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Economic losses due to dystocia or neonatal death as well as animal welfare and ethical concerns demand a reliable prediction of parturition with the aim to improve survival of the dam and her offspring. In this review, estimation of gestational age by ultrasound and prediction of parturition based on clinical signs, behaviour changes and changes in body temperature, composition of mammary gland secretions as well as hormonal changes are discussed in comparison between horses and cattle. Based on the physiological changes associated with the end of gestation and onset of labor, several systems and methods to predict parturition in horses and cattle have been developed. Physiological differences related to breed, maternal age and parity, pathological changes due to intrauterine growth retardation, placental problems or general illness of the dam but also housing and management systems bias a reliable prediction of parturition. This may be acceptable in cattle as long as birth alarm systems give satisfying results at herd level. The situation is different in the horse where the economic and emotional value of an individual mare and her foal usually reaches different dimensions than in cows. The possibilities for prediction of parturition can thus be discussed together, the consequences, however, may differ considerably between the two species., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Feed intake and time spent eating at the feed bunk are important predictors of dairy cows' productivity and animal welfare, and deviations from normal eating behavior may indicate subclinical or clinical disease. In the current study, we developed a random forests algorithm to predict dairy cows' daily eating time (of a total mixed ration from a common feed bunk) using data from a 3-dimensional accelerometer and a radiofrequency identification (RFID) prototype device (logger) mounted on a neck collar. Models were trained on continuous focal animal observations from a total of 24 video recordings of 18 dairy cows at the Danish Cattle Research Centre (Foulum, Tjele, Denmark). Each session lasted from 21 to 48 h. The models included both the present time signal and observations several seconds back in time (lag window). These time-lagged signals were included with the purpose of capturing changes over time. Because of the high costs of installing an RFID antenna in the feed bunk, we also investigated a model based solely on 3-dimensional accelerometer data. Furthermore, to address the trade-off between prediction accuracy and reduced model complexity and its implications for battery longevity, we investigated the importance of including observations back in time using lag window sizes between 8 and 128 s. Performance was evaluated by internal leave-one-cow-out cross-validation. The results indicated that we obtained accurate predictions of daily eating time. For the most complex model (a lag window size of 128 s), the median of the balanced accuracy was 0.95 (interquartile interval: 0.93 to 0.96), and the median daily eating time deviation was 7 min 37 s (interquartile interval: -6 to 15 min). The median of the average daily eating time during sessions was 3 h 41 min with an interquartile interval of 2 h 56 min to 4 h 16 min. Exclusion of RFID data resulted in a considerable decrease in prediction accuracy, mainly due to a decreased sensitivity of locating the cow at the feed bunk (median balanced accuracy of 0.87 at a lag window size of 128 s). In contrast, prediction accuracy only slightly decreased with decreasing lag window size (median balanced accuracy of 0.94 at a lag window size of 8 s). We suggest a lag window size of 64 s for further development of the prototype logger. The methodology presented in this paper may be relevant for future automatic recordings of eating behavior in commercial dairy herds., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Background: Cardiac output, stroke volume, and measurement of other hemodynamic parameters can be useful in the management of critical patients. Given the broad size disparity of veterinary patients, the raw values can vary widely. Their indexed values, however, allow for quick assessment of hemodynamic status and a more standardized target setting by the veterinary care team. Monitors such as lithium dilution cardiac output (LiDCO) and pulse contour cardiac output (PICCO) can display and record the data using indexed values as long as the correct body surface area (BSA) is used. In people, the BSA is calculated using the DuBois formula by entering the patient's weight and height; however, it does not apply to animals because the equivalent relationship is not represented by this formula. Given that the hemodynamic monitors are manufactured for use in human patients, the calculations need to the adapted for veterinary use. As such, the Dubois formula has been rearranged to calculate an assumed height to be entered in the monitor software along with the patient's weight. Once the information is entered, a correct BSA will be calculated by the monitor, and indexed data will be readily available for analysis., Key Findings: Tables with the calculated heights for dogs and cats were generated. The weights and calculated heights were computed into the LiDCO and PICCO monitors for verification, and the correct BSAs were displayed as a result., Significance: The information supplied here allows clinicians and researchers to quickly input patient data into the hemodynamic monitor and obtain indexed data. Indexed data facilitates advanced hemodynamic monitoring by standardizing targets (goal-directed therapy) and allowing for quicker comparison between patients. The table could be used with any monitor that utilizes the DuBois formula for BSA calculation, but the resulting BSA should be validated before proceeding with hemodynamic monitoring., (© Veterinary Emergency and Critical Care Society 2020.)

Worldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to change in the hours prior to parturition, for example, less time ruminating and eating and increased activity level and tail-raise events. These behaviours can be monitored non-invasively using animal-mounted sensors. Thus, behavioural traits are ideal variables for the prediction of calving. This study explored the potential of two sensor technologies for their capabilities in predicting when calf expulsion should be expected. Two trials were conducted at separate locations: (i) beef cows (n = 144) and (ii) dairy cows (n = 110). Two sensors were deployed on each cow: (1) Afimilk Silent Herdsman (SHM) collars monitoring time spent ruminating (RUM), eating (EAT) and the relative activity level (ACT) of the cow, and (2) tail-mounted Axivity accelerometers to detect tail-raise events (TAIL). The exact time the calf was expelled from the cow was determined by viewing closed-circuit television camera footage. Machine learning random forest algorithms were developed to predict when calf expulsion should be expected using single-sensor variables and by integrating multiple-sensor data-streams. The performance of the models was tested using the Matthew's correlation coefficient (MCC), the area under the curve, and the sensitivity and specificity of predictions. The TAIL model was slightly better at predicting calving within a 5-h window for beef cows (MCC = 0.31) than for dairy cows (MCC = 0.29). The TAIL + RUM + EAT models were equally as good at predicting calving within a 5-h window for beef and dairy cows (MCC = 0.32 for both models). Combining data-streams from SHM and tail sensors did not substantially improve model performance over tail sensors alone; therefore, hour-by-hour algorithms for the prediction of time of calf expulsion were developed using tail sensor data. Optimal classification occurred at 2 h prior to calving for both beef (MCC = 0.29) and dairy cows (MCC = 0.25). This study showed that tail sensors alone are adequate for the prediction of parturition and that the optimal time for prediction is 2 h before expulsion of the calf.

Objective: To assess agreement between oscillometric noninvasive blood pressure (NIBP) measurements using LifeWindow monitors (LW9xVet and LW6000V) and invasive blood pressure (IBP). To assess the agreement of NIBP readings using a ratio of cuff width to mid-cannon circumference of 25% and 40%., Study Design: Prospective, randomized clinical study., Animals: A total of 43 adult horses undergoing general anesthesia in dorsal recumbency for different procedures., Methods: Anesthetic protocols varied according to clinician preference. IBP measurement was achieved after cannulation of the facial artery and connection to an appropriately positioned transducer connected to one of two LifeWindow multiparameter monitors (models: LW6000V and LW9xVet). Accuracy of monitors was checked daily using a mercury manometer. For each horse, NIBP was measured with two cuff widths (corresponding to 25% or 40% of mid-cannon bone circumference), both connected to the same monitor, and six paired IBP/NIBP readings were recorded (at least 3 minutes between readings). NIBP values were corrected to the relative level of the xiphoid process. A Bland-Altman analysis for repeated measures was used to assess bias (NIBP-IBP) and limits of agreement (LOAs)., Results: The 40% cuff width systolic arterial pressure [SAP; bias 7.9 mmHg, LOA -26.6 to 42.3; mean arterial pressure (MAP): bias 4.9 mmHg, LOA -28.2 to 38.0; diastolic arterial pressure (DAP): bias 4.2 mmHg, LOA -31.4 to 39.7)] performed better than the 25% cuff width (SAP: bias 26.4 mmHg, LOA -21.0 to 73.9; MAP: bias 15.7 mmHg, LOA -23.8 to 55.2; DAP: bias 10.9 mmHg, LOA -33.2 to 54.9)., Conclusions and Clinical Relevance: Using the LifeWindow multiparameter monitor in anesthetized horses, the 40% cuff width provided better agreement with IBP; however, both cuff sizes and both monitor models failed to meet American College of Veterinary Internal Medicine Consensus Statement Guidelines., (Copyright © 2020 Association of Veterinary Anaesthetists and American College of Veterinary Anesthesia and Analgesia. Published by Elsevier Ltd. All rights reserved.)

