to be associated with the treatment group, and MEL had a greater (P = 0.04) average daily gain through day 14 compared with CON. A significant (P < 0.01) treatment by day interaction was indicated for VAS score, and MEL had lower VAS scores on days 0, 1, 2, and 3 post-castration compared with CON; FLU had lower VAS scores on days 0 and 1 compared with CON. A significant treatment by day interaction was not present (P = 0.25) for CAS. The FLU had lesser percent CAS ≥1 (17.5%; P = 0.05) compared with CON (29.4%); MEL has lesser percent CAS ≥1 observations (14.9%; P = 0.01) compared with CON. The median VAS increased as CAS was more severe. Results indicated MEL and FLU calves temporally improved behavioral responses following surgical castration with positive numerical trends for a 14 d average daily gain (ADG). The VAS system appeared to be an effective method of subjective evaluation of pain in beef calves in this study. Route of administration, duration of therapy, and low relative cost make oral meloxicam a reasonable analgesic treatment in calves when administered at the time of surgical castration.

Validation of an Accelerometer Sensor-Based Collar for Monitoring Grazing and Rumination Behaviours in Grazing Dairy Cows

This study evaluated the accuracy of a sensor-based device (AfiCollar) to automatically monitor and record grazing and rumination behaviours of grazing dairy cows on a real-time basis. Multiparous spring-calved dairy cows (n = 48) wearing the AfiCollar were selected for the visual observation of their grazing and rumination behaviours. The total observation period was 36 days, divided into four recording periods performed at different times of the year, using 12 cows in each period. Each recording period consisted of nine daily observation sessions (three days a week for three consecutive weeks). A continuous behaviour monitoring protocol was followed to visually observe four cows at a time for each daily observation session, from 9:00 a.m. to 5:00 p.m. Overall, 144 observations were collected and the data were presented as behaviour activity per daily observation session. The behaviours visually observed were also recorded through an automated AfiCollar device on a real-time basis over the observation period. Automatic recordings and visual observations were compared with each other using Pearson's correlation coefficient (r), Concordance correlation coefficient (CCC), and linear regression. Compared to visual observation (VO), AfiCollar (AC) showed slightly higher (10%) grazing time and lower (4%) rumination time. AC results and VO results had strong associations with each other for grazing time (r = 0.91, CCC = 0.71) and rumination time (r = 0.89, CCC = 0.80). Regression analysis showed a significant linear relationship between AC and VO for grazing time (R² = 0.83, p < 0.05) and rumination time (R² = 0.78, p < 0.05). The relative prediction error (RPE) values for grazing time and rumination time were 0.17 and 0.40, respectively. Overall, the results indicated that AfiCollar is a reliable device to accurately monitor and record grazing and rumination behaviours of grazing dairy cows, although, some minor improvements can be made in algorithm calibrations to further improve its accuracy.

Pain Management in Farm Animals: Focus on Cattle, Sheep and Pigs

Pain causes behavioral, autonomic, and neuroendocrine changes and is a common cause of animal welfare compromise in farm animals. Current societal and ethical concerns demand better agricultural practices and improved welfare for food animals. These guidelines focus on cattle, sheep, and pigs, and present the implications of pain in terms of animal welfare and ethical perspectives, and its challenges and misconceptions. We provide an overview of pain management including assessment and treatment applied to the most common husbandry procedures, and recommendations to improve animal welfare in these species. A cost-benefit analysis of pain mitigation is discussed for food animals as well as the use of pain scoring systems for pain assessment in these species. Several recommendations are provided related to husbandry practices that could mitigate pain and improve farm animal welfare. This includes pain assessment as one of the indicators of animal welfare, the use of artificial intelligence for automated methods and research, and the need for better/appropriate legislation, regulations, and recommendations for pain relief during routine and husbandry procedures.

Methods for Pain Assessment in Calves and Their Use for the Evaluation of Pain during Different Procedures-A Review

The evaluation and assessment of the level of pain calves are experiencing is important, as the experience of pain (e.g., due to routine husbandry procedures) severely affects the welfare of calves. Studies about the recognition of pain in calves, and especially pain management during and after common procedures, such as castration, dehorning, and disbudding, have been published. This narrative review discusses and summarizes the existing literature about methods for pain assessment in calves. First, it deals with the definition of pain and the challenges associated with the recognition of pain in calves. Then it proceeds to outline the different options and methods for subjective and objective pain assessment in calves, as described in the literature. Research data show that there are several tools suitable for the assessment of pain in calves, at least for research purposes. Finally, it concludes that for research purposes, various variables for the assessment of pain in calves are used in combination. However, there is no variable which can be used solely for the exclusive assessment of pain in calves. Also, further research is needed to describe biomarkers or variables which are easily accessible in the field practice.

Description of Behavioral Patterns Displayed by a Recently Weaned Cohort of Healthy Dairy Calves

Simple Summary

Modern technology has allowed researchers to track the movement patterns of cattle with increasing accuracy in order to gain a greater understanding of both overt and subtle activity trends. The aim of this study was to describe and analyze movement patterns displayed by recently weaned and healthy dairy calves. Three movement pattern clusters were identified, and calves in this study were more active in the afternoon and at night. There was a correlation between the rate of movement, linearity ratio, and the distance traveled. However, turning angles do not have any influence on the distance traveled and the rate of movement across the three cluster-type movements. The findings reported in this study could be used to further develop the interpretation of movement and behavior patterns of calves in order to establish an early detection system for poor health and welfare on dairy farms.

