A field trial of infrared thermography as a non-invasive diagnostic tool for early detection of digital dermatitis in dairy cows

Comparative analysis of computer vision algorithms for the real-time detection of digital dermatitis in dairy cows

Digital dermatitis (DD) is a bovine claw disease responsible for ulcerative lesions on the planar aspect of the hoof. DD is associated with massive herd outbreaks of lameness and influences cattle welfare and production. Early detection of DD can lead to prompt treatment and decrease lameness. Computer vision (CV) provides a unique opportunity to improve early detection. The study aims to train and compare applications for the real-time detection of DD in dairy cows. Eight CV models were trained for detection and scoring, compared using performance metrics and inference time, and the best model was automated for real-time detection using images and video. Images were collected from commercial dairy farms while facing the interdigital space on the plantar surface of the foot. Images were scored for M-stages of DD by a trained investigator using the M-stage DD classification system with distinct labels for hyperkeratosis (H) and proliferations (P). Two sets of images were compiled: the first dataset (Dataset 1) containing 1,177 M0/M4H and 1,050 M2/M2P images and the second dataset (Dataset 2) containing 240 M0, 17 M2, 51 M2P, 114 M4H, and 108 M4P images. Models were trained to detect and score DD lesions and compared for precision, recall, and mean average precision (mAP) in addition to inference time in frame per second (FPS). Seven of the nine CV models performed well compared to the ground truth of labeled images using Dataset 1. The six models, Faster R-CNN, Cascade R-CNN, YOLOv3, Tiny YOLOv3, YOLOv4, Tiny YOLOv4, and YOLOv5s achieved an mAP between 0.964 and 0.998, whereas the other two models, SSD and SSD Lite, yielded an mAP of 0.371 and 0.387 respectively. Overall, YOLOv4, Tiny YOLOv4, and YOLOv5s outperformed all other models with almost perfect precision, perfect recall, and a higher mAP. Tiny YOLOv4 outperformed all other models with respect to inference time at 333 FPS, followed by YOLOv5s at 133 FPS and YOLOv4 at 65 FPS. YOLOv4 and Tiny YOLOv4 performed better than YOLOv5s compared to the ground truth using Dataset 2. YOLOv4 and Tiny YOLOv4 yielded a similar mAP of 0.896 and 0.895, respectively. However, Tiny YOLOv4 achieved both higher precision and recall compared to YOLOv4. Finally, Tiny YOLOv4 was able to detect DD lesions on a commercial dairy farm with high performance and speed. The proposed CV tool can be used for early detection and prompt treatment of DD in dairy cows. This result is a step towards applying CV algorithms to veterinary medicine and implementing real-time DD detection on dairy farms.

Evaluation of the hoof's temperature variations depending on lesion presence, measurement points and leg position

In order to determine the possibility of using infrared thermography (IRT) in preventing lameness in dairy cows, the aim of this study was to evaluate temperature variations depending on the lesion presence, measurement points and leg position. The study used about 3 000 IRT records from 60 Holstein cows housed in a free-stall barn. Surface temperature measurements were taken at two regions of the hooves: the region of the coronary band, and the region of the skin up to 2 cm above the coronary band. A highly significant (P = 0.004; 0.006, P < 0.01) difference in temperature was observed between healthy and diseased legs at both measurement points. Additionally, a significant (P = 0.029; 0.037; 0.045; 0.012; 0.018, P < 0.05) or highly significant (P = 0.004; 0.006, P < 0.01) difference in temperature values between the front and rear legs was established for both measurement points, i.e., the coronary band and the skin. Despite confirming the potential applicability of infrared thermography in the detection of lameness, it is crucial to consider the significant influences of the environmental factors, impurities, and animal-related factors.

Thermal imaging and computer vision technologies for the enhancement of pig husbandry: a review

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

An In-House ELISA for Treponema Antibodies in Bulk Milk as Part of a Monitoring Tool for Claw Health in Dairy Herds

Digital dermatitis (DD) is a painful inflammation at the coronary band of the claws, a major cause of lameness in cattle and associated with infections with several Treponema spp. Clinical inspection of the feet is the best way to diagnose DD, but this is laborious and stressful for cattle. A simple diagnostic tool was developed to monitor DD prevalence at the herd level. An antibody ELISA based on antigens from four different Treponema spp. has been developed and validated in two field studies. In one study, bulk milk and individual milk samples of seven dairy herds, of which clinical claw scores were obtained, were tested. In the second study, bulk milk was tested from 110 herds of which clinical scores were obtained. A weak correlation between clinical scores of cows and the ELISA results in individual milk samples was observed. The ELISA response in bulk milk was higher in herds with higher mean clinical scores. Using the ELISA results in bulk milk, herds with a low or high proportion of cattle with DD lesions could be distinguished. This ELISA is useful to obtain insight into the DD status at the herd level, and is nowadays being used in a claw health monitoring program for dairy cattle in the Netherlands.

Assessing Alternatives to Locomotion Scoring for Detecting Lameness in Dairy Cattle in Tanzania: Infrared Thermography

Lameness detection is a significant challenge. Locomotion scoring (LS), the most widely used system for detecting lameness, has several limitations, including its subjective nature and the existence of multiple systems, each with its own advantages and disadvantages. Therefore, this study aimed to evaluate whether the foot skin temperature (FST) of hind limbs, as measured using infrared thermography (IRT), could potentially be used as an alternative on Tanzanian dairy farms. Each of the three study farms were visited twice during the afternoon milking on consecutive days, with a total of 170 cows assessed. DairyNZ LS (4-point scale (0-3)) was undertaken on the first day as the cows exited the milking parlour after being milked, while on the following day, the plantar aspect of the hind limbs of the cows was thermally imaged while they were standing in the milking parlour, using a handheld T650sc forward-looking infrared camera. Mean FST was higher for cows with a locomotion score of 1 than those with a score of 0; higher for cows with a locomotion score of 2 than those with a score of 1; and higher for cows with a locomotion score of 3 than those with a score of 2, with each one-unit locomotion score increase being associated with a 0.57 °C increase in mean temperature across all zones. The optimal cut-off point of 38.0 °C for mean temperature across all zones was identified using a receiver operator characteristic curve. This cut-off point had a sensitivity of 73.2% and a specificity of 86.0% for distinguishing cows with a locomotion score ≥ 2 (clinical lameness). The prevalence of clinical lameness across all three farms was 33%, which meant that only 72% of cows with a mean FST across all zones ≥ 38.0 °C had been identified as clinically lame using LS. This study confirmed that IRT has the potential to be used to detect lameness on Tanzanian dairy farms. However, before it can be widely used, improvements in accuracy, especially specificity, are needed, as are reductions in equipment (IR camera) costs.

Monitoring Claw Length, Feet Infrared Temperature, Mobility and Backfat Tissue Changes in Replacement Gilts of Different Genetic Lines in Three Farrow-to-Finish Herds in Greece

Feet infrared temperature is associated with feet health and may affect the reproductive performance of sows. In total, 137, 98 and 114 replacement gilts were selected at the age of weaning from 3 herds—A, B and C—with different genetic lines. Dorsal claw length was measured, and anisodactylia was measured in all four feet, at weaning age, and at those gilts that completed their first and second farrowing. At the first and second farrowing stage, the infrared temperature distribution, dew/claw length and backfat thickness were measured concurrently with claw lesion and mobility score evaluation. The maximum temperature significantly differed (p < 0.01) among herds, in the rear feet and in all four feet at the first and second farrowing respectively. Claw lengths statistically differed among herds at all stages (p < 0.05). Anisodactylia in rear feet was lower in herd A (p < 0.05) at weaning, and in herd C at the first and second farrowing (p < 0.05). In addition, the claw lesion score, mobility, backfat thickness and reproductive performance statistically differed among herds (p < 0.05). It is shown that even at an early stage of their reproductive life, claw length differences exist in replacement gilts of different genetic lines.