This review deals with the prospects and achievements of individual dairy cow management (IDCM) and the obstacles and difficulties encountered in attempts to successfully apply IDCM into routine dairy management. All aspects of dairy farm management, health, reproduction, nutrition and welfare are discussed in relation to IDCM. In addition, new IDCM R&D goals in these management fields are suggested, with practical steps to achieve them. The development of management technologies is spurred by the availability of off-the-shelf sensors and expanded recording capacity, data storage, and computing capabilities, as well as by demands for sustainable dairy production and improved animal wellbeing at a time of increasing herd size and milk production per cow. Management technologies are sought that would enable the full expression of genetic and physiological potential of each cow in the herd, to achieve the dairy operation's economic goals whilst optimizing the animal's wellbeing. Results and conclusions from the literature, as well as practical experience supported by published and unpublished data are analyzed and discussed. The object of these efforts is to identify knowledge and management routine gaps in the practical dairy operation, in order to point out directions and improvements for successful implementation of IDCM in the dairy cows' health, reproduction, nutrition and wellbeing.

The objective of the present study was to validate the accuracy of algorithms, implemented in the currently available RumiWatch Converter (RWC) version V0.7.4.5 of the RumiWatch System (RWS), for the classification of behavioural characteristics from jaw and head movements which are monitored by a noseband halter comprising a pressure sensor and a triaxial accelerometer. The accurate classification of behavioural characteristics in different time resolutions is critical for the usage of the RWS for scientific and practical purposes as chewing behaviour provides essential indicators for the assessment of diet adequacy in dairy cows. To validate the RWC V0.7.4.5 classification accuracy for behavioural characteristics of rumination, eating, drinking, other activity and ruminating chews per bolus by direct observation as reference method, 14 dairy cows participated in the trial. Concordance between the consolidated 1-min and 1-h classification results was assessed. The RWC V0.7.4.5 classified only rumination and ruminating chews per bolus precisely, whereas an algorithm optimisation for the classification of eating, drinking and other activity is required. Additionally, classification results from the 1-min and 1-h time summaries were not in agreement with each other except for rumination.

The objective of the study was to develop a grazing algorithm for an ear tag-based accelerometer system (Smartbow GmbH, Weibern, Austria) and to validate the grazing algorithm with data from a noseband sensor. The ear tag has an acceleration sensor, a radio chip, and temperature sensor for calibration and it can monitor rumination and detect estrus and localization. To validate the ear tag, a noseband sensor (RumiWatch, Itin and Hoch GmbH, Liestal, Switzerland) was used. The noseband sensor detects pressure and acceleration patterns, and, with a software program specific to the noseband, pressure and acceleration patterns are used to classify data into eating, ruminating, drinking, and other activities. The study was conducted at the University of Minnesota West Central Research and Outreach Center (Morris, MN) and at Teagasc Animal and Grassland Research and Innovation Centre (Moorepark, Fermoy, Co. Cork, Ireland). During May and June 2017, observational data from Minnesota and Ireland were used to develop the grazing algorithm. During September 2018, data were collected by the ear tag and noseband sensor from 12 crossbred cows in Minnesota for a total of 248 h and from 9 Holstein-Friesian cows in Ireland for a total of 248 h. A 2-sided t-test was used to compare the percentage of grazing and nongrazing time recorded by the ear tag and the noseband sensor. Pearson correlations and concordance correlation coefficients (CCC) were used to evaluate associations between the ear tag and noseband sensor. The percentage of total grazing time recorded by the ear tag and by the noseband sensor was 37.0% [95% confidence interval (CI): 32.1 to 42.0] and 40.5% (95% CI: 35.5 to 45.6), respectively, in Minnesota, and 35.4% (95% CI: 30.6 to 40.2) and 36.9% (95% CI: 32.1 to 41.8), respectively, in Ireland. The ear tag and noseband sensor agreed strongly for monitoring grazing in Minnesota (r = 0.96; 95% CI: 0.94 to 0.97, CCC = 0.95) and in Ireland (r = 0.92; 95% CI: 0.90 to 0.94, CCC = 0.92). The results suggest that there is potential for the ear tag to be used on pasture-based dairy farms to support management decision-making., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

The recent trend in electrocardiogram (ECG) device development is towards wireless body sensors applied for patient monitoring. The ultimate goal is to develop a multi-functional body sensor that will provide synchronized vital bio-signs of the monitored user. In this paper, we present an ECG sensor for long-term monitoring, which measures the surface potential difference between proximal electrodes near the heart, called differential ECG lead or differential lead, in short. The sensor has been certified as a class IIa medical device and is available on the market under the trademark Savvy ECG. An improvement from the user's perspective-immediate access to the measured data-is also implemented into the design. With appropriate placement of the device on the chest, a very clear distinction of all electrocardiographic waves can be achieved, allowing for ECG recording of high quality, sufficient for medical analysis. Experimental results that elucidate the measurements from a differential lead regarding sensors' position, the impact of artifacts, and potential diagnostic value, are shown. We demonstrate the sensors' potential by presenting results from its various areas of application: medicine, sports, veterinary, and some new fields of investigation, like hearth rate variability biofeedback assessment and biometric authentication.

The objective of the present study was to assess the effectiveness of an intravaginal thermometer in the field prediction of the second stage of labor and to determine its impact on the health of dams and newborn calves. Holstein cows (n = 241) were randomly selected about 5 (mean ± SD: 4.7 ± 2.0) days before the expected date of calving and the thermometer was inserted into the vagina. Another 113 cattle served as controls. There was no false alarm during the experiment. The risk of dystocia (Score >1) was 1.9 times higher, the prevalence of stillbirth was 19.8 times higher, the risk of retained fetal membranes (RFM) was 2.8 times higher and the risk of clinical metritis was 10.5 times higher in the control group than in the experimental group. The prevalence of stillbirth was 7 times higher in cows with dystocia compared to cows with eutocia. The presence of dystocia and stillbirth increased the risk of RFM 4 and 5 times, respectively. The occurrence of RFM increased the risk of development of clinical metritis with a 22 times higher odds. The results indicate that the use of calving alert systems not only facilitates controlling the time of parturition and providing prompt and appropriate calving assistance but also decreases the number of dystocia cases and improves reproductive efficiency, postpartum health of the dam and newborn calf survival., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Risk for complications and even death is inherent to anesthesia. However, the use of guidelines, checklists, and training can decrease the risk of anesthesia-related adverse events. These tools should be used not only during the time the patient is unconscious but also before and after this phase. The framework for safe anesthesia delivered as a continuum of care from home to hospital and back to home is presented in these guidelines. The critical importance of client communication and staff training have been highlighted. The role of perioperative analgesia, anxiolytics, and proper handling of fractious/fearful/aggressive patients as components of anesthetic safety are stressed. Anesthesia equipment selection and care is detailed. The objective of these guidelines is to make the anesthesia period as safe as possible for dogs and cats while providing a practical framework for delivering anesthesia care. To meet this goal, tables, algorithms, figures, and "tip" boxes with critical information are included in the manuscript and an in-depth online resource center is available at aaha.org/anesthesia.

The non-invasive monitoring of physiological stress can provide conservation and wildlife managers with an invaluable tool for assessing animal welfare and psychological health of captive and free-ranging populations. A significant decrease in free-ranging primate populations globally and an increase in captive-housed primates have led to a need to monitor the stress and general welfare of these animals. We examined the suitability of three enzyme immunoassays (EIAs) for monitoring stress-related physiological responses in the samango monkey, Cercopithecus albogularis erythrarchus. We conducted an adrenocorticotropic hormone (ACTH) challenge on a male and female at the National Zoological Garden, Pretoria, South Africa. Individual faecal samples were collected 8 days pre- and post-ACTH administration and subsequently analysed for faecal glucocorticoid metabolite (fGCM) concentrations. During the study, biological stressors occurred for both the male and female. Two of the three EIAs tested (11-oxoetiocholanolone I and II) were able to reliably monitor fGCM alterations throughout the study period in both sexes. The 11-oxoetiocholanolone I EIA, however, had the lowest mean deviation from the calculated baseline value and was thus chosen as the preferred assay. Both the physiological activation of the stress response and the biological response to a stressor could be monitored with the chosen assay. The successful establishment of a reliable, non-invasive method for monitoring adrenocortical activity in C. albogularis erythrarchus will now allow conservationists, scientific researchers and wildlife managers to evaluate the level of stress experienced, and general welfare, by animals in captivity as well as free-ranging populations.