Abstract

Animals display movement patterns that can be used as health indicators. The movement of dairy cattle can be characterized into three distinct cluster types. These are cluster type 1 (resting), cluster type 2 (traveling), and cluster type 3 (searching). This study aimed to analyze the movement patterns of healthy calves and assess the relationship between the variables that constitute the three cluster types. Eleven Holstein calves were fitted with GPS data loggers, which recorded their movement over a two week period during spring. The GPS data loggers captured longitude and latitude coordinates, distance, time and speed. It was found that the calves were most active during the afternoon and at night. Slight inconsistencies from previous studies were found in the cluster movements. Cluster type 2 (traveling) reported the fastest rate of movement, whereas cluster type 1 (resting) reported the slowest. These diverse movement patterns could be used to enhance the assessment of dairy animal health and welfare on farms.

Administration of acetylsalicylic acid after parturition in lactating dairy cows under certified organic management: Part II. Biomarkers of nociception, inflammation, and stress

The objective was to assess the effect of oral administration of acetylsalicylic acid after calving on the concentrations of substance P (SP), haptoglobin (HP), and cortisol in lactating dairy cows. Holstein dairy cows (n = 152) from 3 organic herds were included. At parturition, cows were blocked by parity [multiparous (MULT) and primiparous (PRIM)] and calving ease [eutocia (EUT) and dystocia (DYS)] and were randomly assigned to 1 of 2 treatment groups: aspirin (ASP; n = 76), in which within 12 h after parturition cows received 4 treatments with acetylsalicylic acid (100 mg/kg; 2 boluses) at 12-h intervals, or placebo (PLC; n = 76), in which within 12 h after parturition cows received 4 consecutive treatments with gelatin capsules (2 capsules) containing water 12 h apart. Blood samples were collected immediately before treatment and at 12, 24, 36, 48, and 168 h (7 DIM) for assessment of circulating concentration of SP, HP, and cortisol. Based on farm records, cows were classified in the following clinical disease categories: no clinical disease event (NO-EVT), a single clinical disease event (SI-EVT), and more than 1 clinical disease event (MU-EVT). The study data were analyzed as a randomized complete block design using mixed multiple linear and logistic regression models. With regard to HP, there was a tendency for an interaction between treatment and parity, where MULT cows treated with ASP had lower concentration of HP compared with MULT cows treated with PLC (ASP = 124.33 ± 6.83 µg/mL; PLC = 143.9 ± 7.24 µg/mL). Analysis by calving ease showed that cows with DYS had higher concentrations of HP (DYS = 159.17 ± 5.97 µg/mL; EUT = 138.72 ± 6.22 µg/mL) and SP (only at 168 h; DYS = 64.99 pg/mL, 95% confidence interval, CI: 2.68-2.81; EUT = 60.33 pg/mL, 95% CI: 2.91-3.06) after calving compared with EUT cows. Regardless of treatment, PRIM cows had higher concentrations of SP (MULT = 55.11 pg/mL, 95% CI: 1.27-1.30; PRIM = 57.62 pg/mL, 95% CI: 1.99-2.06), HP (MULT = 134.14 ± 4.96 µg/mL; PRIM = 163.75 ± 7.76 µg/mL), and cortisol (MULT = 18.65 µg/mL, 95% CI: 1.02-1.05; PRIM = 21.92 µg/mL, 95% CI: 1.67-1.74) compared with MULT cows. In addition, cows that experienced SI-EVT or MU-EVT had higher concentrations of HP (NO-EVT = 134.13 ± 5.95 µg/mL; SI-EVT = 142.68 ± 7.32 µg/mL; MU-EVT = 170.03 ± 9.42 µg/mL) and cortisol (NO-EVT = 17.86 µg/mL, 95% CI: 1.20-1.24; SI-EVT = 21.01 µg/mL, 95% CI: 1.61-1.67; MU-EVT = 22.01 µg/mL, 95% CI: 2.08-2.18) compared with cows with NO-EVT recorded. Results from this study suggest that a short-duration anti-inflammatory therapy after calving reduced HP in MULT cows but may not have effects on SP and cortisol concentrations. Calving ease and parity affected the concentrations of markers of inflammation, nociception, and stress regardless of treatment. Further research is warranted to assess anti-inflammatory strategies aimed at decreasing inflammation and stress in DYS and PRIM cows and therefore improve welfare and performance of these high-priority groups.

Analysis of Cattle Social Transitional Behaviour: Attraction and Repulsion

Understanding social interactions in livestock groups could improve management practices, but this can be difficult and time-consuming using traditional methods of live observations and video recordings. Sensor technologies and machine learning techniques could provide insight not previously possible. In this study, based on the animals' location information acquired by a new cooperative wireless localisation system, unsupervised machine learning approaches were performed to identify the social structure of a small group of cattle yearlings (n=10) and the social behaviour of an individual. The paper first defined the affinity between an animal pair based on the ranks of their distance. Unsupervised clustering algorithms were then performed, including K-means clustering and agglomerative hierarchical clustering. In particular, K-means clustering was applied based on logical and physical distance. By comparing the clustering result based on logical distance and physical distance, the leader animals and the influence of an individual in a herd of cattle were identified, which provides valuable information for studying the behaviour of animal herds. Improvements in device robustness and replication of this work would confirm the practical application of this technology and analysis methodologies.