Broad-spectrum infrared thermography for detection of M2 digital dermatitis lesions on hind feet of standing dairy cattle

Low-effort, reliable diagnostics of digital dermatitis (DD) are needed, especially for lesions warranting treatment, regardless of milking system or hygienic condition of the feet. The primary aim of this study was to test the association of infrared thermography (IRT) from unwashed hind feet with painful M2 lesions under farm conditions, with lesion detection as ultimate goal. Secondary objectives were to determine the association between IRT from washed feet and M2 lesions, and between IRT from unwashed and washed feet and the presence of any DD lesion. A total of 641 hind feet were given an M-score and IRT images of the plantar pastern were captured. Multivariable logistic regression analyses were done with DD status as dependent variable and maximum infrared temperature (IRTmax), lower leg cleanliness score and locomotion score as independent variables, and farm as fixed effect. To further our understanding of IRTmax within DD status, we divided IRTmax into two groups over the median value of IRTmax in the datasets of unwashed and washed feet, respectively, and repeated the multivariable logistic regression analyses. Higher IRTmax from unwashed hind feet were associated with M2 lesions or DD lesions, in comparison with feet without an M2 lesion or without DD, adjusted odds ratio 1.6 (95% CI 1.2-2.2) and 1.1 (95% CI 1.1-1.2), respectively. Washing of the feet resulted in similar associations. Dichotomization of IRTmax substantially enlarged the 95% CI for the association with feet with M2 lesions indicating that the association becomes less reliable. This makes it unlikely that IRTmax alone can be used for automated detection of feet with an M2 lesion. However, IRTmax can have a role in identifying feet at-risk for compromised foot health that need further examination, and could therefore function as a tool aiding in the automated monitoring of foot health on dairy herds.

Molecular, Physiological and Hematological Responses of Crossbred Dairy Cattle in a Tropical Savanna Climate

A comprehensive study was conducted to assess the effects of seasonal transition and temperature humidity index (THI) on the adaptive responses in crossbred dairy cows reared in a tropical savanna region. A total of 40 lactating dairy cattle reared by small-scale dairy farmers in Bengaluru, India, were selected for this study. The research period comprised the transitioning season of summer to monsoon, wherein all traits were recorded at two points, one representing late summer (June) and the other early monsoon (July). A set of extensive variables representing physiological responses (pulse rate, respiration rate, rectal temperature, skin surface temperature), hematological responses (hematological profile), production (test day milk yield, milk composition) and molecular patterns (PBMC mRNA relative expression of selective stress response genes) were assessed. A significant effect of seasonal transition was identified on respiration rate (RR), skin surface temperature, mean platelet volume (MPV), platelet distribution width (PDWc), test day milk yield and on milk composition variables (milk density, lactose, solids-not-fat (SNF) and salts). The THI had a significant effect on RR, skin surface temperature, platelet count (PLT), plateletcrit (PCT) and PDWc. Lastly, THI and/or seasonal transition significantly affected the relative PBMC mRNA expression of heat shock protein 70 (HSP70), interferon beta (IFNβ), IFNγ, tumor necrosis factor alpha (TNFα), growth hormone (GH) and insulin-like growth factor-1 (IGF-1) genes. The results from this study reveal environmental sensitivity of novel physiological traits and gene expressions to climatic stressors, highlighting their potential as THI-independent heat stress biomarkers.

Integrated infrared thermography and accelerometer-based behavior logger as a hoof lesion identification tool in dairy cows with various foot diseases under subtropical climates

Infrared thermography (IRT) can measure a temperature change on the surface of objects, and is widely used as an inflammation or fever detection tool. The objective of this longitudinal study was to investigate the feasibility of detecting hoof lesion cattle using IRT under subtropical climate conditions. The experiment was conducted in two free-stall commercial dairy farms and 502 dairy cows participated between August 2020 and March 2022. Before hoof trimming, the portable IRT was used to measure the maximum temperature of each hoof from three shooting directions, including anterior (hoof coronary band), lateral (hoof lateral coronary band), and posterior (skin between heel and bulbs). In order to evaluate the effect of hoof lesions on the behavior of dairy cows, we also collected behavior data by automated accelerometers. The results indicated that the temperature of hooves with lesions was significantly higher than that of sound hooves in hot environments regardless of the shooting directions (P < 0.0001). In all of three shooting directions, the maximum temperature of feet with severe lesion was significantly higher than those of feet with mild lesion and sound feet (P < 0.05). Cows with lesion feet had lower daily activity and feeding time than sound cows before clinical diagnosis (P < 0.05). Furthermore, we used thresholds of both anterior hoof temperature at 32.05 °C and average daily activity at 410.5 (arbitrary unit/d) as a lame cow detecting tool. The agreement of this integrated tool reached 75% with clinical diagnosis, indicating that this integrated approach may be feasible for practice in dairy farm. In conclusion, IRT has the potential to be used as a hoof lesion detecting tool under subtropical climate conditions when using sound hoof temperature as reference points, and detection precision can be improved when IRT integrated with automated accelerometers as a lame cow detecting tool.

Thermography for disease detection in livestock: A scoping review

Infra-red thermography (IRT) offers potential opportunities as a tool for disease detection in livestock. Despite considerable research in this area, there are no common standards or protocols for managing IRT parameters in animal disease detection research. In this review, we investigate parameters that are essential to the progression of this tool and make recommendations for their use based on the literature found and the veterinary thermography guidelines from the American Academy of Thermology. We analyzed a defined set of 109 articles concerned with the use of IRT in livestock related to disease and from these articles, parameters for accurate IRT were identified and sorted into the fields of camera-, animal- or environment-related categories to assess the practices of each article in reporting parameters. This review demonstrates the inconsistencies in practice across peer-reviewed articles and reveals that some important parameters are completely unreported while others are incorrectly captured and/or under-represented in the literature. Further to this, our review highlights the lack of measured emissivity values for live animals in multiple species. We present guidelines for the standards of parameters that should be used and reported in future experiments and discuss potential opportunities and challenges associated with using IRT for disease detection in livestock.

Comparison of Low- and High-Cost Infrared Thermal Imaging Devices for the Detection of Lameness in Dairy Cattle

Simple Summary

Lameness has high economic and welfare cost to the U.K. dairy industry; accurate and early detection of lameness minimises this cost. Thermal imaging devices can be used as a method of detecting lameness; however, these devices are typically high-cost and fragile, limiting their usefulness in a farm setting. This study looked at the effectiveness of low-cost thermal imaging devices when used as lameness detection aids, by comparing one to a research-specification thermal imaging device. Thermal images were taken of cattle feet, and each cow was assessed for lameness. Both devices tested were able to determine whether the cattle were lame; however, the research-specification device performed marginally better at this function. This minimal difference in effectiveness between these devices suggests that low-cost thermal imaging devices could be used as a lameness detection aid; increased use of these devices by farmers may increase lameness detection rates and benefit animal welfare.

Abstract

Lameness has a high economic cost to the U.K. dairy industry; accurate and early detection of lameness minimises this cost. Infrared thermal imaging (IRT) devices have shown promising results for use as a lameness detection aid in cattle when used in research settings; these devices are typically high-cost, limiting their adoption. This study analysed the effectiveness of low-cost IRT devices (LCDs) as lameness detection aids, by comparing both maximum environmentally adjusted temperature values and hindfeet temperature difference collected by an LCD to the mobility score of the cow; this test was repeated for data collected by a research-specification device. Data collection occurred during routine milking of 83 cattle; each cow’s mobility was scored afterwards. Significant differences were found between lame and sound cows with the LCD, upon analysis of both methods. There was no significant difference between the data captured by differing devices. The maximum sensitivity and specificity values for the LCD were calculated as 66.95 and 64.53, respectively, compared with 70.34 and 70.94, respectively, for the research-specification device; optimum threshold values for these were equivalent for both devices, suggesting IRT lameness identification is not device-dependent. It was concluded that a minimal difference in effectiveness between tested devices suggests that LCDs could be used as a lameness detection aid; consequently, there is potential for widespread adoption as on-farm detection aids.