Wearable precision dairy monitoring (PDM) technologies currently used to detect estrus may provide insight into disease detection. However, the incorporation of PDM into farm management and its perceived usefulness for dairy producers have not been explored. As the targeted end users of these products, information is needed on how producers use generated disease alerts as well as barriers to adoption and usefulness. The objective of this research was to assess the perceived usefulness producers attributed to alerts from a daily generated alert list designed to identify sick or injured cows or cows that experienced a major management change. Data from 1,171 cows on 4 commercial farms in Kentucky were collected from October 2015 to October 2016. Each cow was equipped with 2 PDM technologies: a leg tag (measuring activity in steps/d and lying time in h/d) and a neck collar (measuring eating time in h/d). Alerts were generated based on an individual cow's decrease of ≥30% in activity, lying, and eating time compared with each cow's 10-d moving mean. Producers sorted alerts into 3 overall categories: (1) the cow alert was perceived to be true and the cow was visually checked, (2) the cow alert was perceived to be true, but the cow was not visually checked, and (3) the cow alert behavior change was doubted by the producer and the cow was not visually checked. Further subdivisions were also provided to explain the choice for an overall category. Over the year, 24,012 cow alerts were generated (eating time, n = 9,543; lying time, n = 9,777; activity, n = 1,590; or a combination of behaviors, n = 3,102). Only 8% of the alerts were doubted by the producer. Although 55% of alerts were perceived to be true, producers visually assessed cows based on only 21% of the alerts with a large variation between farms (2 to 45% of the alerts visually assessed). Producers were more likely to completely ignore alerts over time. Producers were more likely to perceive cow alerts to be true and visually check cows when ≤20 alerts occurred per day, cows were fresh or in early lactation, alerts occurred during the work week, or when cow alerts were for eating time, activity, or a combination of multiple behaviors. Behavioral disease alerts must be improved and correspond to an actionable change for producers to use them. Incorporating herd management software, creating and managing alerts by lactation stage, and focusing on behaviors producers already find useful could improve future alert utilization., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Measuring vital signs is central to medical practice, but they are difficult to monitor in awake laboratory animals. We examined the feasibility of a noninvasive device for telemetric assessment of respiration rate, heart rate, temperature and movement in pigs. Awake piglets were monitored continuously for 31 h (interquartile range, 7) before ( n = 4) and after ( n = 3) surgery. Data quality was sufficient for determination of all parameters. We conclude that continuous, noninvasive monitor- ing of pigs is possible by using the evaluated device.

Objective: To compare a Parasympathetic Tone Activity (PTA) monitor with cardiovascular changes in invasive mean arterial pressure (IMAP) and heart rate (HR) when evaluating the response to nociceptive stimuli in anaesthetized dogs., Study Design: Prospective experimental study., Animals: A group of nine (seven male and two female) adult Beagle dogs weighing 13.4 ± 1.5 kg (mean ± standard deviation)., Methods: Anaesthesia was induced with propofol and maintained with sevoflurane in oxygen. Electrical stimuli of different nociceptive intensities were applied for 30 seconds. Stimuli were classified in each patient according to the response obtained (relevant change ≥ 20%) as low (no response), medium (PTA only) or high (PTA and IMAP/HR). Immediate and averaged values of PTA, IMAP and HR were recorded every second from 60 seconds before to 120 seconds after application of the nociceptive stimulus. Time to nociceptive response and peak response were evaluated with analysis of variance and t test., Results: Immediate PTA baseline values did not differ significantly before application of the low, medium and high stimuli (73 ± 15, p = 0.966). Immediate PTA response was observed with the medium stimulus at 33 ± 7 seconds with a maximum decrease of 57 ± 13% at 69 ± 5 seconds. With the high stimulus, the immediate PTA response was of a similar magnitude to the medium stimulus with a response at 28 ± 7 seconds (p = 0.221) and a maximum decrease of 68 ± 15% (p = 0.115) at 72 ± 7 seconds (p = 0.436). The cardiovascular change occurred (22 ± 8 seconds) prior to the immediate PTA response (p = 0.032)., Conclusions and Clinical Relevance: The PTA monitor detected nociceptive stimuli at lower intensities than those eliciting cardiovascular changes. However, nociceptive stimuli of higher intensities provoked cardiovascular changes that occurred before a PTA response was observed., (Copyright © 2019 Association of Veterinary Anaesthetists and American College of Veterinary Anesthesia and Analgesia. Published by Elsevier Ltd. All rights reserved.)

Cold-stress syndrome (CSS) is one of the leading natural threats to free-ranging Florida manatees ( Trichechus manatus latirostris ). Cold water exposure below the species' acceptable physiologic range is a frequent occurrence for manatees during cold weather months causing CSS-induced systemic illness and significant annual mortality. Although CSS is a commonly presented condition at manatee rehabilitation facilities, the core body temperatures in CSS manatees are currently unknown due to the lack of clinically applicable and accurate temperature measurement methodologies. Our objective was to establish a clinically applicable measurement methodology of core body temperature in manatees. A novel, minimally invasive temperature technique to obtain esophageal temperature by placing a temperature sensor through an oro-gastric tube was compared to current oral and nasal methods in 20 clinically healthy manatees. Results identified the esophageal measurement as the best performing and most precise temperature methodology. The superior performance of esophageal temperature measurements differed significantly from both nasal and oral measurements, while nasal and oral measurements did not differ when compared with each other. The esophageal measurements were consistent with manatee core body temperature, facilitating generation of a reference interval for core body temperature in healthy manatees (35.0-35.8 C). Four CSS medical cases were evaluated with the newly validated esophageal temperature method, facilitating diagnosis of hypothermia. The application of this temperature measurement technique to CSS manatees in field or rehabilitation settings will help in understanding CSS pathophysiology, improve medical assessments during rehabilitation, and contribute to conservation efforts.

Background: A factory-calibrated flash glucose monitoring system (FGMS; FreeStyle Libre) recently was evaluated in dogs with uncomplicated diabetes mellitus. It is not known if this system is reliable during diabetic ketoacidosis (DKA)., Objectives: To assess the performance of the FGMS in dogs with DKA and to determine the effect of severity of ketosis and acidosis, lactate concentration, body condition score (BCS), and time wearing the sensor on the accuracy of the device., Animals: Fourteen client-owned dogs with DKA., Methods: The interstitial glucose (IG) measurements were compared with blood glucose (BG) measurements obtained using a validated portable glucometer. The influence of changes in metabolic variables (β-hydroxybutyrate, pH, bicarbonate, and lactate) and the effect of BCS and time wearing on sensor performance were evaluated. Accuracy was determined by fulfillment of ISO15197:2013 criteria., Results: Metabolic variables, BCS, and time wearing were not associated with the accuracy of the sensor. Good agreement between IG measurements and BG was obtained both before and after DKA resolution (r = .88 and r = .93, respectively). Analytical accuracy was not achieved, whereas clinical accuracy was demonstrated with 100% and 99.6% of results in zones A + B of the Parkes consensus error grid analysis before and after DKA resolution, respectively., Conclusions and Clinical Importance: Changes in metabolic variables, BCS, and time wearing do not seem to affect agreement between IG and BG. Despite not fulfilling the ISO requirements, the FGMS provides clinically accurate estimates of BG in dogs with DKA., (© 2019 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.)

Blubber has been proposed as a possible alternative to blood in the assessment of endocrine physiology in marine mammals because it can be collected via remote biopsy, which removes some of the confounding variables and logistical constraints associated with blood collection. To date, few studies have directly assessed the relationships between circulating versus blubber steroid hormone profiles in marine mammals, and these studies have been limited to a small subset of steroid hormones, which collectively limit the current utility of blubber steroid hormone measurements. In this study, we used liquid-chromatography tandem-mass spectrometry (LC-MS/MS) to screen for 16 steroid hormones in matched blood and blubber samples from free-ranging common bottlenose dolphins (Tursiops truncatus). Seven steroid hormones were detected and quantified, including two progestogens, two androgens, and three corticosteroids. Using principal components analysis (PCA), we explored relationships between hormones in both matrices and three physiological states: sexual maturity, pregnancy, and acute stress response. Plasma and blubber testosterone and its precursors, 17-hydroxyprogesterone and androstenedione, loaded to the first principal component (PC1), and PC1 scores were higher in mature males. Plasma and blubber progesterone loaded to PC2, and pregnant/probable pregnant females had significantly higher PC2 scores. Pregnant females also had higher PC1 scores than other females, suggesting differences in androgen profiles between these groups. There was disagreement between plasma and blubber corticosteroid profiles, as indicated by their loading to different PCs; plasma corticosteroids loaded to PC3 and blubber corticosteroids to PC4. PC3 scores were significantly predicted by elapsed time to blood collection (i.e., time between initiating the capture process and blood collection), while elapsed time to blubber collection significantly predicted PC4 scores, indicating that corticosteroid profiles shift in both tissues during acute stress. Corticosteroid profiles were not related to demographic group, site-month, body mass index, water temperature, or time spent outside of the water on the processing boat. Overall, these results demonstrate that blubber steroid hormone profiles reflect changes in endocrine function that occur over broad temporal scales., (Copyright © 2019 Elsevier Inc. All rights reserved.)