Transforming the Adaptation Physiology of Farm Animals through Sensors

Despite recent scientific advancements, there is a gap in the use of technology to measure signals, behaviors, and processes of adaptation physiology of farm animals. Sensors present exciting opportunities for sustained, real-time, non-intrusive measurement of farm animal behavioral, mental, and physiological parameters with the integration of nanotechnology and instrumentation. This paper critically reviews the sensing technology and sensor data-based models used to explore biological systems such as animal behavior, energy metabolism, epidemiology, immunity, health, and animal reproduction. The use of sensor technology to assess physiological parameters can provide tremendous benefits and tools to overcome and minimize production losses while making positive contributions to animal welfare. Of course, sensor technology is not free from challenges; these devices are at times highly sensitive and prone to damage from dirt, dust, sunlight, color, fur, feathers, and environmental forces. Rural farmers unfamiliar with the technologies must be convinced and taught to use sensor-based technologies in farming and livestock management. While there is no doubt that demand will grow for non-invasive sensor-based technologies that require minimum contact with animals and can provide remote access to data, their true success lies in the acceptance of these technologies by the livestock industry.

A Review of Welfare Indicators of Indoor-Housed Dairy Cow as a Basis for Integrated Automatic Welfare Assessment Systems

Simple Summary

Many techniques have been developed to measure single indicators of reduced welfare in farm animals, such as changes in the walking pattern to detect lameness in dairy cows. However, there is still a need to combine these single measurements to get a more complete picture of the wellbeing of an animal. Based on a literature review on dairy cow welfare, this review provides a basis for the development of an integrated automatic system to assess the welfare of dairy cows on the farm. It provides an overview of the main welfare issues for dairy cows, such as lameness, heat stress, or pain and of the most established indicators that could help to detect these welfare issues on the farm. We found that there are several indicators, such as reduced feed intake, that are common to most welfare issues and that are therefore suitable to detect reduced welfare in general, while other indicators mainly identify one welfare issue, such as increased respiratory rate, as an indicator of heat stress. Combining these different types of indicators would provide a good basis to develop an integrated automatic system that could assist farmers in the detection of reduced welfare on their farms.

Abstract

For on-farm welfare assessment many automatic methods have been developed to detect indicators of reduced welfare. However, there is still a need to integrate data from single sources to obtain a complete picture of the welfare of an animal. This review offers a basis for developing integrated automatic systems to assess dairy cow welfare by providing an overview of the main issues that challenge cow welfare (e.g., lameness) and of well-established indicators that could detect these issues on the farm. Based on a literature review of 4 reviews on cow welfare in general and 48 reviews on single welfare issues, we identified 18 different major welfare issues and 76 matching indicators that could be detected automatically on the farm. Several indicators, e.g., feed intake, showed a consistent association with welfare across many different issues. Although some of these indicators are discussed critically, this means there are many indicators that potentially could detect reduced welfare in general. Other types of indicators could detect one specific welfare issue, e.g., increased respiratory rate for heat stress. These different types of indicators combined provide a basis to develop integrated automatic systems that ultimately would help farmers to detect welfare problems at an early stage.

Technical note: Validation of a system for monitoring individual behavior of Holstein cows

The objectives of the 2 studies reported herein were to validate the accuracy of an automated monitoring device (AMD) to detect side lying, resting, activity, rumination, eating, walking, and panting in nonlactating and lactating dairy cows. Additionally, we aimed to determine whether the total time per cow-state recorded by the AMD within a 30-min interval corresponds to the total time per cow-state recorded simultaneously by visual observation. Study personnel (n = 2) observed pregnant nonlactating Holstein cows (n = 10) for 30 min in the morning and 30 min in the afternoon for 6 consecutive days and recorded continuously each cow-state. In study 2, study personnel (n = 2) observed lactating Holstein cows (n = 10) for 30 min in the morning and 30 min in the afternoon for 6 consecutive days. In both studies, cow-state was recorded every second, and within 1 min, the most prevalent cow-state was considered to be the behavior presented by the cow during that interval. Using the observer as the gold standard, test characteristics were calculated for the minute-by-minute interval analyses. For the 30-min interval analyses, the concordance correlation coefficient (p_c) and the coefficient of determination (R²) between the total minutes for each cow-state recorded by the observer and the AMD were calculated. In study 1, for the minute-by-minute interval analyses, test characteristics were high for rumination (≥90.1%) and eating (≥73.8%), moderate for resting (≥62.9%), but negligible for medium activity (≥17%). For the 30-min interval analyses, the correlations between the total time of visual observations compared with the total time recorded by AMD for rumination (R² = 0.97, p_c = 0.98) and eating (R² = 0.91, p_c = 0.94) were very high, for resting (R² = 0.77, p_c = 0.79) was high, and for medium activity (R² = 0.41, p_c = 0.41) was low. In study 2, for the minute-by-minute interval analyses, test characteristics were high for rumination (≥79.4%), eating (≥74.2%), and resting (≥73.0%), but they were low for panting (≥31.3%) and negligible for medium activity (≥22.2%). For the 30-min interval analyses, the correlations were similar to study 1 (rumination: R² = 0.85, p_c = 0.91; eating: R² = 0.95, p_c = 0.97; resting: R² = 0.84, p_c = 0.90; medium activity: R² = 0.44, p_c = 0.57; and panting: R² = 0.21, p_c = 0.42). In summary, the AMD used in this study provided accurate data regarding resting, rumination, and eating of pregnant nonlactating and lactating Holstein cows.

