Technical note: Preliminary evaluation of an automated indwelling rumen temperature bolus measurement system to detect pyrexia in preweaned dairy calves

Literature Review on Technological Applications to Monitor and Evaluate Calves' Health and Welfare

Precision livestock farming (PLF) research is rapidly increasing and has improved farmers' quality of life, animal welfare, and production efficiency. PLF research in dairy calves is still relatively recent but has grown in the last few years. Automatic milk feeding systems (AMFS) and 3D accelerometers have been the most extensively used technologies in dairy calves. However, other technologies have been emerging in dairy calves' research, such as infrared thermography (IRT), 3D cameras, ruminal bolus, and sound analysis systems, which have not been properly validated and reviewed in the scientific literature. Thus, with this review, we aimed to analyse the state-of-the-art of technological applications in calves, focusing on dairy calves. Most of the research is focused on technology to detect and predict calves' health problems and monitor pain indicators. Feeding and lying behaviours have sometimes been associated with health and welfare levels. However, a consensus opinion is still unclear since other factors, such as milk allowance, can affect these behaviours differently. Research that employed a multi-technology approach showed better results than research focusing on only a single technique. Integrating and automating different technologies with machine learning algorithms can offer more scientific knowledge and potentially help the farmers improve calves' health, performance, and welfare, if commercial applications are available, which, from the authors' knowledge, are not at the moment.

Dairy Cattle Rumen Bolus Developments with Special Regard to the Applicable Artificial Intelligence (AI) Methods

It is a well-known worldwide trend to increase the number of animals on dairy farms and to reduce human labor costs. At the same time, there is a growing need to ensure economical animal husbandry and animal welfare. One way to resolve the two conflicting demands is to continuously monitor the animals. In this article, rumen bolus sensor techniques are reviewed, as they can provide lifelong monitoring due to their implementation. The applied sensory modalities are reviewed also using data transmission and data-processing techniques. During the processing of the literature, we have given priority to artificial intelligence methods, the application of which can represent a significant development in this field. Recommendations are also given regarding the applicable hardware and data analysis technologies. Data processing is executed on at least four levels from measurement to integrated analysis. We concluded that significant results can be achieved in this field only if the modern tools of computer science and intelligent data analysis are used at all levels.

Wearable Wireless Biosensor Technology for Monitoring Cattle: A Review

The review aimed to collect information about the wearable wireless sensor system (WWSS) for cattle and to conduct a systematic literature review on the accuracy of predicting the physiological parameters of these systems. The WWSS was categorized as an ear tag, halter, neck collar, rumen bolus, leg tag, tail-mounted, and vaginal mounted types. Information was collected from a web-based search on Google, then manually curated. We found about 60 WWSSs available in the market; most sensors included an accelerometer. The literature evaluating the WWSS performance was collected through a keyword search in Scopus. Among the 1875 articles identified, 46 documents that met our criteria were selected for further meta-analysis. Meta-analysis was conducted on the performance values (e.g., correlation, sensitivity, and specificity) for physiological parameters (e.g., feeding, activity, and rumen conditions). The WWSS showed high performance in most parameters, although some parameters (e.g., drinking time) need to be improved, and considerable heterogeneity of performance levels was observed under various conditions (average I² = 76%). Nevertheless, some of the literature provided insufficient information on evaluation criteria, including experimental conditions and gold standards, to confirm the reliability of the reported performance. Therefore, guidelines for the evaluation criteria for studies evaluating WWSS performance should be drawn up.

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

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

A Systematic Review on Commercially Available and Validated Sensor Technologies for Welfare Assessment of Dairy Cattle