Evaluating Alternatives to Locomotion Scoring for Lameness Detection in Pasture-Based Dairy Cows in New Zealand: Infra-Red Thermography

Simple Summary

Early detection accompanied by effective treatment is vital to minimise the negative impacts of lameness in dairy cows. Locomotion scoring is commonly used for detecting lameness but can be challenging to implement effectively in cows at pasture-based systems. One potential alternative detection is measuring foot skin temperature using an infrared camera. Data were collected from a 940-cow dairy farm in New Zealand with cows observed at two consecutive afternoon milkings. Locomotion scoring was undertaken at the first milking and thermal imaging of the hind feet at the second milking. As the locomotion score increased, mean foot skin temperature increased, showing that measuring temperature could be a useful alternative to locomotion scoring. However, the process needs to be speeded up and automated if it is to be used widely.

Abstract

Lameness in cattle is a complex condition with huge impacts on welfare, and its detection is challenging for the dairy industry. The present study aimed to evaluate the association between foot skin temperature (FST) measured using infrared thermography (IRT) and locomotion scoring (LS) in dairy cattle kept at pasture. Data were collected from a 940-cow dairy farm in New Zealand. Cows were observed at two consecutive afternoon milkings where LS was undertaken at the first milking (4-point scale (0–3), DairyNZ). The next day, cows were thermally imaged from the plantar aspect of the hind feet using a handheld T650sc forward-looking infrared camera (IRT). The association between FST and locomotion score was analysed using a generalised linear model with an identity link function and robust estimators. ROC curves were performed to determine optimal threshold temperature cut-off values by maximising sensitivity and specificity for detecting locomotion score ≥ 2. There was a linear association between individual locomotion scores and FST. For mean temperature (MT), each one-unit locomotion score increase was associated with a 0.944 °C rise in MT. Using MT at a cut-off point of 34.5 °C produced a sensitivity of 80.0% and a specificity of 92.4% for identifying cows with a locomotion score ≥ 2 (lame). Thus, IRT has a substantial potential to be used on-farm for lameness detection. However, automation of the process will likely be necessary for IRT to be used without interfering with farm operations.

Infrared Thermography Evaluation of Feet Temperature and Its Association with Claw Lengths and Anisodactylia in Purebred Sows of Three Greek Herds

The aim of the study was to investigate the associations of lower feet temperature with claw lengths measurements in purebred sows. In total 22, 19 and 45 multiparous sows in three herds A, B and C of PIC, DANBRED and TOPIGS genetic lines respectively participated in the study. Mean parity was 2.5, 2.3 and 3.0 for sows from herds A, B and C respectively. Measurements were made during the periparturient period. Infrared temperature distribution was measured in carpus/tarsus, upper-lower metacarpi/metatarsi and phalanges (IRT1, IRT2, IRT3 and IRT4 respectively). In addition, dorsal, diagonal, heel-sole and dew claw lengths of medial and lateral claw were measured and the difference in dorsal claw length between medial and lateral claw (anisodactylia) was calculated in all four feet. Differences between herds regarding IRT and claw length measurements were analyzed with one-way ANOVA with herds as a fixed factor. Correlations between IRT and claw length measurements in each foot including data from all herds were evaluated using the Pearson's correlation test. Maximum IRT1 to 4 in almost all rear feet, differed significantly between herds, being lower in sows of herd C than A and B (p < 0.05). Claw lengths of all feet were lower in herd C than those of A and B (p < 0.05). Anisodactylia, differed significantly only in rear feet between herds been higher in herd A than C and B (p < 0.05). In all sows, claw lengths and rear feet anisodactylia were positively correlated with maximum IRT1 to IRT4 (p < 0.05). According to the results, IRT temperature distribution of lower feet of purebred sows of different genetic lines were positive correlated with claw lengths measurements and anisodactylia. Collectively, measuring IRT temperature of lower feet of sows with mobile IRT device could be used as an additional tool towards monitoring feet and claw health.

Evaluation of Infrared Thermography for the Detection of Footrot and White Line Disease Lesions in Dairy Sheep

The objectives of this study were to investigate temperature distribution at the sheep hoof and evaluate the reliability and diagnostic performance of infrared thermography (IRT) for the detection of footrot and white line disease (WLD) lesions in intensively reared dairy sheep. Hoof lesions were clinically assessed, and IRT was used to measure temperature distribution on hoof superficial tissue in 600 multiparous ewes. Binary regression models were developed and validated, and receiver operating characteristic curves were estimated to assess the predictive value and diagnostic performance of IRT for the detection of hoof lesions. The most sensitive prediction model for the detection of IFR was based on the difference between ambient and hoof heel temperature (sensitivity: 83.3%, specificity: 47.8%, and threshold value: 6.5 °C), whereas the most specific prediction model was based on the difference between ambient and coronary band temperature (sensitivity: 51.9%, specificity: 79.7%, and threshold value: 11.3 °C). In the case of WLD, the diagnostic performance of IRT had limited predictive value. IRT could be a useful tool for hoof health screening in dairy sheep. However, it must be cautiously adapted in cases where environmental, operating, and operator variables are not effectively controlled.

A study on the use of thermal imaging as a diagnostic tool for the detection of digital dermatitis in dairy cattle

Our aims were to (1) determine how interdigital skin temperature (IST), measured using infrared thermography, was associated with different stages of digital dermatitis (DD) lesions and (2) develop and validate models that can use IST measurements to identify cows with an active DD lesion. Between March 2019 and March 2020, infrared thermographic images of hind feet were taken from 2,334 Holstein cows across 4 farms. We recorded the maximum temperature reading from infrared thermographic images of the interdigital skin between the heel bulbs on the hind feet. Pregnant animals were enrolled approximately 1 to 2 mo precalving, reassessed 1 wk after calving, and again at approximately 50 to 100 d postpartum. At these time points, IST and the clinical stage of DD (M-stage scoring system: M1-M4.1) were recorded in addition to other data such as the ambient environmental temperature, height, body condition score, parity, and the presence of other foot lesions. A mixed effect linear regression model with IST as the dependent variable was fitted. Interdigital skin temperature was associated with DD lesions; compared to healthy feet, IST was highest in feet with M2 lesions, followed by M1 and M4.1 lesions. Subsequently, the capacity of IST measurements to detect the presence or absence of an active DD lesion (M1, M2, or M4.1) was explored by fitting logistic regression models, which were tested using 10-fold validation. A mixed effect logistic regression model with the presence of active DD as the dependent variable was fitted first. The average area under the curve for this model was 0.80 when its ability to detect presence of active DD was tested on 10% of the data that were not used for the model's training; an average sensitivity of 0.77 and an average specificity of 0.67 was achieved. This model was then restricted so that only explanatory variables that could be practically recorded in a nonresearch, external setting were included. Validation of this model demonstrated an average area under the curve of 0.78, a sensitivity of 0.88, and a specificity of 0.66 for 1 of the time points (precalving). Lower sensitivity and specificity were achieved for the other 2 time points. Our study adds further evidence to the relationship between DD and foot skin temperature using a large data set with multiple measurements per animal. Additionally, we highlight the potential for infrared thermography to be used for routine on-farm diagnosis of active DD lesions.