This study evaluated the monitoring methods in asymptomatic dogs with high serum cystatin C (Cys-C) concentrations. Ten dogs with high serum Cys-C were divided into two groups based on the owner's choice; one receiving clinical pathology-based monitoring at an animal hospital specialised in chronic kidney disease, and the other receiving symptom-based monitoring at home, partly because they showed no clinical symptoms. The dogs that received the clinical pathology-based monitoring led to an early treatment intervention, resulted in a longer survival period than dogs received the symptom-based monitoring (P<0.05). It became clear that early treatment intervention by clinical pathology-based monitoring extends the renal survival period even in asymptomatic dogs with increased serum Cys-C concentrations.

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 Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The use of radio frequency identification (RFID) technology is common in animal-monitoring applications in the wild and in zoological and agricultural settings. RFID is used to track animals and to collect information about movements and other behaviors, as well as to automate or improve husbandry. Disney's Animal Kingdom® uses passive RFID technology to monitor nest usage by a breeding colony of northern carmine bee-eaters. We implemented RFID technologies in various equipment configurations, initially deploying low-frequency (LF) 125 kHz RFID and later changing to high-frequency (HF) 13.56 MHz RFID technology, to monitor breeding behavior in the flock. We installed antennas connected to RFID readers at the entrances of nest tunnels to detect RFID transponders attached to leg bands as birds entered and exited tunnels. Both LF-RFID and HF-RFID systems allowed the characterization of nest visitation, including the timing of nest activity, breeding pair formation, identification of egg-laying females, participation by nonresidents, and detection of nest disruptions. However, we collected a substantially larger volume of data using the increased bandwidth and polling speed inherent with HF-RFID, which permitted tag capture of multiple birds simultaneously and resulted in fewer missed nest visits in comparison to LF-RFID. Herein, we describe the evolution of the RFID setups used to monitor nest usage for more than 7 years, the types of data that can be gained using RFID at nests, and how we used these data to gain insights into carmine bee-eater breeding behavior and improve husbandry., (© 2019 Wiley Periodicals, Inc.)

Automated monitoring of fertility in dairy cows using milk progesterone is based on the accurate and timely identification of luteolysis. In this way, well-adapted insemination advice can be provided to the farmer to further optimize fertility management. To properly evaluate and compare the performance of new and existing data-processing algorithms, a test data set of progesterone time-series that fully covers the desired variability in progesterone profiles is needed. Further, the data should be measured with a high frequency to allow rapid onset events, such as luteolysis, to be precisely determined. Collecting this type of data would require a lot of time, effort, and budget. In the absence of such data, an alternative was developed using simulated progesterone profiles for multiple cows and lactations, in which the different fertility statuses were represented. To these, relevant variability in terms of cycle characteristics and measurement error was added, resulting in a large cost-efficient data set of well-controlled but highly variable and farm-representative profiles. Besides the progesterone profiles, information on (the timing of) luteolysis was extracted from the modeling approach and used as a reference for the evaluation and comparison of the algorithms. In this study, 2 progesterone monitoring tools were compared: a multiprocess Kalman filter combined with a fixed threshold on the smoothed progesterone values to detect luteolysis, and a progesterone monitoring algorithm using synergistic control, PMASC, which uses a mathematical model based on the luteal dynamics and a statistical control chart to detect luteolysis. The timing of the alerts and the robustness against missing values of both algorithms were investigated using 2 different sampling schemes: one sample per cow every 8 h versus 1 sample per day. The alerts for luteolysis of the PMASC algorithm were on average 20 h earlier compared with the ones of the multiprocess Kalman filter, and their timing was less sensitive to missing values. This was shown by the fact that, when 1 sample per day was used, the Kalman filter gave its alerts on average 24 h later, and the variability in timing of the alerts compared with simulated luteolysis increased with 22%. Accordingly, we postulate that implementation of the PMASC system could improve the consistency of luteolysis detection on farm and lower the analysis costs compared with the current state of the art., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Background: Accelerometry is an accepted means of quantifying human physical activity. Quantitative physical activity tracking could be beneficial for studies into equine health and disease prevention, for example in relation to obesity management., Objectives: Validate accelerometer use in grazing horses, determine between-day repeatability, and assess the effects of pasture size on time budget (i.e. duration in each activity category)., Study Design: Proof of concept., Methods: Accelerometers (ActiGraph) were positioned at the poll. Horses underwent 5 min of observed activity in three categories: standing, grazing and ambulating. Receiver-operating characteristic curve analysis, used on ten second data epochs, calculated cut points between the activities. A 20-day study was then undertaken on 6 horses at pasture. Time in each category (per day) was deduced; a Mann Whitney U test was performed to compare standard vs. small paddock and day vs. night turn out., Results: Cut-off values with the optimum sensitivity (94.7-97.7%) and specificity (94.7-96.8%) were found to be <127.6 counts for standing, 127.6-702.7 counts for grazing and >702.7 counts for ambulating. Repeatability was analysed descriptively: Median (IQR) of the between-day difference in minutes standing, grazing and ambulating were 46.9 (21.3-87.9), 77.3 (40.2-124.5) and 15.6 (6.8-40.2) respectively. Median times standing and ambulating were significantly different between standard and small paddocks: standing: 8.7 vs. 10.3 h (P<0.001); ambulating: 55.7 vs. 39.6 min (P = 0.002). There was no significant difference in the median time spent grazing. There were significant differences between day and night: standing: 32.95% vs. 50.97% (P = 0.001), grazing: 60.81% vs. 46.77% (P<0.001) and ambulating: 4.57% vs. 2.40% (P<0.001)., Main Limitations: Small sample size and lack of cross-validation of cut-off points on independent, 'unseen' data., Conclusions: Accelerometry can differentiate standing, grazing and ambulating in horses. Our proof-of-concept study demonstrates modifying pasture size influences activity budgets; opening avenues into studying obesity management., (© 2019 EVJ Ltd.)

Introduction: Thermographic examination of 157 German Holstein heifer calves was performed to investigate the feasibility of this technique for on-farm recording of surface temperature of the head and to examine potential factors that affect the recordings. Baseline values were obtained from six defined locations on the head including both eyes, both horn buds, the muzzle and the mucous membrane of the muzzle using a high-end thermographic camera (ThermoPro TP8, Firma DIAS Infrared GmbH). Evaluation of the influence of various factors on thermographic measurements showed that ambient temperature had the largest effect on surface temperature of the head (regression coefficient, 0.10 to 0.32, p ≤ 0.01) whereas humidity had no effect (in t-test p ≥ 0.33 over all locations). There was a no correlation between rectal temperature and surface temperature (rp ≤ 0.05). The surface temperature decreased with increasing age of the calves (regression coefficient, - 0.42 to - 0.14, p ≤ 0.01). The agreement between double readings made shortly after one another was excellent at all locations (r ≥ 0.95). The emission of infrared energy varied among different locations; the most infrared energy was emitted by the eyes and the least by the muzzle. Paired locations (eyes and horn buds) had symmetric emission patterns of infrared energy. Measuring the surface temperature of the head of calves in their normal barn environment using a standardised protocol was feasible and thus could potentially be used for monitoring calves under field conditions.

Radio frequency identification (RFID) technology offers a real-time solution to monitor behavioral responses of individual animals to various stimuli, which provides crucial implications on farm management and animal well-being. The objectives of this study were to (1) develop and describe an ultra-high frequency radio frequency identification (UHF-RFID) system for continuously monitoring feeding and drinking behaviors of individual broilers in group settings; and (2) validate the performance of the UHF-RFID system against video analysis in determining the instantaneous bird number (IBN) and time spent (TS) at feeder and drinker. The UHF-RFID system consisted of cable-tie tags, antennas, a reader and a data acquisition (DAQ) system. The antennas generated electromagnetic fields where tags were detected and registered by the DAQ system. Electromagnetic fields of the antennas were modified to cover areas of concern (i.e. tube feeders and nipple drinkers) through a series of system evaluations and customizations including tag sensitivity test, power adjustment, radio wave shielding, and assessment of interference by add-ons (e.g. plastic wraps for protecting antennas and an empty carton box for zoning out broilers) and feed/feeder. System validation was performed in two experimental rooms, each with 60 tagged broilers. The results showed that the max reading distances of tags with an identical manufacturer's specification were markedly different, indicating large variations in sensitivity among the tags. Desired electromagnetic fields could be achieved by adjusting the power supplied to antennas and by partially shielding antennas with customized stainless steel sheets. The protection materials and fully loaded feeder had little effect on electromagnetic fields of the antennas. The accuracies of the UHF-RFID system for determining IBN and TS were, respectively, 92.5±4.2% and 99.0±1.2% by the feeder antennas and 94.7±4.2% and 93.7±6.9% by the drinker antennas. It is concluded that the UHF-RIFD system can accurately detect and record feeding and drinking behaviors of individual broilers in group settings and thus is a useful tool for investigating impacts of resource allocations and management practices on these behaviors.