Comparison of thermal imaging and rectal temperature in the diagnosis of pyrexia in pre-weaned calves using on farm conditions

Measuring core body temperature is used as part of the diagnostic process in assessing the health of animals. Typically in calves, this is carried out using a rectal thermometer which can be time consuming, stressful to the calf and is invasive by nature. A non-invasive technique that is gaining recognition is thermal imaging. This study investigated the use of thermal imaging as a technique to assess core body temperature in pre-weaned artificially reared calves. A total of 125 male and female calves had rectal temperatures measured daily from day 7 until day 40 of life, and at the same time had a thermal image taken of the area around the medial canthus of the eye. A weak correlation (r = 0.28) was found between calf rectal temperature and thermal image temperature. A multivariable predictive model for core body temperature increased the correlation (r = 0.32) when including the environmental parameters of air temperature (p < .001) and wind speed (p < .001) as well as reconstituted milk replacer consumption (p < .01). The effectiveness of a predictive model including these parameters for the detection of calves with a core body temperature ≥ 39.5 °C was examined and found to have a sensitivity of 0% and a specificity of 100%. The results of this study demonstrate the need to take thermal environmental parameters into consideration when using thermal imaging to assess body temperature. However, the results suggest that accurate measures of core body temperature using thermal imaging cannot be achieved under commercial farm conditions. Further research is needed to determine what other factors could be measured to increase predictive ability.

Technical note: validation of a system for monitoring individual behavior in beef heifers

The objectives of the 2 studies conducted were to validate the accuracy of an automated monitoring device (AMD; HR-LDn tags, SCR Engineers Ltd., Netanya, Israel) for different types of behaviors or cow-states (side lying, resting, medium activity, high activity, rumination, grazing, walking, and panting) in beef heifers and to determine if the total time per cow-state recorded by the AMD corresponds to the total time per cow-state recorded by instantaneous observations. Cow-state is recorded every second and, within 1 min, the most prevalent cow-state is considered to be the behavior presented by the animal during that interval. Study personnel (n = 2) observed heifers (n = 10) for 20 min from 0800 to 1140 h and 10 min from 1500 to 1640 h during 4 consecutive days and recorded continuously each cow-state at started and ended. Thus, study personnel were able to determine within a 1-min interval, which cow-state was most prevalent and represented the heifer's behavior. Because the proprietary machine learning algorithm prioritizes certain behaviors over others based on their contribution to the understanding of generalized bovine behavior patterns, we also determined the most prevalent behavior observed in 5-min intervals. Test characteristics (sensitivity, specificity, accuracy, and negative and positive predicted values) were calculated using the observer as the gold standard. In study 2, heifer behavior was scanned by observers (n = 2) every 5 min from 0800 to 1100 h and 1500 to 1800 h for 3 consecutive days. Total minutes per cow-state according to the observer were compared with the total minutes per cow-state according to the AMD during the same period to determine the correlation coefficient. In study 1, test characteristics were high (low ≤ 40%, moderate = 41 to 74%, high ≥ 75%) for rumination (≥ 89.7%), grazing (≥ 76.5%), and side lying (≥ 81.8%), and moderate for resting (≥ 48.8%). In study 2, the correlation coefficient for rumination (R2 = 0.92) and grazing (R2 = 0.90) were high and the correlation coefficient for resting (R2 = 0.66) and walking (R2 = 0.33) were moderate. We conclude that the AMD used in this study showed high accuracy when measuring rumination and grazing, but it was subpar when measuring resting and walking. The algorithms employed by the AMD used need to be improved for determination of walking and resting behaviors of beef cattle.

The new design of cows' behavior classifier based on acceleration data and proposed feature set

Monitor and classify behavioral activities in cows is a helpful support solution for livestock based on the analysis of data from sensors attached to the animal. Accelerometers are particularly suited for monitoring cow behaviors due to small size, lightweight and high accuracy. Nevertheless, the interpretation of the data collected by such sensors when characterizing the type of behaviors still brings major challenges to developers, related to activity complexity (i.e., certain behaviors contain similar gestures). This paper presents a new design of cows' behavior classifier based on acceleration data and proposed feature set. Analysis of cow acceleration data is used to extract features for classification using machine learning algorithms. We found that with 5 features (mean, standard deviation, root mean square, median, range) and 16-second window of data (1 sample/second), classification of seven cow behaviors (including feeding, lying, standing, lying down, standing up, normal walking, active walking) achieved the overall highest performance. We validated the results with acceleration data from a public source. Performance of our proposed classifier was evaluated and compared to existing ones in terms of the sensitivity, the accuracy, the positive predictive value, and the negative predictive value.

Performance and Behavioural Responses of Group Housed Dairy Calves to Two Different Weaning Methods

The weaning of dairy calves is a significant stressor which can impact on calf performance and welfare. However, many traditional methods of assessing the effects of stressors can be invasive and impractical for farmers. This study aimed to use a combination of non-invasive monitoring technologies alongside traditional measures of calf performance to examine the impact of two contrasting weaning methods commonly used on dairy farms in the United Kingdom. Ninety group-housed Holstein Friesian calves were allocated to one of two weaning methods: (i) gradual weaning (GW) with volume of milk replacer (MR) stepping down from 36 days of age and complete withdrawal of MR at 57 days of age and (ii) abrupt weaning (AW) with consistent daily volume of milk replacer and complete withdrawal of MR at 50 days of age. Feeding regimes were such that calves from both treatments were offered the same total amount of milk powder. Gradually weaned calves displayed increased solid feed intake at an earlier age when compared with AW calves. Feed conversion efficiency (FCE) was reduced in gradually weaned calves between days 36 and 49. However, there was no difference in live weight (LWT) or average daily gain (ADG) throughout this period. Abrupt weaning at 50 days of age resulted in decreased ADG and FCE between days 50 and 56. However, there were no treatment differences in ADG between days 57 and 62. Live weight tended to be increased by 2.2 kg in GW calves when compared with AW calves at the end of experiment on day 63. Frequency of unrewarded visits to the milk feeder throughout the pre-wean period was consistently increased in GW calves. Daily lying time was reduced in AW compared with GW calves in the days following abrupt weaning (days 50-55). However, these differences did not persist between days 57 and 62. Heart rate variability (HRV) tended to be decreased in GW compared with AW calves in the period following complete withdrawal of milk replacer. Findings from the current study suggest that calves offered the same total amount of milk powder can be weaned either gradually from 36 days of age or abruptly at 50 days of age without significant impact to live weight at 63 days of age. However, both behavioural and physiological data collected using the methods described could suggest that gradual weaning of calves from 36 days of age results in an increase in underlying frustration. This study highlights the potential of using a combination of non-invasive monitoring technologies in assessing calf response to common management practices.