In order to base welfare assessment of dairy cattle on real-time measurement, integration of valid and reliable precision livestock farming (PLF) technologies is needed. The aim of this study was to provide a systematic overview of externally validated and commercially available PLF technologies, which could be used for sensor-based welfare assessment in dairy cattle. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic literature review was conducted to identify externally validated sensor technologies. Out of 1,111 publications initially extracted from databases, only 42 studies describing 30 tools (including prototypes) met requirements for external validation. Moreover, through market search, 129 different retailed technologies with application for animal-based welfare assessment were identified. In total, only 18 currently retailed sensors have been externally validated (14%). The highest validation rate was found for systems based on accelerometers (30% of tools available on the market have validation records), while the lower rates were obtained for cameras (10%), load cells (8%), miscellaneous milk sensors (8%), and boluses (7%). Validated traits concerned animal activity, feeding and drinking behavior, physical condition, and health of animals. The majority of tools were validated on adult cows. Non-active behavior (lying and standing) and rumination were the most often validated for the high performance. Regarding active behavior (e.g., walking), lower performance of tools was reported. Also, tools used for physical condition (e.g., body condition scoring) and health evaluation (e.g., mastitis detection) were classified in lower performance group. The precision and accuracy of feeding and drinking assessment varied depending on measured trait and used sensor. Regarding relevance for animal-based welfare assessment, several validated technologies had application for good health (e.g., milk quality sensors) and good feeding (e.g., load cells, accelerometers). Accelerometers-based systems have also practical relevance to assess good housing. However, currently available PLF technologies have low potential to assess appropriate behavior of dairy cows. To increase actors' trust toward the PLF technology and prompt sensor-based welfare assessment, validation studies, especially in commercial herds, are needed. Future research should concentrate on developing and validating PLF technologies dedicated to the assessment of appropriate behavior and tools dedicated to monitoring the health and welfare in calves and heifers.

Symposium review: Precision technologies for dairy calves and management applications

There is an increasing interest in using precision dairy technologies (PDT) to monitor real-time animal behavior and physiology in livestock systems around the world. Although PDT in adult cattle is extensively reviewed, PDT use for the management of preweaned dairy calves has not been reviewed. We systematically reviewed research on the use and application of precision technologies in calves. Accelerometers have the potential to be used to monitor lying behavior, step activity, and rumination, which are useful to detect changes in behavior that may be indicative of disease, responses to painful procedures, or positive welfare behaviors such as play. Automated calf feeding systems can control delivery of nutritional plans to individualize feeding and weaning of calves; changes in feeding behaviors (such as milk intake, drinking speed, and unrewarded visits) may also be used to identify early onset of disease. The PDT devices also measure physiological and physical attributes in dairy calves. For instance, temperature monitoring devices such as infrared thermography, ruminal boluses, and implanted microchips have been assessed in calves, but no herd management-based commercial system is available. Many other PDT are in development with potential to be used in dairy calf management, such as image and acoustic-based monitoring, real-time location, and use of enrichment items for monitoring positive emotional states. We conclude that PDT have great potential for application in dairy calf management, enabling precise behavioral and physiological monitoring, targeted feeding programs, and identification of calves with poor health or behavioral impairments. We strongly encourage further development and validation of commercially available technologies for on-farm application of the monitoring of dairy calf welfare, performance, and health.

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.

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.

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.

Assessing the effects of weekly preweaning health scores on dairy calf mortality and productivity parameters: cohort study

A longitudinal cohort study was conducted to follow the health of 787 calves from one UK dairy farm over a two-and-a-half-year period. Weekly health scores were gathered using a modified version of the Wisconsin Calf Scoring system (which did not record ear position) until calves were eight weeks of age, combined with data on colostral passive transfer, mortality, age at first conception and 305-day milk yield. High morbidity levels were detected, with 87 per cent of calves experiencing at least one clinically significant event (diarrhoea, pyrexia, pneumonia, nasal or ocular discharge, navel ill or joint ill). High rectal temperature, diarrhoea and a cough were the most prevalent findings. The effect of total protein levels was significantly associated with the development of pyrexia as a preweaning calf (P<0.01), but no other clinical health scores. The majority of moribund calves had just one clinically severe clinical sign detected at each of the weekly recordings. The overall mortality rate was 21.5 per cent up to 14 months of age, with 12.7 per cent of calves dying during the preweaning period. However, most calves that died were not recorded as having experienced a severe clinical sign in the time between birth and death, indicating a limitation in weekly calf scoring in detecting acute disease leading to death. Therefore, more frequent calf scoring or use of technology for continuous calf monitoring on farms is required to reduce mortality on farms with high disease incidence rates.