The commercially available collar device MooMonitor+ was evaluated with regards to accuracy and application potential for measuring grazing behavior. These automated measurements are crucial as cows feed intake behavior at pasture is an important parameter of animal performance, health and welfare as well as being an indicator of feed availability. Compared to laborious and time-consuming visual observation, the continuous and automated measurement of grazing behavior may support and improve the grazing management of dairy cows on pasture. Therefore, there were two experiments as well as a literature analysis conducted to evaluate the MooMonitor+ under grazing conditions. The first experiment compared the automated measurement of the sensor against visual observation. In a second experiment, the MooMonitor+ was compared to a noseband sensor (RumiWatch), which also allows continuous measurement of grazing behavior. The first experiment on n = 12 cows revealed that the automated sensor MooMonitor+ and visual observation were highly correlated as indicated by the Spearman's rank correlation coefficient (rs) = 0.94 and concordance correlation coefficient (CCC) = 0.97 for grazing time. An rs-value of 0.97 and CCC = 0.98 was observed for rumination time. In a second experiment with n = 12 cows over 24-h periods, a high correlation between the MooMonitor+ and the RumiWatch was observed for grazing time as indicated by an rs-value of 0.91 and a CCC-value of 0.97. Similarly, a high correlation was observed for rumination time with an rs-value of 0.96 and a CCC-value of 0.99. While a higher level of agreement between the MooMonitor+ and both visual observation and RumiWatch was observed for rumination time compared to grazing time, the overall results showed a high level of accuracy of the collar device in measuring grazing and rumination times. Therefore, the collar device can be applied to monitor cow behavior at pasture on farms. With regards to the application potential of the collar device, it may not only be used on commercial farms but can also be applied to research questions when a data resolution of 15 min is sufficient. Thus, at farm level, the farmer can get an accurate and continuous measurement of grazing behavior of each individual cow and may then use those data for decision-making to optimize the animal management.

Background: Famotidine is sometimes administered as a continuous rate infusion (CRI) to treat gastrointestinal ulceration in critically ill dogs. However, clinical studies have not evaluated the efficacy of a famotidine CRI in dogs., Hypothesis/objectives: To evaluate the efficacy of famotidine at raising intragastric pH when it is administered as a CRI in dogs. We hypothesized that CRI treatment with famotidine would meet clinical goals for raising intragastric pH ≥3 and 4., Animals: Nine healthy Beagle dogs., Methods: Randomized 2-way crossover. All dogs received 1.0 mg/kg IV q12h famotidine or CRI famotidine at 1.0 mg/kg IV loading dose and 8.0 mg/kg/d for 3 consecutive days. Beginning on day 0 of treatment, intragastric pH monitoring was used to continuously record intragastric pH. Mean percentage times (MPTs) for which intragastric pH was ≥3 and ≥4 were compared between groups using analysis of variance., Results: There was a statistically significant difference (P < .05) in MPT ≥3 and ≥4 between the CRI and IV q12h groups on all treatment days. On days 1, 2, and 3, the MPTs ± SD for which pH was ≥3 were 92.1 ± 8.5, 96.3 ± 6.2, and 90.0 ± 15.7 for the CRI treatment group and 49.3 ± 27.3, 42.2 ± 19.6, and 45.8 ± 10.1, respectively, for the twice-daily group., Conclusions and Clinical Importance: These results suggest that a famotidine CRI, but not standard doses of famotidine, achieves the clinical goals established in people to promote healing of gastric tissue injury and offers an alternative to intravenous treatment with proton pump inhibitors in dogs., (© 2019 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.)

Analysing behaviours can provide insight into the health and overall well-being of dairy cows. Automatic monitoring systems using e.g., accelerometers are becoming increasingly important to accurately quantify cows' behaviours as the herd size increases. The aim of this study is to automatically classify cows' behaviours by comparing leg- and neck-mounted accelerometers, and to study the effect of the sampling rate and the number of accelerometer axes logged on the classification performances. Lying, standing, and feeding behaviours of 16 different lactating dairy cows were logged for 6h with 3D-accelerometers. The behaviours were simultaneously recorded using visual observation and video recordings as a reference. Different features were extracted from the raw data and machine learning algorithms were used for the classification. The classification models using combined data of the neck- and the leg-mounted accelerometers have classified the three behaviours with high precision (80-99%) and sensitivity (87-99%). For the leg-mounted accelerometer, lying behaviour was classified with high precision (99%) and sensitivity (98%). Feeding was classified more accurately by the neck-mounted versus the leg-mounted accelerometer (precision 92% versus 80%; sensitivity 97% versus 88%). Standing was the most difficult behaviour to classify when only one accelerometer was used. In addition, the classification performances were not highly influenced when only X, X and Z, or Z and Y axes were used for the classification instead of three axes, especially for the neck-mounted accelerometer. Moreover, the accuracy of the models decreased with about 20% when the sampling rate was decreased from 1Hz to 0.05Hz., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

According to the cort-fitness hypothesis, glucocorticoid levels correlate negatively with fitness. However, field studies found mixed support for this hypothesis, potentially because the association between glucocorticoids and fitness might depend on prevailing environmental conditions. Based on the long-term monitoring of a natural rodent population, we tested whether individuals with elevated corticosterone levels were more likely to disappear, accounting for individual condition and among-year variation in food availability, population density and predation pressure. We used basal corticosterone levels measured at the onset of the pre-breeding season in 331 African striped mice from six generations. While basal corticosterone levels were highly repeatable within individuals, between-individual variation was large. Survival analysis revealed that disappearance risk over the pre-breeding season increased with elevated basal corticosterone levels for light but not for heavy individuals. High levels of corticosterone may be more deleterious to smaller individuals (i.e. through allostatic overload), eventually increasing their mortality risk, and disappearance would represent actual death. An alternative non-exclusive explanation could be that high levels of corticosterone selectively trigger dispersal in light individuals, and disappearance would rather reflect their departure from the population. Although environmental conditions varied considerably among generations, none of the interactions between corticosterone and environmental variables were significant. Disappearance probability was positively correlated with both predation pressure and with food availability, a factor favoring dispersal. In sum, elevated basal corticosterone levels increased disappearance in light striped mice, either directly via reduced survival prospects and/or indirectly via dispersal., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The objective of this study was to validate the CowManager SensOor ear-tag accelerometer (Agis Automatisering BV, Harmelen, the Netherlands) against visual observations of feeding, rumination, resting, and active behaviors of tiestall-housed dairy cows. Prior validation of the sensor has been published for freestall and grazing dairy herds. However, the behavioral differences that exist among these and a tiestall system necessitate additional validation. Lactating Holstein cows (n = 10) at different lactation stages and parities were included in the study. Cows were monitored both visually and with the sensor for 10 h/d for 4 consecutive days (10 cows × 10 h × 4 d = 400 h of observation total). A single trained observer classified each minute of visual observation into 1 of 13 behaviors and then summarized them into the 4 behavioral categories of eating, rumination, not active, or active. The sensor registered ear movements continuously and, based on a proprietary model, converted them into the behavioral categories. Multivariate mixed models were run to obtain covariance estimates, from which correlation coefficients were computed to assess agreement between visual observation and sensor data. The models included the percentage of time spent performing each behavior per day as the dependent variable and technology (visual observation versus sensor) and day as fixed effects. The models also included the random effects of technology and the repeated effects of technology and day. The correlation strength between visual observation and sensor data varied from poor to almost perfect by behavioral category (eating: r = 0.27; rumination: r = 0.69; eating-rumination: r = 0.83; not active: r = 0.95; and active: r = 0.89). The results suggest that the sensor can be used to accurately monitor active and not-active behaviors of tiestall-housed dairy cows. The results also suggest that although the sensor shows promise for identifying feeding behaviors in general, the independent classification of rumination and eating requires additional sensitivity., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Aims: To investigate the progression of obesity-related type 2 diabetes mellitus (T2DM) in rhesus monkeys, especially dynamic changes in insulin and glucagon., Materials and Methods: We followed a cohort of 52 rhesus monkeys for 7 years throughout the progression of obesity-related T2DM. Intravenous glucose tolerance tests were performed every 6 months to evaluate dynamic changes in glucose, insulin and glucagon levels., Results: Obesity in rhesus monkeys increased the overall mortality and T2DM morbidity. During the progression of T2DM, glucagon remained consistently elevated, while insulin initially increased in compensation but then dropped to below normal levels when the monkeys developed overt T2DM. After a glucose challenge, both the first and second phases of insulin secretion increased during the early stage of T2DM; in later stages the first phase was delayed and the second phase was diminished., Conclusion: Our findings showed that, beside the decreased insulin level, hyperglucagonaemia also plays an important role in the development of T2DM., (© 2018 John Wiley & Sons Ltd.)