The Effects of Vehicle Type, Transport Duration and Pre-Transport Feeding on the Welfare of Sheep Transported in Low Temperatures

Low temperatures can provide a risk to the welfare of sheep during transport because of increased ventilation chilling the sheep, and we examined the importance of three factors-covering the vehicle, duration of transport, and feeding prior to transport-on the welfare of sixty transported 4-month-old Dorper × Mongolian female sheep in a cold climate. Sheep in a covered vehicle had greater increases in head and ear temperatures than those in an open vehicle. Sheep transported for 2 h increased their leg temperatures, whereas those transported for 1 h had reduced leg temperatures. Increases in non-esterified fatty acids (NEFA) and lactate dehydrogenase (LDH) in the blood samples during the long transport suggested that sheep had more muscular and metabolic activity, compromising their well-being. Feeding prior to transport did not affect body temperatures, but those not fed prior to transport had reduced alanine transferase, HSP and cortisol in their blood, whereas those that were fed had reduced NEFAs, LDH and creatine kinase. Prior feeding had no effect on the sheep temperature indices over a two-hour transport period. Thus, the sheep most at risk of the adverse effects of cold temperatures were those transported in open vehicles, those transported for a longer time, and those not fed before transport.

Non-Invasive Cattle Body Temperature Measurement Using Infrared Thermography and Auxiliary Sensors

To achieve a sensitive and accurate method in body temperature measurement of cattle, this study explores the uses of infrared thermography (IRT), an anemometer, and a humiture meter as a multiple sensors architecture. The influence of environmental factors on IRT, such as wind speed, ambient temperature, and humidity, was considered. The proposed signal processes removed the IRT frames affected by air flow, and also eliminated the IRT frames affected by random body movement of cattle using the frame difference method. In addition, the proposed calibration method reduced the impact of ambient temperature and humidity on IRT results, thereby increasing the accuracy of IRT temperature. The difference of mean value and standard deviation value between recorded rectal reference temperature and IRT temperature were 0.04 °C and 0.10 °C, respectively, and the proposed system substantially improved the measurement consistency of the IRT temperature and reference on cattle body temperature. Moreover, with a relatively small IRT image sensor, the combination of multiple sensors architecture and proper data processing still achieved good temperature accuracy. The result of the root-mean-square error (RMSE) was 0.74 °C, which is quite close to the accurate result of the IRT measurement.

A Review: Development of Computer Vision-Based Lameness Detection for Dairy Cows and Discussion of the Practical Applications

The computer vision technique has been rapidly adopted in cow lameness detection research due to its noncontact characteristic and moderate price. This paper attempted to summarize the research progress of computer vision in the detection of lameness. Computer vision lameness detection systems are not popular on farms, and the accuracy and applicability still need to be improved. This paper discusses the problems and development prospects of this technique from three aspects: detection methods, verification methods and application implementation. The paper aims to provide the reader with a summary of the literature and the latest advances in the field of computer vision detection of lameness in dairy cows.

Randomized controlled trial comparison of analgesic drugs for control of pain associated with induced lameness in lactating dairy cattle

Both the economic loss and welfare implications of lameness affect the dairy industry. Currently no analgesic drugs are approved to alleviate lameness-associated pain in lactating dairy cattle in the United States. In this randomized controlled trial, 48 lactating Holsteins were enrolled to evaluate the effect of oral meloxicam and i.v. flunixin meglumine on induced lameness. Cows were allocated to 1 of 4 treatment groups (n = 12 per group): lameness and flunixin meglumine (LAME + FLU); lameness and meloxicam (LAME + MEL); lameness and placebo (LAME + PLBO); or sham induction and placebo (SHAM + PLBO). Six hours before treatment, arthritis-synovitis was induced in the distal interphalangeal joint with 20 mg of amphotericin B, whereas SHAM cows were given an intra-articular injection of an equal volume (4 mL) of isotonic saline. Cows in LAME + FLU received 2.2 mg/kg flunixin meglumine i.v. and whey protein placebo orally; LAME + MEL were administered 1 mg/kg meloxicam orally and 2 mL/45 kg sterile saline placebo i.v.; LAME + PLBO were administered 2 mL/45 kg sterile saline placebo i.v. and whey protein placebo orally; and SHAM + PLBO received 2 mL/45 kg sterile saline placebo i.v. and whey protein placebo orally. The initial treatment of MEL, FLU, or PLBO was identified as time 0 h and followed by a second dose 24 h later with data collection for 120 h. The methods used to assess analgesic efficacy were electronic pressure mat, visual lameness assessment, visual analog score, plasma cortisol concentration, plasma substance P concentration, mechanical nociception threshold, and infrared thermography imaging. Linear mixed effect modeling was the primary method of statistical analysis. Visual lameness scoring indicated a lower proportion of the FLU + LAME group was lame at the T2 h and T8 h time points in comparison to the positive controls, whereas MEL therapy resulted in a lower proportion of lame cows at the T8 h time point. Cortisol area under the effect curve was lower following FLU therapy compared with LAME + PBLO for the 0-2 h (LSM difference = 35.1 ng·h/mL, 95% CI: 6.8, 63.3 ng·h/mL), 2-8 h (LSM difference = 120.6 ng·h/mL, 95% CI: 77.2, 164.0 ng·h/mL), and 0-24 h (LSM difference = 226.0 ng·h/mL, 95% CI: 103.3, 348.8 ng·h/mL) time intervals. Following MEL therapy, cortisol area under the effect curve was lower than LAME + PLBO for both the 2 to 8 h (LSM difference = 93.6 ng·h/mL, 95% CI: 50.2, 137.0 ng·h/mL) and 0 to 24 h time intervals (LSM difference = 187.6 ng·h/mL, 95% CI: 64.9, 310.4 ng·h/mL). Analysis of data from other assessment modalities failed to discern biologically relevant differences between treatment groups. We conclude that meaningful differences were evident for visual lameness assessment and cortisol from MEL and FLU treatment versus the positive control. Further clinical research is needed toward development of a model that will create reproducible events that are more pronounced in severity and duration of lameness which can be validated as a substitute for naturally occurring lameness cases.

Different methods of assessing udder temperature through thermography and their relation with rectal temperature

Infrared thermography of the lateral side portion of the udder was taken from 38 lactating cows in a 6-day experiment. Thermograms were analyzed using specific software with the use of eight different methods. The experiment was aimed at correlating the different methods with each other and with rectal temperature (RT), in order to suggest a method to assess udder side temperature, and also at creating regression equations to enable RT calculation through the use of thermographic data. All methods of analyzing thermograms were highly correlated; correlations between thermograms and RT were significant (P < 0.01) and above 0.840. The highest correlation was between RT and the maximum temperature obtained using a horizontal rectangle placed within the lateral (side) portion of the udder (maximum temperature in a horizontal rectangle (MHR), 0.897). With the exception of the average temperature of a horizontal rectangle, linear regression coefficients were significant (P < 0.05) and coefficients of determination were higher than 75.51%. We suggest the use of MHR to evaluate udder side temperature. The ease of accessing the side of the udder, the welfare advantages of non-invasive observations, and the high correlation with RT suggest the use of thermograms in the lateral portion of the udder to assess animals' temperature.

Image Analysis and Computer Vision Applications in Animal Sciences: An Overview

Computer Vision, Digital Image Processing, and Digital Image Analysis can be viewed as an amalgam of terms that very often are used to describe similar processes. Most of this confusion arises because these are interconnected fields that emerged with the development of digital image acquisition. Thus, there is a need to understand the connection between these fields, how a digital image is formed, and the differences regarding the many sensors available, each best suited for different applications. From the advent of the charge-coupled devices demarking the birth of digital imaging, the field has advanced quite fast. Sensors have evolved from grayscale to color with increasingly higher resolution and better performance. Also, many other sensors have appeared, such as infrared cameras, stereo imaging, time of flight sensors, satellite, and hyperspectral imaging. There are also images generated by other signals, such as sound (ultrasound scanners and sonars) and radiation (standard x-ray and computed tomography), which are widely used to produce medical images. In animal and veterinary sciences, these sensors have been used in many applications, mostly under experimental conditions and with just some applications yet developed on commercial farms. Such applications can range from the assessment of beef cuts composition to live animal identification, tracking, behavior monitoring, and measurement of phenotypes of interest, such as body weight, condition score, and gait. Computer vision systems (CVS) have the potential to be used in precision livestock farming and high-throughput phenotyping applications. We believe that the constant measurement of traits through CVS can reduce management costs and optimize decision-making in livestock operations, in addition to opening new possibilities in selective breeding. Applications of CSV are currently a growing research area and there are already commercial products available. However, there are still challenges that demand research for the successful development of autonomous solutions capable of delivering critical information. This review intends to present significant developments that have been made in CVS applications in animal and veterinary sciences and to highlight areas in which further research is still needed before full deployment of CVS in breeding programs and commercial farms.