The behavior of dairy cattle in late gestation: Effects of parity and dystocia

The aim of this study was to objectively assess, using an automated behavioral monitoring system, any behavioral differences between primiparous and multiparous cows before calving, and to quantify any behavioral differences between assisted (dystocic) and unassisted (eutocic) calvings. Data were collected from 32 multiparous and 12 primiparous Holstein dairy cattle to describe normal calving behavior and parity differences. To quantify behavior related to calving difficulty, the data from 14 animals that had dystocia at calving were matched to cows that had an eutocic calving based on parity, locomotion score, calf breed, calf sex, month, and year of calving. An IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) was fitted to the right hind leg of cows 4 wk before their expected calving date. Data for lying time, standing time, number of steps, motion index (total motion), and the total number of standing and lying bouts (postural transitions) were automatically collected and summed into 15-min blocks. Behavioral variables were summarized into 2-h periods and 24-h periods before analyses. Mixed-effect models were used to analyze cow behavior in the last 4 d before calving (d -4 to -1), and on the day of calving. In the 4 d before calving, compared with multiparous cows, primiparous cows lay down an average 2.8 h/d less, had 9.1 more postural transitions/d (37.7 ± 1.2 vs. 27.6 ± 0.7), walked 172 more steps/d, and had a higher motion index (2,673.2 vs. 1,981.5 units/d). There was an effect of 2-h period on all behavioral variables on the day of calving. No indicator of calving difficulty was found on the day of calving, nor the days leading up to calving. These findings suggest that parity should be considered when predicting the day of calving, and changes in cow behavior on the day of calving could be used to identify calving cows, and to predict the time of calving.

Using Non-Invasive Monitoring Technologies to Capture Behavioural, Physiological and Health Responses of Dairy Calves to Different Nutritional Regimes during the First Ten Weeks of Life

This study aimed to examine the use of non-invasive monitoring technologies as a means of capturing behavioural, physiological and health responses of calves allocated to different nutritional regimes. Seventy-four Holstein Friesian calves were individually penned and allocated to receive either high (HML) or conventional (CML) milk replacer (MR) levels between 5-70 days of age. Additionally calves were allocated to one of four forage treatments: (i) chopped straw offered between 14-70 days of age (CS14), (ii) chopped straw offered between 56-70 days of age (CS56), (iii) grass silage offered between 56-70 days of age (GS56), and (iv) no forage in the pre-wean period (NF). A representative sample of calves from each treatment were fitted with activity sensors and heart rate monitors throughout the experimental period to examine lying behaviour and heart rate variability, respectively. Thermal images of the eye and rectal area of each calf were taken 5 days/week between 5-77 days of age. Faecal and respiratory scoring of each individual calf was carried out on a daily basis throughout the experimental period. Milk replacer feeding level had limited effects on measures of calf health, although HML calves tended to have an increased likelihood for receiving treatment for scour than CML calves. Daily lying time (min/d) was lower in HML calves following reduction in MR feeding frequency at 43 days of age and weaning at 71 days of age when compared with CML calves. Additionally, HML calves displayed a lower heart rate variability following weaning, this suggestive of increased stress load. There were limited effects of forage treatment, however, CS14 calves displayed a greater daily lying time following MR step-down at 68 days of age, this potentially indicating increased rumination. Results of the present study highlight the benefits of using remote monitoring technologies as a means of detecting behavioural and physiological changes as a result of nutritional management strategy in individually housed dairy calves.

The effect of calf jacket usage on performance, behaviour and physiological responses of group-housed dairy calves

Poor performance and ill-health of calves in the pre-wean period can affect future productivity. Increasing numbers of producers are opting to use calf jackets as a means of mitigating the potential negative effects of low ambient temperatures, wind speed and precipitation on growth and health. This study aimed to use a range of noninvasive monitoring technologies to investigate the effects of using calf jackets in the first 3 weeks of life on calf performance and behavioural and physiological parameters. Ninety Holstein-Friesian calves were allocated to one of the two treatments: (i) Jacketed until 21 days of age and (J; n = 44) ii. Nonjacketed (NJ; n = 46). Calves were group housed and fed milk replacer (MR) and concentrate solid feed via automatic feeders. Calves were weaned at day 56, and the experiment was completed at day 63. Health assessments were conducted on a daily basis throughout the experiment using predefined faecal and respiratory scoring protocols. A range of novel, noninvasive monitoring technologies were used to examine the activity, heart rate and thermal profiles of calves on an individual basis throughout the experimental period. There were no differences in calf live weight (LWT), average daily gain (ADG) or feed conversion efficiency (FCE) in J and NJ calves between days 5 to 20. However, NJ calves consumed more MR and had more unrewarded visits to the milk feeder than J calves during this period. Although calf LWT was comparable across treatments in the week following jacket removal (days 21 to 28), both ADG and FCE tended to be greater in NJ calves. There were no treatment differences in calf LWT at the end of the study (d63). When measured over a period of 24 h and at a mean ambient temperature of 7.7°C, skin surface temperature was 6.37°C higher in J calves. Core body temperature was higher in J calves between days 5 to 20; however, there were no differences in IR eye or IR rectal temperature. No differences in lying behaviour occurred, with calves spending 18 and 17 h/day lying between days 5 to 20 and days 21 to 28, respectively. Under the climatic and management conditions described, no significant benefits to calf performance were found as a result of the provision of calf jackets to group-housed calves in the first 3 weeks of life. The higher frequency of unrewarded visits to the milk feeder in NJ calves during the first 3 weeks of life could be suggestive of a lack of satiety in these calves.