Demand has been increasing recently for an automated monitoring system of animal behavior as a tool for the management of livestock animals. This study investigated the association between the behavior of dairy cattle and the acceleration data collected using three-axis neck-mounted accelerometers, as well as the feasibility of improving the precision of behavior classifications through machine learning. In total 38 Holstein dairy cows were used, and kept in four different farms. A logger was mounted to each collar to obtain acceleration data for calculating the activity level and variations. At the same time the behavior of the cattle was observed visually. Characteristic acceleration waves were recorded for eating, rumination, and lying, respectively; and the activity level and variations were significantly different among these behaviors (p < 0.01). Decision tree learning was performed on the data set from Farm A and validated its precision; which proved to be 99.2% in cross-validation, and 100% in test data sets from Farms B to D. This study showed that highly precise classifications for eating, rumination, and lying is possible by using decision tree learning to calculate the activity level and variations of cattle based on the data obtained by three-axis accelerometers mounted to a collar., (© 2019 Japanese Society of Animal Science.)

In this study, the changes of salivary stress biomarkers were contrasted with skin lesions during weaning in piglets. The stress biomarkers evaluated were cortisol (as the reflection of hypothalamic-pituitary-adrenal (HPA) axis), chromogranin A (CgA) and alpha amylase (sAA) (both as the reflection of sympathoadrenal-medullary (SAM) axis). In addition, the accumulation of skin lesions were assessed as proxy measures of aggression. One hundred and two Danbred piglets (51 female and 51 male) from primiparous and multiparous sows were studied from birth to two days post-weaning. Saliva sampling and lesion scoring were performed one day pre-weaning (-1), and one (+1) and two days post-weaning (+2). Our results show that on +1, there was a significant (P < .0001) increase in salivary cortisol, CgA and skin lesions; whereas on +2, there was a significant increase (P < .0001) in salivary CgA and skin lesions. CgA was correlated with the skin lesion score (r = 0.4; P < .0001). sAA did not significantly change at any sampling time. It can be concluded that stress associated to weaning, is associated with changes in salivary CgA and cortisol stress biomarkers and an increase in skin lesions. However, CgA shows higher correlation with skin lesions which indicates that stress due to fighting activates the SAM stress pathway. Therefore, a combination of physiological biomarkers (CgA and cortisol) and proxy of aggression (skin lesions) is preferable than the use of a single biomarker or behavioural indicator when monitoring the social stress response associated to weaning in piglets., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Monitoring variables of cardiac performance in horses is challenging owing to patient size, temperament, and anatomic peculiarities. Blood pressure is a major determinant of afterload, but it is not a reliable surrogate of cardiac performance and tissue perfusion. Cardiac output, together with arterial and venous oxygen content, provides insight as to the adequacy of delivery of blood and oxygen to the body as a whole and can be used to gauge the fluid responsiveness and cardiovascular status of the patient. Measurement of intracardiac pressures serves to assess cardiac filling pressures, myocardial performance, and vascular resistance., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The objective of this study was to determine whether data from an electronic drinking system that tracks individual animal attendance with ear tag transponders could be used to detect social competition between dairy cows at the drinker. Specifically, we sought to identify the interval between one cow leaving the drinker and another cow taking her place that most accurately identified competitive replacements (when physical contact initiated by one cow causes the other to entirely remove her head from the drinker and the initiator subsequently places her head in the same drinker). The optimal interval to accurately identify replacements at the drinker was determined using a receiver operating characteristic curve and by evaluating the sensitivity (Se), specificity (Sp), and confusion matrix values (true positives, true negatives, false positives, false negatives) of different thresholds identified by 3 metrics: the Youden index, the point closest to (0,1) on the curve, and the point where Se roughly equals Sp. Lactating Holstein dairy cows (n = 20) were monitored for 4 consecutive 24-h periods by video recording and with an electronic drinking system. Two periods were used to identify the optimal interval (the baseline set), and the other 2 periods were used to validate the interval (the validation set). The occurrence of a replacement identified by video was paired with the interval between drinking events of 2 cows at the same electronic drinker to identify the interval that best predicted replacement events. Based on the low prevalence of replacement events compared with nonreplacement events, the interval with the lowest number of false positives was considered optimal. Of the 3 potential metrics, the point on the receiver operating characteristic curve where Se and Sp were roughly equal yielded the fewest false positives. The optimal interval to identify replacements at the drinker was ≤29 s, with 82% Se and 83% Sp in the baseline set. This interval was found to have 85% Se and 89% Sp when applied to the validation set. These results indicate that social competition between dairy cows at the drinker can be accurately measured with an electronic drinking system., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Precision dairy technology is important because of the possibility to continuously and accurately measure behavior, biometrics, and productivity on commercial and research dairy farms by an automated method with minimal human intervention. The behavior-monitoring collar (BMC) used in this study is a commercially available precision dairy technology (MooMonitor+, Dairymaster, Co. Kerry, Ireland), designed to measure rumination, heat detection, feeding, and resting behavior of dairy cows. The study objective was to compare cow behavior measured by the BMC with visual observations. Twenty-four lactating, group-housed, Holstein dairy cows (mean ± standard deviation; days in milk: 196 ± 101; parity: 2.0 ± 1.1; milk yield: 40.0 ± 9.8 kg/d) were randomly selected for observation at the University of Kentucky's research dairy farm, Lexington). Behavior-monitoring collars were assigned to cows as per farm protocol. Each cow was observed for 240 min within 1 d (0700 to 0900 h, and 1900 to 2100 h). Recordings of rumination, feeding, and resting time (min) by the BMC were compared with visual observation using Pearson correlation, concordance correlation coefficient (CCC), linear regression, and Bland-Altman plots for validation of precision and accuracy. Data from the BMC were considered precise if the correlation coefficient and coefficient of determination were high (>0.70), and mean bias from the Bland-Altman plots included zero with the 95% interval of agreement. The BMC was considered accurate if the slope from the linear regressions did not differ significantly from 1, and the CCC (ρ c ) were at least moderate (>0.90). We found very high Pearson correlation coefficients (0.99, 0.93, and 0.94) and coefficients of determination (0.97, 0.85, and 0.88) for rumination, feeding, and resting, respectively. Bland-Altman plots were acceptable; the plots did not show any bias. The Bland-Altman mean differences ± standard deviation (BMC - observation) were -7.57 ± 6.31, 15.81 ± 11.84, and -13.03 ± 9.37 min, respectively. The Bland-Altman plot's 95% interval of agreement encompassed 100% of the observations of resting time, and all but one cow's observations for both rumination and feeding time. The slope of the linear regression, however, was different than 1 for all behaviors, and rumination was the only behavior with moderate CCC. In summary, this study validates the high precision of rumination, resting, and feeding behaviors measured by a BMC in lactating dairy cows., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Introduction: In the present study the ante partum ruminating behavior and the later birth course were examined. Between May 2016 and April 2017 all cows, on a North German farm with 430 Holstein Friesian cows, were equipped with a transponder recording the ruminating behavior at least one week before the calculated date of birth. In total, 28 births could be monitored. Regardless of the course of birth, a decrease in ruminal activity was observed in all animals in the days before birth. The most significant decrease was on the last day before the birth. A significant difference occurred only at certain times. The present study confirmed an association between the early decline in ruminal activity and any imminent -dystocia. Further and in-depth studies are needed to create an appropriate algorithm.