Accurate detection of lameness in dairy cattle with computer vision: A new and individualized detection strategy based on the analysis of the supporting phase

Lameness has a considerable influence on the welfare and health of dairy cows. Many attempts have been made to develop automatic lameness detection systems using computer vision technology. However, these detection methods are easily affected by the characteristics of individual cows, resulting in inaccurate detection of lameness. Therefore, this study explores an individualized lameness detection method for dairy cattle based on the supporting phase using computer vision. This approach is applied to eliminate the influence of the characteristics of individual cows and to detect lame cows and lame hooves. In this paper, the correlation coefficient between lameness and the supporting phase is calculated, a lameness detection algorithm based on the supporting phase is proposed, and the accuracy of the algorithm is verified. Additionally, the reliability of this method using computer vision technology is verified based on deep learning. One hundred naturally walking cows are selected from video data for analysis. The results show that the correlation between lameness and the supporting phase was 0.864; 96% of cows were correctly classified, and 93% of lame hooves were correctly detected using the supporting phase-based lameness detection algorithm. The mean average precision is 87.0%, and the number of frames per second is 83.3 when the Receptive Field Block Net Single Shot Detector deep learning network was used to detect the locations of cow hooves in the video. The results show that the supporting phase-based lameness detection method proposed in this paper can be used for the detection and classification of cow lameness and the detection of lame hooves with high accuracy. This approach eliminates the influence of individual cow characteristics and could be integrated into an automatic detection system and widely applied for the detection of cow lameness.

A sampling strategy for the determination of infrared temperature of relevant external body surfaces of dairy cows

Infrared thermography is a tool to investigate the welfare of cattle. This study aimed to identify a sampling strategy for recording infrared thermograms in dairy cows, in order to most efficiently determine biologically relevant changes in the maximum infrared temperature (IRT) of the eyes and coronary band of forelimbs. Thirty-one dairy cows were used for the study. They were assessed with four replicates of thermograms for each of the head and lower forelimb per cow for 6 mostly consecutive days (sessions). The data obtained were subjected to random effects Analysis of Variance which was used to estimate the variance components for this sampling model, using maximum IRT of both eyes; (left + right eye)/2 and both limbs; (left + right coronary band of forelimb)/2 as dependant variables. The variance components were used to calculate least significant differences (LSD) between two theoretical treatment groups under different sampling scenarios. Analysis showed that there was minimal improvement in precision beyond 2 thermograms within a session but there was improvement with increasing the number of sessions from 2 to 3. The LSD of both eyes and both limbs reached a biologically relevant difference (0.4 and 0.9 °C, respectively) at a minimum number of 14 - 16 cows monitored for 2 consecutive thermography sessions, or 10 - 12 cows for 3 sessions. We conclude that no more than 2 replicate IRT measures are required per session but that measuring on 3 consecutive days should be considered, depending on whether time or number of cows used is the primary limitation.

[Taking body temperature in cattle - critical evaluation of an established diagnostic test]

Measuring the body temperature is an essential component of the clinical examination of bovines. Next to its value for the diagnosis of diseases, body temperature also is an important value in clinical studies concerning estrus detection, calving time point prediction, or the evaluation of heat stress. This systematic review critically evaluates different methods of measuring bovine body temperature including rectal measurement, vaginal or ruminal temperature loggers, milk temperature, and infrared body surface thermography. Although body temperature measurement is a commonly employed and established diagnostic test, a close look at scientific studies displays multiple factors influencing body temperature data. The variability of results emphasizes the relevance of critically evaluating new measuring methods before introducing them into research or routine practice. Especially in terms of identifying specific cut-off values, i. e. for fever defined as body temperature > 39.5°C, the precision of the method is of importance, as the acquired values possess a high degree of influence on the veterinary decision taking process.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

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.

Effects of hair coat characteristics on radiant surface temperature in horses

Horse owners may lack knowledge about natural thermoregulation mechanisms in horses. Horses are managed intensively; usually stabled at night and turned out during the day. Some are clipped and many wear a blanket, practices which reduce the horse's ability to regulate heat dissipation. The aim of this study was to investigate the relationship between hair coat characteristics, body condition and infrared surface temperatures from different body parts of horses. Under standard conditions, the body surface temperature of 21 adult horses were investigated using infrared thermography. From several readings on the same body part, a mean temperature was calculated for each body part per horse. Detailed information on horse breed, age, management and body condition was collected. Hair coat samples were also taken for analyses. A mixed statistical model was applied. Warmblood horse types (WB) had lower hair coat sample weights and shorter hair length than coldblood horse types (CB). The highest radiant surface temperatures were found at the chest 22.5 ± 0.9 °C and shoulders 20.4 ± 1.1 °C and WB horses had significantly higher surface temperatures than CB horses on the rump (P < 0.05). Horses with a higher hair coat sample weight had a lower surface temperature (P < 0.001) and hind hooves with iron shoes had a significant lower surface temperature than unshod hind hooves (P = 0.03). In conclusion, individual assessment of radiant surface temperature using infrared thermography might be a promising tool to gather data on heat loss from the horses' body. Such data may be important for management advice, as the results showed individual differences in hair coat characteristics and body condition in horses of similar breeds.

Aetiology, Risk Factors, Diagnosis and Control of Foot-Related Lameness in Dairy Sheep

During the last twenty years, considerable research efforts have recognized the consequences of foot-related lameness primarily in cattle, and meat and wool sheep. Despite the lack of extensive epidemiological studies, field observations and isolated research reports in dairy sheep have suggested that the problem might be more severe in semi-intensive and intensive farming systems. Footrot, contagious ovine digital dermatitis, ovine interdigital dermatitis, white line disease, and pedal joint abscess are the most common causes of foot-related lameness. Dichelobacter nodosus, Fusobacterium necrophorum, Treponema spp., and Actinomyces pyogenes are the most significant foot-related lameness-associated pathogens. Despite a documented hereditary predisposition, environmental factors are the most important in determining the occurrence of foot-related lameness. Moist and warm environment, increased parity and milk yield, inappropriate housing conditions and infrastructures, inadequate hygiene status, imbalanced nutrition, and insufficient foot care are the most critical risk factors. Furthermore, a foot-lameness control plan should include targeted implementation of claw trimming and footbathing, evidence-based planning of hygiene measures in preventive veterinary practices (i.e., antibiotic administration, vaccinations against footrot), selective breeding to footrot resistance, and, most importantly, the continuous training of farming personnel. Controlling foot-lameness in dairy sheep is critical in determining the well-being of animals, and strongly affects the farm's profitability and sustainability.

Risk Factors and Detection of Lameness Using Infrared Thermography in Dairy Cows – A Review

Lameness in dairy cows is a worldwide problem, usually a consequence of hoof diseases. Hoof problems have a negative impact on animal health and welfare as well as the economy of the farm. Prevention and early diagnosis of lameness should prevent the development of the disease and consequent high costs of animal treatment. In this review, the most common causes of both infectious and noninfectious lesions are described. Susceptibility to lesions is primarily influenced by the quality of the horn. The quality of the horn is influenced by internal and external conditions such as hygiene, nutrition, hormonal changes during calving and lactation, the animal’s age or genetic predisposition. The next part of this review summarizes the basic principles and possibilities of using infrared thermography in the early detection of lameness in dairy cows.