Control of bovine respiratory disease, with and without co-morbidity by otitis media, in dairy heifers comparing gamithromycin, tulathromycin, or no medication at a commercial development facility

The objective of this study was to evaluate one strategy for control (metaphylaxis) of bovine respiratory disease, with and without co-morbidity with otitis media, in dairy heifers at a commercial development facility. Individual heifers were the experimental unit. At weaning, 1 of 3 experimental treatments (gamithromycin, tulathromycin, or no medication) was randomly assigned to 1,567 heifers from 11 different dairies. Gamithromycin was administered to 631 heifers, tulathromycin was administered to 621 heifers, and no medication was administered to 315 heifers (negative control). Heifers were then commingled and penned according to body weight. Each pen contained heifers from each group, and periodically, larger numbers of heifers were penned together. All heifers were observed for the subsequent 42 d and treated according to protocols prescribed for the facility. Morbidity due to respiratory disease was less for heifers medicated with gamithromycin than for heifers medicated with tulathromycin. Morbidity due to respiratory disease was less for heifers medicated with gamithromycin than for heifers in the negative control group. Fewer heifers medicated with either antimicrobial were subsequently treated because of co-morbidity with otitis media. Mortality was not different among the treatment groups. Heifers medicated with either antimicrobial had greater average daily gain than did heifers in the negative control group.

Use of thermal imaging in dairy calves: exploring the repeatability and accuracy of measures taken from different anatomical regions

Three experiments were undertaken to 1) quantify the repeatability and reproducibility of thermal imaging across day and operator experience and 2) assess the correlation between descriptive infrared (IR) temperature parameters from different anatomical areas and core body temperature in dairy calves under 12 wk of age. In experiment 1, a single operator captured 30 replicate images of both the left and right eyes (defined as the whole eye + 1 cm margin) and the rectal area (defined as the anus +1.5 cm margin) from each of 16 calves. In experiment 2, three operators of varying experience captured images from both the left and right eyes and the rectal area of each of 12 calves. In experiment 3, a single operator captured images of the right eye and rectal area for a period of 5 consecutive days for each of 205 calves. All images were captured between 0900 and 1300 h. Core body temperature, obtained via rectal thermometer, was recorded every day for each of the 205 calves following completion of IR image capture. Ambient temperature and relative humidity were adjusted for each thermal image prior to manual extraction of maximum, minimum, and average temperature parameters. In experiment 1, lowest error variance was found within the maximum temperature parameter and the right eye was determined as the most repeatable anatomical area, with 80.48% of the total proportion of variance attributed to the calf. Results indicated that capturing at least three replicate images would provide the precision required to identify ill-health in calves. In experiment 2, operator variance was low across anatomical areas, with values of ≤0.01°C² for the right and left eyes and ≤0.04°C² for the rectal area. In experiment 3, day to day variation of thermal image measurements and core body temperature were minimal across anatomical areas with values of ≤0.008°C². Correlations ranging from 0.16 to 0.32, and from 0.31 to 0.47 were found between maximum eye and core body temperature and maximum rectal area and core body temperature, respectively. Results of the present study indicate a low level of variability and high level of repeatability within IR temperature measurements in calves under 12 wk of age, particularly within maximum temperature parameters. Providing operators of varying abilities with a basic standardized protocol is sufficient to limit between-operator variation. Further research is required to investigate whether correlation between IR and core body temperature can be improved.

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Data to decisions

Big data are frequently used in many facets of business and agronomy to enhance knowledge needed to improve operational decisions. Livestock operations collect data of sufficient quantity to perform predictive analytics. Predictive analytics can be defined as a methodology and suite of data evaluation techniques to generate a prediction for specific target outcomes. The objective of this manuscript is to describe the process of using big data and the predictive analytic framework to create tools to drive decisions in livestock production, health, and welfare. The predictive analytic process involves selecting a target variable, managing the data, partitioning the data, then creating algorithms, refining algorithms, and finally comparing accuracy of the created classifiers. The partitioning of the datasets allows model building and refining to occur prior to testing the predictive accuracy of the model with naive data to evaluate overall accuracy. Many different classification algorithms are available for predictive use and testing multiple algorithms can lead to optimal results. Application of a systematic process for predictive analytics using data that is currently collected or that could be collected on livestock operations will facilitate precision animal management through enhanced livestock operational decisions.