The objectives of this study were to evaluate the effectiveness and accuracy of monitoring feeding behavior patterns using cumulative summation (CUSUM) procedures to predict the onset of bovine respiratory disease (BRD) in beef cattle. Growing bulls (N = 231) on a 70-d growth and efficiency trial were used in this study. Between days 28 and 38 of the study, 30 bulls were treated for BRD based on observed clinical signs and elevated rectal temperature (>39.5 °C); remaining bulls (n = 201) were considered healthy. Clinically-ill and healthy bulls were used to evaluate sensitivity and specificity of CUSUM models, with accuracy calculated as the average of sensitivity and specificity. All data were standardized prior to generating CUSUM charts in a daily accumulative manner. Eight univariate CUSUM models were evaluated including DMI, bunk visit (BV) frequency, BV duration, head down (HD) duration, eating rate, maximal nonfeeding interval (NFI Max), SD of nonfeeding interval (NFI SD), and time to bunk (TTB). Accuracies for detection of BRD were 80.1, 69.4, 72.4, 79.1, 63.7, 64.6, 73.2, and 48.7%, respectively, and average day of detection prior to observed symptoms of BRD were 1.0, 3.2, 3.2, 4.8, 10.2, 2.7, 1.5, and 0.6 d, respectively. Principal component analysis (PCA) of all 8 univariate traits (full model) was used to construct multivariate factors that were similarly monitored with CUSUM. Two reduced multivariate models were also constructed that included the 3 best performing feeding behavior traits (BV duration, HD duration, NFI SD) with (RBD) and without DMI (RB). Accuracy of the full multivariate model was similar to the best of the univariate models (75.0%). However, both of the reduced multivariate models (RB and RBD) were more accurate (84.0%) than the full multivariate model. All 3 of the multivariate models signaled (P < 0.05) 2.0 to 2.1 d prior to clinical observation. These results demonstrate that the use of PCA-derived multivariate factors in CUSUM charts was more accurate compared with univariate CUSUM charts, for pre-clinical detection of BRD. Furthermore, adding DMI to the RB model did not further improve accuracy or signal day of BRD detection. The use of PCA-based multivariate models to monitor feeding behavior traits should be more robust than relying on univariate trait models for preclinical detection of BRD. Results from this study demonstrate the value of using CUSUM procedures to monitor feeding behavior patterns to more accurately detect BRD prior to clinical symptoms in feedlot cattle., (© The Author(s) 2018. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Lying behaviour is important for the welfare of the cow. Therefore, reliable electronic devices may improve the management of the cows, and the devices can be used as a tool in research. However, accelerometer-based devices measure acceleration, and an algorithm is therefore necessary for the calculation of lying behaviour. Thus, validation of such devices is imperative prior to use. The objective of this study was to validate the use of the AfiTagII device for measurements of the lying time and frequency of lying bouts of Danish Holstein (DH) and Danish Jersey (DJ) cows in a loose-house system on two different bedding materials. The validation included correlations and linear regression analyses of data collected by the AfiTagII compared with data collected both by direct observations and recordings from a previously validated device (IceQube). In total, 40 cows were observed directly with primiparous and multiparous DJ and DH cows, equally represented. Furthermore, 21 cows were monitored with both AfiTagII and IceQube devices, and data from both devices were collected simultaneously. The devices were attached to the hind leg of the cow. The estimates of the lying time from the AfiTagII device was highly correlated with the recordings from direct observations (r=0.98), and there was a linear relation between these with an intercept equal to 0 and a slope close to 1. The estimates of the lying time from the AfiTagII device was also highly correlated with the IceQube recordings (r=0.94). However, the intercept deviated from 0. The frequency of lying bouts recorded by the AfiTAgII compared to direct observations showed a positive predictive value of 0.96 for lactating cows on the slatted floor and of 0.85 for the dry cows on the deep bedding. The correlations between frequency of lying bouts recorded with the two devices were high (r=0.94), but the intercept deviated from 0. In conclusion, the AfiTagII has a high accuracy for the measurements of lying behaviour in both DH and DJ cows kept on different bedding materials.

Background: Monitoring of intracranial pressure (ICP) is a critical component in the management of intracranial hypertension. Safety, efficacy, and optimal location of microsensor devices have not been defined in dogs., Hypothesis/objective: Assessment of ICP using a microsensor transducer is feasible in anesthetized and conscious animals and is independent of transducer location. Intraparenchymal transducer placement is associated with more adverse effects., Animals: Seven adult, bred-for-research dogs., Methods: In a prospective investigational study, microsensor ICP transducers were inserted into subdural and intraparenchymal locations at defined rostral or caudal locations within the rostrotentorial compartment under general anesthesia. Mean arterial pressure and ICP were measured continuously during physiological maneuvers, and for 20 hours after anesthesia., Results: Baseline mean ± SD values for ICP and cerebral perfusion pressure were 7.2 ± 2.3 and 78.9 ± 7.6 mm Hg, respectively. Catheter position did not have a significant effect on ICP measurements. There was significant variation from baseline ICP accompanying physiological maneuvers (P < .001) and with normal activities, especially with changes in head position (P < .001). Pathological sequelae were more evident after intraparenchymal versus subdural placement., Conclusions and Clinical Importance: Use of a microsensor ICP transducer was technically straightforward and provided ICP measurements within previously reported reference ranges. Results support the use of an accessible dorsal location and subdural positioning. Transient fluctuations in ICP are normal events in conscious dogs and large variations associated with head position should be accounted for when evaluating animals with intracranial hypertension., (Copyright © 2018 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.)

This research communication addresses the goal of validating an algorithm to monitor natural occurrence of feeding behaviours in dairy Mediterranean buffalo based on the output of a noseband pressure sensor (RumiWatch®, halter). Several characteristics of the feeding behaviour were detected with a very high (ruminating boluses), high (chews per bolus) and moderate degree of correlation (chews per minute) with video analyses (gold standard). All of them were associated with a low mean difference with the gold standard, and the mean relative measurement error ranged between low (ruminating boluses) and moderate (chews per bolus and chews per minute). The proportion of correctly detected events for the variables rumination and eating time was 98 and 99%, respectively. The collection of data and subsequent evaluation of the parameters investigated may provide objective information on Mediterranean Buffalo behaviours allowing for reliable studies of the animal welfare in this ruminant in the future.

In a system in which cows are grouped and given differential access to feeding bins with different rations, and where these groups change over time, it is important to find out how a change in the ration (and hence feeding bin) affects the cow's feeding behaviour. Monitoring the locomotion of cows can be used to predict oestrus and improve health (lameness diagnosis), but activity monitors can also be used to estimate both activity and numbers of feeding visits by cows. Ice tag activity monitors were attached to the right hind legs of ten cows. Walking, standing, lying data and health records were used to record changes before and after a change in each cow's feeding bin. Results comparing activity before and after feeding bin change revealed significant increases in motion index, number of steps taken per minute and number of lying bouts per minute (all P &lt; 0.001). Comparing the behaviours of cows subsequently followed during the dry period showed significant differences in motion indices and number of steps taken per minute (P &lt; 0.001) in the dry period. The results indicate that cows are affected by feeding bin change and group change, which can lead to an increase in behaviour associated with the stress response, especially in heifers.

There is increasing scrutiny of the animal welfare impacts of all animal use activities, including agriculture, the keeping of companion animals, racing and entertainment, research and laboratory use, and wildlife management programs. A common objective of animal welfare monitoring is to quantify the frequency of adverse animal events (e.g., injuries or mortalities). The frequency of such events can be used to provide pass/fail grades for animal use activities relative to a defined threshold and to identify areas for improvement through research. A critical question in these situations is how many animals should be sampled? There are, however, few guidelines available for data collection or analysis, and consequently sample sizes can be highly variable. To address this question, we first evaluated the effect of sample size on precision and statistical power in reporting the frequency of adverse animal welfare outcomes. We next used these findings to assess the precision of published animal welfare investigations for a range of contentious animal use activities, including livestock transport, horse racing, and wildlife harvesting and capture. Finally, we evaluated the sample sizes required for comparing observed outcomes with specified standards through hypothesis testing. Our simulations revealed that the sample sizes required for reasonable levels of precision (i.e., proportional distance to the upper confidence interval limit (δ) of ≤ 0.50) are greater than those that have been commonly used for animal welfare assessments (i.e., >300). Larger sample sizes are required for adverse events with low frequency (i.e., <5%). For comparison with a required threshold standard, even larger samples sizes are required. We present guidelines, and an online calculator, for minimum sample sizes for use in future animal welfare assessments of animal management and research programs., Competing Interests: The authors have declared that no competing interests exist.

The feasibility of the home monitoring of heart rate (HR) and rhythm through ECG tracings recorded by owners with a smartphone ECG device was evaluated in dogs. Smartphone ECG tracings were recorded by owners at home using a single-lead ECG device and sent via email for interpretation. A questionnaire was prepared to assess the owner's opinion regarding this home monitoring service. Recordings were evaluated by two operators, and agreement was evaluated for HR and rhythm diagnosis. Thirty-three dogs were included. Thirty-one owners (94 per cent) felt that the recording technique was easy to learn and that the smartphone ECG device was easy to use. A total of 15 owners (45 per cent) required a second person to hold the dog during recording. Of the 150 smartphone ECG tracings that were received, 134 (89 per cent) were interpretable. The median difference between the two operators to assess the mean HR on the smartphone tracings was 10 bpm (-10, +25 bpm). Perfect agreement (κ=1) between operators was observed in the heart rhythm evaluation. Most owners sent adequate ECG tracings for interpretation via email from their smartphone. Home monitoring of HR and heart rhythm may represent an additional tool in the management of dogs with arrhythmias., Competing Interests: Competing interests: None declared., (© British Veterinary Association 2018. No commercial re-use. See rights and permissions. Published by BMJ.)