The Use of Infrared Thermography for the Monitoring of Udder Teat Stress Caused by Milking Machines

Simple Summary

The aim of this study was to test the use of infrared thermography as a possible tool for detecting short-term stress, of cow udder teat, caused by milking procedures. Thermographic images were collected and evaluated to calculate the values of two indicators: the average and the maximum skin surface temperatures at the base, center, and tip of each teat. Obtained results confirmed a relationship between the two indicators (T_avg, T_max) and the level of teat stress generally evaluated by visual observation of its color. Nevertheless, the low accuracy reached by the two indicators does not seem to justify the development of an ad hoc infrared device for the monitoring of cow udder teat stress.

Abstract

The aim of this study was to test infrared thermography (IRT) as a possible tool for scoring teat color changes after cluster removal; thus, indirectly, to classify the short-term stress of teats caused by milking machines. Thermographic images (n = 137) from three farms were collected and evaluated to calculate the average and maximum skin surface temperatures (SSTs) at the base, center, and tip of each teat (T_avg,B, T_avg,C, T_avg,T, T_max,B, T_max,C, and T_max,T). Obtained results confirmed a significant relationship between the indicators T_avg, T_max and the levels of teat color change (level one: pink-colored teat; level two: red-colored teat; level three: blue or purple-colored teat). Nevertheless, when a teat was considered to be stressed because its scoring fell in level 3 of the color-change scale used, sensitivity and specificity in the classification of the teat status ranged respectively between 45.6% and 54.3%, and 54.4% and 59.2%, for the indicators T_avg; and 56.5% and 60.9%, and 59.7% and 61.8%, for the indicators T_max. When a teat was considered stressed because its scoring fell between the levels 2 and 3 of the scale adopted, sensitivity and specificity were between 49.0% and 55.8%, and 58.3% and 61.8%, for the indicators T_avg; and 55.8% and 59.9%, and 60.6% and 61.4%, for the indicators T_max. As a consequence, the low values of sensitivity and specificity do not seem to justify the development of an ad hoc infrared device for the monitoring of udder teat stress. Nonetheless, this technology can be a viable solution for a preliminary evaluation of the mechanical stress of teats if a milking system would be equipped with an infrared sensor already in place for other purposes (e.g., the monitoring of udder health status).

Effects of transdermal flunixin meglumine on experimentally induced lameness in adult dairy cattle

Lameness is a common animal health condition with significant production and welfare implications. The transdermal formulation of flunixin meglumine is the only approved drug for pain control in cattle in the United States. Thirty adult dairy cows were enrolled in a study to determine the effect of transdermal flunixin on cattle with induced lameness. Cows were allocated to 1 of 3 treatment groups, with 10 cows per group: lameness and flunixin (L+F), lameness and placebo (L+P), or sham induction and placebo (S+P). An arthritis-synovitis was induced in the distal interphalangeal joint of the left hind lateral digit, using 20 mg of amphotericin B, 6 h before the application of treatment. Cows enrolled into the sham induction group had 4 mL of isotonic saline injected into the joint. Cows were dosed with transdermal flunixin at 3.33 mg/kg (1 mL/15 kg), or a placebo at 1 mL/15 kg, every 24 h for 3 d. The first treatment of flunixin or placebo was considered the start of the study, identified as time 0 h. Data were collected from all cows for 120 h following the initial treatment application. Outcome measures included plasma cortisol; substance P; visual lameness assessment; mechanical nociception threshold (MNT), presented as difference between left and right feet; infrared thermography (IRT), presented as difference between left and right feet; and gait analysis using a pressure mat. Cortisol concentrations were lower for the L+F group starting at 1.5 h after drug administration. Substance P levels showed no evidence for treatment differences among groups. Differences between the left hind MNT and right hind MNT were detected, with S+P having the lowest difference at -0.04 kilograms-force (kgf; 95% CI: -1.86 to 1.78 kgf), and L+P having the highest at -2.96 kgf (95% CI: 1.55 to 4.36 kgf). The L+F group was intermediate at -2.08 kgf (95% CI: 0.89 to 3.27 kgf). Similarly, when the difference between the maximum temperatures of the coronary band were examined via IRT, the L+P group had the highest difference at 1.64°C (95% CI: 1.02 to 2.26°C), with the L+F and S+P groups measuring 0.57°C (95% CI: 0.06 to 1.08°C) and 0.53°C (95% CI: -0.2 to 1.25°C) respectively. We found no evidence for differences among treatment groups when analyzing force, contact pressure, step impulse, or stride length. Based on differences in MNT, IRT, and cortisol, transdermal flunixin is an effective analgesic agent for induced lameness. Multiple doses of transdermal flunixin may be required to be clinically effective, based on MNT and IRT data. Further investigation of transdermal flunixin and its analgesic effects is warranted in naturally occurring lameness.

Interobserver agreement of digital dermatitis M-scores for photographs of the hind feet of standing dairy cattle

Digital dermatitis (DD) is the leading infectious cause of lameness in dairy cattle, and it affects their welfare and productivity worldwide. At the herd level, DD is often assessed while cows are standing in a milking parlor, and lesions are most commonly evaluated using the M-score. The objective of this study was to examine the interobserver agreement for M-scores of the feet of standing cattle, based on digital color photographs of dairy cattle hind feet. A total of 88 photographs and written descriptors of the M-score were sent to 11 scorers working at 10 different institutions in 5 countries. The scorers received no formal training immediately before scoring the photographs; however, all regularly used the M-score to score DD. The answers for 36 photographs were excluded from the analysis because the photograph either had more than 1 M-stage as mode or not all scorers assigned an M-score to it. The M-scores of the 11 scorers from 52 photographs were available for analysis. Interobserver agreement was tested using Gwet's agreement coefficient (AC1) and the mode was assumed correct. Overall, moderate agreement emerged for the M-score (AC1 = 0.48). For the individual M-stages, almost perfect agreement existed for M0 (AC1 = 0.99), M1 (AC1 = 0.92), and M3 (AC1 = 0.82), and substantial agreement for M2 (AC1 = 0.61), M4 (AC1 = 0.65), and M4.1 (AC1 = 0.71). This outcome indicates the degree of individual variation in M-scoring in this context by unstandardized, experienced European observers, particularly for the M2, M4, and M4.1 stages. Standardized training is likely to improve the consistency of M-scoring and thus the generalizability of future DD research results on this important endemic disease.

Precision Livestock Farming in Swine Welfare: A Review for Swine Practitioners

Simple Summary

The increasing implementation of technological advances originally developed for video gaming (PlayStation, Xbox) is helping to progress livestock production so that it is both more efficient and more focused on the welfare of the animals. Such advances are necessary to ensure that innovations can emerge from applications using cameras, microphones and sensors to enhance the farmers’ eyes, ears and nose in everyday farming. This technology for remote monitoring of livestock, termed precision livestock farming, is the ability to automatically track individual livestock in real time. The goal of this review is to apprise swine veterinarians and their clientele on precision livestock farming with a general introduction to the technology available, a review of research and commercially available technology and the implications and opportunities for swine practitioners and farmers. Drawing from pig welfare criteria in the Common Swine Industry Audit, this review explains how these applications can be used to improve swine welfare within current pork production stakeholder expectations. Swine veterinarians and specialists, by virtue of their animal advocacy role, interpretation of benchmarking data, and stewardship in regulatory and commodity programs, can play a broader role in facilitating the transfer of precision livestock farming and technology to their clients.