Using advanced technologies to quantify beef cattle behavior

For decades, we have relied upon visual observation of animal behavior to define clinical disease, assist in breeding selection, and predict growth performance. Limitations of visual monitoring of cattle behavior include training of personnel, subjectivity, and brevity. In addition, extensive time and labor is required to visually monitor behavior in large numbers of animals, and the prey instinct of cattle to disguise abnormal behaviors in the presence of a human evaluator is problematic. More recently, cattle behavior has been quantified objectively and continuously using advanced technologies to assess animal welfare, indicate lameness or disease, and detect estrus in both production and research settings. The current review will summarize three methodologies for quantification of cattle behavior with focus on U.S. beef production systems; 1) three-axis accelerometers that quantify physical behavior, 2) systems that document feeding and watering behavior via radio frequency, and 3) triangulation or global positioning systems to determine location and movement of cattle within a pen or pasture. Furthermore, advances in Wi-Fi and radio frequency technology have allowed many of these systems to operate remotely and in real-time and efforts are underway to develop commercial applications that may allow early detection of respiratory or other cattle diseases in the production environment. Current challenges with commercial application of technology for early disease detection include establishment of an appropriate algorithm to ensure maximum sensitivity and specificity, reliable and repeatable data collection in harsh environments, cost:benefit, and integration with traditional methodology for clinical diagnosis. Advanced technologies have also allowed cattle researchers to determine temporal variance in behavior or variability between experimental treatments. However, these data sets are typically very large and challenges exist regarding statistical analysis and reporting.

Use of three-dimensional accelerometers to evaluate behavioral changes in cattle experimentally infected with bovine viral diarrhea virus

OBJECTIVE To assess the use of 3-D accelerometers to evaluate behavioral changes in cattle experimentally infected with a low-virulent strain of bovine viral diarrhea virus (BVDV). ANIMALS 20 beef steers (mean weight, 238 kg). PROCEDURES Calves were allocated to a BVDV (n = 10) or control (10) group. On day 0, calves in the BVDV group were inoculated with a low-virulent strain of BVDV (4 × 10(6) TCID50, intranasally), and calves in the control group were sham inoculated with BVDV-free medium (4 mL; intranasally). An accelerometer was affixed to the right hind limb of each calf on day -7 to record activity (lying, walking, and standing) continuously until 35 days after inoculation. Baseline was defined as days -7 to -1. Blood samples were collected at predetermined times for CBC, serum biochemical analysis, virus isolation, and determination of anti-BVDV antibody titers. RESULTS All calves in the BVDV group developed viremia and anti-BVDV antibodies but developed only subclinical or mild disease. Calves in the control group did not develop viremia or anti-BVDV antibodies. Mean time allocated to each activity did not differ significantly between the BVDV and control groups on any day except day 8, when calves in the BVDV group spent less time standing than the calves in the control group. Following inoculation, calves in both groups tended to spend more time lying and less time walking and standing than they did during baseline. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated that behavioral data obtained by accelerometers could not distinguish calves subclinically infected with BVDV from healthy control calves. However, subtle changes in the behavior of the BVDV-infected calves were detected and warrant further investigation.

Determination of value of bovine respiratory disease control using a remote early disease identification system compared with conventional methods of metaphylaxis and visual observations

Mitigation of the deleterious effects of bovine respiratory disease (BRD) is an important issue in the cattle industry. Conventional management of calves at high risk for BRD often includes mass treatment with antimicrobials at arrival followed by visual observation for individual clinical cases. These methods have proven effective; however, control program efficacy is influenced by the accuracy of visual observation. A remote early disease identification (REDI) system has been described that monitors cattle behavior to identify potential BRD cases. The objective of this research was to compare health and performance outcomes using either traditional BRD control (visual observation and metaphylaxis) or REDI during a 60-d postarrival phase in high-risk beef calves. The randomized controlled clinical trial was performed in 8 replicates at 3 different facilities over a 19-mo period. In each replicate, a single load of calves was randomly allocated to receive either conventional management (CONV; total = 8) or REDI (total = 8) as the method for BRD control. Cattle were monitored with each diagnostic method for the first 30 d on feed and performance variables were collected until approximately 60 d after arrival. Statistical differences ( < 0.10) were not identified in common performance (ADG) or health (morbidity, first treatment success, and mortality risk) among the treatment groups. Calves in the REDI pens had a lower ( < 0.01) average number of days on feed at first treatment (9.1 ± 1.2 d) compared with CONV pens (15.8 ± 1.2 d). There were no statistical differences ( > 0.10) in risk of BRD treatment and REDI calves were not administered antimicrobials at arrival; therefore, REDI calves had a lower ( < 0.01) average number of doses of antimicrobials/calf (0.75 ± 0.1 doses) compared with CONV calves (1.67 ± 0.1 doses). In this trial, the REDI system was comparable to conventional management with the potential advantages of earlier BRD diagnosis and decreased use of antimicrobials. Further research should be performed to evaluate the longer-term impacts of the 2 systems.

Feeding behavior as an early predictor of bovine respiratory disease in North American feedlot systems

Bovine respiratory disease (BRD), which can cause substantial losses for feedlot operations, is often difficult to detect based solely on visual observations. The objectives of the current study were to determine a BRD case identification based on clinical and laboratory parameters and assess the value of feeding behavior for early detection of BRD. Auction-derived, mixed-breed beef steers (n = 213) with an average arrival weight of 294 kg were placed at a southern Alberta commercial feedlot equipped with an automated feed bunk monitoring system. Feeding behavior was recorded continuously (1-s intervals) for 5 wk after arrival and summarized into meals. Meals were defined as feeding events that were interrupted by less than 300 s nonfeeding. Meal intake (g) and meal time (min) were further summarized into daily mean, minimum, maximum, and sum and, together with frequency of meals per day, were fit into a discrete survival time analysis with a conditional log-log link. Feedlot staff visually evaluated (pen-checked) health status twice daily. Within 35 d after arrival, 76% (n = 165) of the steers had 1 or more clinical signs of BRD (reluctance to move, crusted nose, nasal or ocular discharge, drooped ears or head, and gaunt appearance). Whereas 41 blood samples could not be processed due to immediate freezing, for 124 of these steers, complete and differential blood cell count, total serum protein, plasma fibrinogen, serum concentration of haptoglobin (HP), and serum amyloid A (SAA) were determined. The disease definition for BRD was a rectal temperature ≥ 40.0°C, at least 2 clinical signs of BRD, and HP > 0.15 mg/mL. It was noteworthy that 94% of the 124 steers identified by the feedlot staff with clinical signs of BRD had HP > 0.15 mg/mL. An increase in mean meal intake, frequency, and mean inter-meal interval was associated with a decreased hazard for developing BRD 7 d before visual identification (P < 0.001). Furthermore, increased mean mealtime, frequency, and mean inter-meal interval were associated with a decreased BRD hazard up to 7 d before feedlot staff noticed clinical symptoms (P < 0.001). In conclusion, mean intake per meal as well as mean meal time and frequency of meals could be used to predict the hazard of BRD in feedlot cattle 7 d before visual detection and could be considered in commercial feedlot settings once a predictive algorithm has been developed.