Bio-loggers are miniaturized autonomous devices that record quantitative data on the state of free-ranging animals (e.g. behavior, position and physiology) and their natural environment. This is especially relevant for species where direct visual observation is difficult or impossible. Today, ongoing technical development allows the monitoring of numerous parameters in an increasing range of species over extended periods. However, the external attachment of devices might affect various aspects of animal performance (energetics, thermoregulation, foraging as well as social and reproductive behavior), which ultimately affect fitness. External attachment might also increase entanglement risk and the conspicuousness of animals, leaving them more vulnerable to predation. By contrast, implantation of devices can mitigate many of these undesirable effects and might be preferable, especially for long-term studies, provided that the many challenges associated with surgical procedures can be mastered. Implantation may then allow us to gather data that would be impossible to obtain otherwise and thereby may provide new and ecologically relevant insights into the life of wild animals. Here, we: (i) discuss the pros and cons of attachment methods; (ii) highlight recent field studies that used implanted bio-loggers to address eco-physiological questions in a wide range of species; and (iii) discuss logger implantation in light of ethical considerations., (© 2018 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.)

This study aimed to evaluate the effectiveness of estrous detection technique based on continuous measurements of vaginal temperature (VT) and conductivity (VC) with supervised machine learning in cattle. The VT and VC of 17 cows in tie-stalls were measured using our developed wearable vaginal sensor from Day 11 (Day 0 = ovulation day) to Day 11 of the subsequent estrous cycle at 15-min interval. After the maximum VT and VC were extracted hourly, their changes were expressed as residual VT (rVT = actual VT - mean VT for the same time on the previous 3 days) and as VC ratio (VCr = actual VC/mean VC for the same time on Day 11-13), respectively, and were used for analysis. Trans-rectal ultrasonography was performed to monitor ovarian structure changes. The plasma concentrations of reproductive hormones (progesterone: P 4 , estradiol-17β: E 2 , and LH) were measured in the experimental period. Standing estrus was confirmed by testing with herd mates at 3-h interval. The rVT decreased transiently, which coincided with decreasing P 4 a few days before estrus, and a sharp increase was associated with LH surge during estrus. The VCr increased as estrus approached, corresponding with decreasing P 4 and increasing E 2 and LH. After noise reduction, features, possible to follow-up estrus-associated changes in rVT and VCr, were extracted and used for developing estrous detection models; 9 models were developed with 3 feature sets (features extracted from rVT alone, VCr alone, and combination of rVT and VCr) and 3 machine learning algorithms (decision tree: DT, support vector machine: SVM, and artificial neural network: ANN). Cross-validation showed that models using the features from the combination of rVT and VCr showed better performance in terms of sensitivity and precision than those using features from VCr alone, and precision than those of using features from rVT alone. Within the models using the features from the combination of rVT and VCr, sensitivity and precision of the model generated by ANN were numerically, but not statistically, higher than those generated by DT and SVM. Of 17 estruses, 16 were detected, with one false positive, when the best model was used. Furthermore, both mean and variance of the interval from the beginning of the estrous detection alert to ovulation (27.3 ± 6.7 h, mean ± SD of 16 estruses) were not significantly different to those from the onset of standing estrus to ovulation (30.8 ± 5.8 h, n = 17), indicating that the estrus can be detected real-time by the present technique. Hence, the estrous detection technique based on continuous measurements of VT and VC with supervised machine learning has a potential for efficient and accurate estrous detection in cattle., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The measurement of the respiration rate (RR) in cattle is a valuable tool for monitoring health status. Thus, an RR sensor can be essential for stress detection, especially heat stress. Heat stress leads to a deviation of the normal RR and results in a decrease of milk production and fertility. Therefore, continuous monitoring of the RR can help early detection of heat stress and, thus, initiate timely counteractive actions to minimize physical stress. The most common method to measure the RR in cattle is to count the flank movement visually; however, this method is time-consuming and labor-intensive. In addition, the continuous measurement of the RR is difficult to implement and can be physically strenuous. Therefore, a device based on a differential pressure sensor that can record RR automatically has been developed to make continuous long-term studies possible. The aim of this study was to validate the data measured by the device with the help of a reference method. The reference method used was counting the flank movements of a total of 6 cows (Holstein-Friesian). The rear flank movements of each cow were recorded by a camera and counted independently of the device by an observer. Eight videos of 1 min each were recorded per cow. The data analysis was done with cows in 3 different body positions: dozing, lying, and standing. A total of 48 RR measurements of the device were compared with the counted RR frequencies of the video recording. The results were highly correlated during dozing [correlation coefficient (r) = 0.92, n = 13], lying (r = 0.98, n = 15), and standing (r = 0.99, n = 20). The evaluation showed that the device is suitable for automated RR counting. Further development of a marketable device is planned., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

As one of the few felids that is predominantly diurnal, cheetahs (Acinonyx jubatus) can be exposed to high heat loads in their natural habitat. Little is known about long-term patterns of body temperature and activity (including hunting) in cheetahs because long-term concurrent measurements of body temperature and activity have never been reported for cheetahs, or, indeed, for any free-living felid. We report here body temperature and locomotor activity measured with implanted data loggers over 7 months in 5 free-living cheetahs in Namibia. Air temperature ranged from a maximum of 39 °C in summer to -2 °C in winter. Cheetahs had higher (∼0.4 °C) maximum 24-h body temperatures, later acrophase (∼1 h), with larger fluctuations in the range of the 24-h body temperature rhythm (approximately 0.4 °C) during a hot-dry period than during a cool-dry period, but maintained homeothermy irrespective of the climatic conditions. As ambient temperatures increased, the cheetahs shifted from a diurnal to a crepuscular activity pattern, with reduced activity between 900 and 1500 hours and increased nocturnal activity. The timing of hunts followed the general pattern of activity; the cheetahs hunted when they were on the move. Cheetahs hunted if an opportunity presented itself; on occasion they hunted in the midday heat or in total darkness (new moon). Biologging revealed insights into cheetah biology that are not accessible by traditional observer-based techniques., (© 2018 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.)

We present an animal model used to evaluate the in vivo performance of electrochemical amperometric continuous lactate sensors compared to blood gas instruments. Electrochemical lactate sensors were fabricated, placed into 5 Fr central venous catheters (CVCs), and paired with wireless potentiostat devices. Following in vivo evaluation and calibration, sensors were placed within the jugular and femoral veins of a porcine subject as a preliminary assessment of in vivo measurement accuracy. The mobile electronic circuit potentiostat devices supplied the operational voltage for the sensors, measured the resultant steady-state current, and recorded the sensor response values in internal memory storages. An in vivo time trace of implanted intravenous (IV) sensors demonstrated lactate values that correlated well with the discrete measurements of blood samples on a benchtop point-of-care sensor-based instrument. Currents measured continuously from the implanted lactate sensors over 10 h were converted into lactate concentration values through use of a two-point in vivo calibration. Study shows that intravenously implanted sensors had more accurate readings, faster peak-reaching rates, and shorter peak-detection times compared to subcutaneously placed sensors. IV implanted and subcutaneously placed sensors closer to the upper body (in this case neck) showed faster response rates and more accurate measurements compared to those implanted in the lower portion of the porcine model. This study represents an important milestone not only towards continuous lactate monitoring for early diagnosis and intervention in neonatal patients with congenital heart disease undergoing cardiopulmonary bypass surgeries, but also in the intervention of critical ill patients in the Intensive Care Units or during complex surgical procedures.

The types of changes in physical appearance and behavior that occur in elderly people similarly develop in elderly animals. Signs and symptoms that might cause concern in younger people or mice may be normal in their elderly but generally healthy counterparts. Although numerous scoring methods have been developed to assess rodent health, these systems were often designed for young adults used in specific types of research, such as cancer or neurologic studies, and therefore may be suboptimal for assessing aging rodents. Approaches known as frailty assessments provide a global evaluation of the health of aged mice, rats, and people, and mouse frailty scores correlate well with the likelihood of death. Complementing frailty assessment, prediction of imminent death in aged mice can often be accomplished by focusing on 2 objective parameters-body weight and temperature. Before they die, many (but not all) mice develop marked reductions in body weight and temperature, thus providing signs that close monitoring, intervention, or preemptive euthanasia may be necessary. Timely preemptive euthanasia allows antemortem collection of data and samples that would be lost if spontaneous death occurred; preemptive euthanasia also limits terminal suffering. These approaches to monitoring declining health and predicting death in elderly research mice can aid in establishing and implementing timely interventions that both benefit the research and reduce antemortem suffering.