Abstract

The burgeoning research and applications of technological advances are launching the development of precision livestock farming. Through sensors (cameras, microphones and accelerometers), images, sounds and movements are combined with algorithms to non-invasively monitor animals to detect their welfare and predict productivity. In turn, this remote monitoring of livestock can provide quantitative and early alerts to situations of poor welfare requiring the stockperson’s attention. While swine practitioners’ skills include translation of pig data entry into pig health and well-being indices, many do not yet have enough familiarity to advise their clients on the adoption of precision livestock farming practices. This review, intended for swine veterinarians and specialists, (1) includes an introduction to algorithms and machine learning, (2) summarizes current literature on relevant sensors and sensor network systems, and drawing from industry pig welfare audit criteria, (3) explains how these applications can be used to improve swine welfare and meet current pork production stakeholder expectations. Swine practitioners, by virtue of their animal and client advocacy roles, interpretation of benchmarking data, and stewardship in regulatory and traceability programs, can play a broader role as advisors in the transfer of precision livestock farming technology, and its implications to their clients.

Automatic lameness detection in cattle

There is an increasing demand for health and welfare monitoring in modern dairy farming. The development of various innovative techniques aims at improving animal behaviour monitoring and thus animal welfare indicators on-farm. Automated lameness detection systems have to be valid, reliable and practicable to be applied in veterinary practice or under farm conditions. The objective of this literature review was to describe the current automated systems for detection of lameness in cattle, which have been recently developed and investigated for application in dairy research and practice. The automatic methods of lameness detection broadly fall into three categories: kinematic, kinetic and indirect methods. The performance of the methods were compared with the reference standard (locomotion score and/or lesion score) and evaluated based on level-based scheme defining the degree of development (level I, sensor technique; level II, validation of algorithm; level III, performance for detection of lameness and/or lesion; level IV, decision support with early warning system). Many scientific studies have been performed on levels I-III, but there are no studies of level IV technology. The adoption rate of automated lameness detection systems by herd managers mainly yields returns on investment by the early identification of lame cows. Long-term studies, using validated automated lameness detection systems aiming at early lameness detection, are still needed in order to improve welfare and production under field conditions.

Monitoring foot surface temperature using infrared thermal imaging for assessment of hoof health status in cattle: A review

Detection of lameness early in cows is important from the animal welfare point of view and for reducing economic losses. Currently, many studies are being conducted for assessment of hoof health status by measuring the surface temperature of skin in cattle and other animal species in different parts of the world. Infrared Thermography (IRT) is able to detect lesions of hooves associated with lameness by measuring the changes in coronary band and hoof skin surface temperature. The surface temperature of a lame limb will be increased when the hoof has lesion(s). IRT has been used as a non-invasive diagnostic tool for early detection of hoof lesions based on the temperature difference between affected and non-affected hoof and maximum foot temperature on the regions of interest. In spite of having many potential applications in cattle production, factors affecting the temperature readings in thermograms must also are considered while taking images. Standard operating procedures must be established before taking thermographs under different circumstances, by considering all the factors that affect its normal function. IRT may help in minimising the cost of veterinary services, low yield, compromised fertility and culling expenses, where lameness cannot be resolved in early stages.

Dairy cattle welfare as a result of human-animal relationship – a review

Despite the various concepts of human-animal relationship, the welfarist approach to this problem is one of the most often considered in theory and used in practice. When dealing with issues related to dairy cattle welfare (DCW), it is necessary to take into account both the reality characteristic for animals used to obtain milk (e.g. the problem of automatic milking of cows) and for slaughter cattle (e.g. slaughter of culled animals). It is not surprising, therefore, that issues related to DCW are the focus of the attention of the public, researchers, breeders as well as the dairy and meat industries. The aim of this article was to possibly most comprehensively cover the above-mentioned issues, although due to its huge scope it was obviously necessary to limit the article to what I think are currently most important issues. That is why in the review I (1) characterized the issues related to the division of human responsibility for DCW; (2) discussed the importance of technology to human-animal relationship; (3) elaborated the matter of stress, emotionality of animals and their cognitive abilities in the aspect of “negative” and “positive” DCW; (4) considered the possibilities of non-invasive assessment of animal welfare in the future and (5) discussed topics related to improving the conditions of the slaughter of animals. In summary, it was proposed paying more attention than has been paid until now, to the assessment of positive DCW in scientific research and breeding practice. I also drew attention to the necessity of reliable information flow on the line of the breeder/milk producer - industry - consumer, as negligence in this area is one of the reasons for public disinformation regarding the level of animal welfare.

The use of infrared thermography for detecting digital dermatitis in dairy cattle: What is the best measure of temperature and foot location to use?

Lameness in dairy cattle is a persistent problem, indicating pain caused by underlying disease states and is associated with reduced milk yields. Digital dermatitis is a common cause of lameness. Thermal imaging is a technique that may facilitate early detection of this disease and has the potential for use in automated detection systems. Previous studies with thermal imaging have imaged either the heels or the coronary band of the foot and typically only used the maximum temperature (Max) value as the outcome measure. This study investigated the utility of other statistical descriptors: 90th percentile (90PCT), 95th percentile (95PCT), standard deviation (SD) and coefficient of variation (CoV) and compared the utility of imaging the heel or coronary band. Images were collected from lame and healthy cows using a high-resolution thermal camera. Analyses were done at the cow and foot level. There were significant differences between lame and healthy feet detectable at the heels (95th percentile: P<0.05; SD: P<0.05) and coronary band (SD: P<0.05). Within lame cows, 95PCT values were higher at the heel (P<0.05) and Max values were higher at the coronary band (P<0.05) in the lame foot compared to the healthy foot. ROC analysis showed an AUC value of 0.72 for Max temperature and 0.68 for 95PCT at the heels. It was concluded that maximum temperature is the most accurate measure, but other statistical descriptors of temperature can be used to detect lameness. These may be useful in certain contexts, such as where there is contamination. Differentiation of lame from healthy feet was most apparent when imaging the heels.

First Evaluation of Infrared Thermography as a Tool for the Monitoring of Udder Health Status in Farms of Dairy Cows

The aim of the present study was to test infrared thermography (IRT), under field conditions, as a possible tool for the evaluation of cow udder health status. Thermographic images (n. 310) from different farms (n. 3) were collected and evaluated using a dedicated software application to calculate automatically and in a standardized way, thermographic indices of each udder. Results obtained have confirmed a significant relationship between udder surface skin temperature (USST) and classes of somatic cell count in collected milk samples. Sensitivity and specificity in the classification of udder health were: 78.6% and 77.9%, respectively, considering a level of somatic cell count (SCC) of 200,000 cells/mL as a threshold to classify a subclinical mastitis or 71.4% and 71.6%, respectively when a threshold of 400,000 cells/mL was adopted. Even though the sensitivity and specificity were lower than in other published papers dealing with non-automated analysis of IRT images, they were considered acceptable as a first field application of this new and developing technology. Future research will permit further improvements in the use of IRT, at farm level. Such improvements could be attained through further image processing and enhancement, and the application of indicators developed and tested in the present study with the purpose of developing a monitoring system for the automatic and early detection of mastitis in individual animals on commercial farms.

A Review of the Relationship Between Hoof Trimming and Dairy Cattle Welfare

A narrative integrative review on the evidence for hoof trimming found 16 articles on efficacy, frequency, and associations with behavior and physiologic parameters. Review of these studies revealed (1) hoof trimming is associated with behavior and physiologic changes; (2) increasing the frequency of hoof trimming seems to decrease the incidence of hoof lesions; (3) there is limited research to support any particular technique; and (4) descriptions of the hoof trimming techniques used is inadequate in most articles. To increase scientific support for hoof trimming practices, current knowledge gaps in technique, timing, and frequency of hoof trimming need to be addressed.