Pain and sickness behavior associated with corneal lesions in dairy calves

Infectious bovine keratoconjunctivitis (IBK) is a common corneal disease of calves that adversely affects animal welfare by causing pain and weight loss. Identifying behavioral indicators of pain and sickness in calves with IBK is necessary for designing studies that aim to identify effective means of pain mitigation. Consistent with principles of the 3Rs for animal use in research, data from a randomized blinded challenge study was used to identify and describe variation of behaviors that could serve as reliable indicators of pain and sickness in calves with corneal injuries. Behavioral observations were collected from 29 Holstein calves 8 to 12 weeks of age randomly allocated to one of three treatments: (1) corneal scarification only, (2) corneal scarification with inoculation with Moraxella bovoculi and (3) corneal scarification with inoculation with Moraxella bovis. Behavior was continuously observed between time 1230 - 1730 h on day -1 (baseline time period) and day 0 (scarification time period). Corneal scarification and inoculation occurred between 0800 - 1000 h on day 0. Frequency of head-directed behaviors (head shaking, head rubbing, head scratching) and durations of head rubbing, feeding, standing with head lifted, lying with head lifted and sleeping were compared between study days and groups. Following scarification, the frequency of head-directed behavior significantly increased (p = 0.0001), as did duration of head rubbing (p=0.02). There was no significant effect of trial, trial day, treatment or treatment-day interaction on other behaviors studied. Our study demonstrated that head-directed behavior, such as head shaking, rubbing and scratching, was associated with scarification of eyes using an IBK challenge model, but sickness behavior was not observed.

Temporal-spatial heterogeneity in animal-environment contact: implications for the exposure and transmission of pathogens

Contact structure, a critical driver of infectious disease transmission, is not completely understood and characterized for environmentally transmitted pathogens. In this study, we assessed the effects of temporal and spatial heterogeneity in animal contact structures on the dynamics of environmentally transmitted pathogens. We used real-time animal position data to describe contact between animals and specific environmental areas used for feeding and watering calves. The generated contact structure varied across days and among animals. We integrated animal and environmental heterogeneity into an agent-based simulation model for Escherichia coli O157 environmental transmission in cattle to simulate four different scenarios with different environmental bacteria concentrations at different areas. The simulation results suggest heterogeneity in environmental contact structure among cattle influences pathogen prevalence and exposure associated with each environment. Our findings suggest that interventions that target environmental areas, even relatively small areas, with high bacterial concentration can result in effective mitigation of environmentally transmitted pathogens.

The Challenges to Improve Farm Animal Welfare in the United Kingdom by Reducing Disease Incidence with Greater Veterinary Involvement on Farm

Simple Summary

Sick cattle and sheep are often treated by farmers without prior veterinary examination and, as a consequence, incorrect diagnoses and inappropriate therapies are common, but these failings largely go undetected and unreported. Many farmers maintain that market forces render veterinary care of individual sick sheep and cattle too expensive. Delays in requesting veterinary attention are not uncommon causing unnecessary animal suffering and a poorer outcome. Incidence rates of endemic diseases in the United Kingdom are too high, causing animal welfare concerns, but these could be reduced by the implementation of proven veterinary flock/herd health programmes.

Abstract

The Cattle Health and Welfare Group of Great Britain report (CHAWG; 2012) lists the most important cattle diseases and disorders but fails to fully acknowledge the importance of animal mental health and; in so doing; misses the opportunity to further promote animal welfare. There are effective prevention regimens; including vaccination; husbandry and management strategies for all ten listed animal health concerns in the CHAWG report; however control measures are infrequently implemented because of perceived costs and unwillingness of many farmers to commit adequate time and resources to basic farm management tasks such as biosecurity; and biocontainment. Reducing disease prevalence rates by active veterinary herd and flock health planning; and veterinary care of many individual animal problems presently “treated” by farmers; would greatly improve animal welfare. Published studies have highlighted that treatments for lame sheep are not implemented early enough with many farmers delaying treatment for weeks; and sometimes even months; which adversely affects prognosis. Disease and welfare concerns as a consequence of sheep ectoparasites could be greatly reduced if farmers applied proven control strategies detailed in either veterinary flock health plans or advice available from expert veterinary websites. Recent studies have concluded that there is also an urgent need for veterinarians to better manage pain in livestock. Where proven treatments are available; such as blockage of pain arising from ovine obstetrical problems by combined low extradural injection of lignocaine and xylazine; these are seldom requested by farmers because the technique is a veterinary procedure and incurs a professional fee which highlights many farmers’ focus on economics rather than individual animal welfare.