The use of infrared images to detect ticks in cattle and proposal of an algorithm for quantifying the infestation

This paper presents a study on the use of low resolution infrared images to detect ticks in cattle. Emphasis is given to the main factors that influence the quality of the captured images, as well as to the actions that can increase the amount of information conveyed by these images. In addition, a new automatic method for analyzing the images and counting the ticks is introduced. The proposed algorithm relies only on color transformations and simple mathematical morphology operations, thus being easy to implement and computationally light. Tests were carried out using a large database containing images of the neck and hind end of the animals. It was observed that the proposed algorithm is very effective in detecting ticks visible in the images, even if the contrast with the background is not high. On the other hand, due to both intrinsic and extrinsic factors, the thermographic images used in this study did not always succeed in creating enough contrast between ticks and cattle's hair coat. Although these problems can be mitigated by following some directives, currently only rough estimates for tick counts can be achieved using infrared images with low spatial resolution.

A single prolonged milking interval of 24h compromises the well-being and health of dairy Holstein cows

Cows are often shown at dairy shows with overfilled udders to achieve a better show placing. However, it is unclear to what degree "over-bagging" affects the health and well-being of show cows. The goal of this study was to assess the effect of a single prolonged milking interval (PMI) of 24h on the measurable signs of health and well-being in dairy cows in early and mid-lactation and to assess the effect of a nonsteroidal anti-inflammatory drug (NSAID) on well-being during a PMI. Fifteen Holstein cows were studied in early lactation (89.5±2.7d in milk) and were given an NSAID or physiological saline in a crossover design. Ten cows were studied again in mid-lactation (151.6±4.0d in milk). Data on clinical signs of cows' health, behavior, and well-being were collected at 1 or 2h intervals before and during a PMI of 24h. Data from the last 6h of a 12h milking interval were compared with the last 6h of the PMI. Compared with that of a cow in the last 6h of a 12-h milking interval, the behavior of cows in early lactation (saline group) changed during the last 6h of the PMI: we observed decreased eating time (22.4 vs. 16.2min/h), increased ruminating time (13.3 vs. 25.0min/h), and increased hind limb abduction while walking (score 41.7 vs. 62.6) and standing (31.2 vs. 38.9cm). Udder firmness was increased (2.9 vs. 4.5kg) during this period and more weight was placed on the hind limbs (46.4 vs. 47.0%). We also found pathological signs at the end of the PMI: all cows showed milk leaking, and 10 of 15 cows developed edema in the subcutaneous udder tissue. Somatic cell count was significantly increased from 12h to 72h after the PMI. Administration of an NSAID had no influence on measured variables, except that the occurrence of edema was not significantly increased during PMI in the flunixin group (10 of 15 and 6 of 15 cows for the saline and flunixin groups, respectively). In the cows in mid-lactation, different variables were not significantly changed in the PMI compared with baseline values (e.g., eating and ruminating time, occurrence of edema, and abduction). We conclude that the cows' health and well-being were compromised by a single PMI of 24h, because their behavior changed and pathological signs were recorded. Administration of an NSAID had a slight effect on cows' well-being during a PMI. The stage of lactation had more effect on the cows' health and well-being, because fewer variables were changed in mid-lactation.

Assessment of foot health and animal welfare: clinical findings in 229 dairy Mediterranean Buffaloes (Bubalus bubalis) affected by foot disorders

BACKGROUND

Lameness represents the third most important health-related cause of economic loss in the dairy industry after fertility and mastitis. Although, dairy Mediterranean Buffaloes (MB) and dairy cows share similar breeding systems predisposing to similar herd problems, published studies exploring its relevance and role in these ruminants are still rare and incomplete. The aims of this study were to describe the clinical findings of foot disorders (FDs) in dairy MB and their influence on animal welfare, determined by assessment of locomotion score (LS), body condition score (BCS) and cleanliness score (CS).

RESULTS

Of 1297 multiparous MB submitted to routine trimming procedures, 229 buffaloes showed at least one FD. The prevalence of buffaloes affected by FDs was 17.7 %, while motility and lameness indexes were 84.1 % (1091/1297) and 15.9 % (206/1297), respectively. Overgrowth was present in 17.0 % (220/1297), corkscrew claw in 15.8 % (205/1297), interdigital phlegmon in 0.9 % (12/1297), white line abscess in 0.8 % (11/1297), digital dermatitis in 0.1 % (1/1297) and interdigital hyperplasia in 0.1 % (1/1297). Simultaneous presence of FDs was recorded in 17.0 % of MB (221/1297): overgrowth and corkscrew claw occurred together in 15.8 % of cases (205/1297), overgrowth and interdigital phlegmon in 0.3 % (4/1297), overgrowth and white line abscess in 0.8 % (11/1297), digital dermatitis and interdigital hyperplasia in 0.1 % (1/1297). The presence of FDs was always associated with lameness (LS > 2), except from 23 MB with simultaneous overgrowth and interdigital phlegmon occurrence. The majority of MB within the under-conditioned group (95.5 %, 43/45) and all those with CS > 2 (122/122) had a locomotion score above the threshold of normality (LS > 2). Furthermore, foot diseases such as interdigital hyperplasia, white line abscess and digital dermatitis or interdigital hyperplasia seemed to occur more frequently associated with decreased BCS and increased CS scores.

CONCLUSIONS

This study describes for the first time the involvement of white line disease, interdigital phlegmona, digital dermatitis and interdigital hyperplasia in foot disorders of dairy Mediterranean buffalo and shows their association with an impairment of animal welfare.

The Role of Infrared Thermography as a Non-Invasive Tool for the Detection of Lameness in Cattle

The use of infrared thermography for the identification of lameness in cattle has increased in recent years largely because of its non-invasive properties, ease of automation and continued cost reductions. Thermography can be used to identify and determine thermal abnormalities in animals by characterizing an increase or decrease in the surface temperature of their skin. The variation in superficial thermal patterns resulting from changes in blood flow in particular can be used to detect inflammation or injury associated with conditions such as foot lesions. Thermography has been used not only as a diagnostic tool, but also to evaluate routine farm management. Since 2000, 14 peer reviewed papers which discuss the assessment of thermography to identify and manage lameness in cattle have been published. There was a large difference in thermography performance in these reported studies. However, thermography was demonstrated to have utility for the detection of contralateral temperature difference and maximum foot temperature on areas of interest. Also apparent in these publications was that a controlled environment is an important issue that should be considered before image scanning.

Effect of routine claw trimming on claw temperature in dairy cows measured by infrared thermography

Infrared thermography (IRT) was used to assess the effect of routine claw trimming on claw temperature. In total, 648 IRT observations each were collected from 81 cows housed in 6 tiestalls before and 3 wk after claw trimming. The feet were classified as either healthy (nonlesion group, n = 182) or affected with infectious foot disorders (group IFD, n = 142). The maximal surface temperatures of the coronary band and skin and the difference of the maximal temperatures (ΔT) between the lateral and medial claws of the respective foot were assessed. Linear mixed models, correcting for the hierarchical structure of the data, ambient temperature, and infectious status of the claws, were developed to evaluate the effect of time in relation to the trimming event (d 0 versus d 21) and claw (medial versus lateral). Front feet and hind feet were analyzed separately. Ambient temperature and infectious foot status were identified as external and internal factors, respectively, that significantly affected claw temperature. Before claw trimming, the lateral claws of the hind feet were significantly warmer compared with the medial claws, whereas such a difference was not evident for the claws of the front feet. At d 21, ΔT of the hind feet was reduced by ≥ 0.25 °C, whereas it was increased by ≤ 0.13 °C in the front feet compared with d 0. Therefore, trimming was associated with a remarkable decrease of ΔT of the hind claws. Equalizing the weight bearing of the hind feet by routine claw trimming is associated with a measurable reduction of ΔT between the paired hind claws.