Digital Dermatitis In Dairy Cows Research Articles

Benchmarking analysis of computer vision algorithms on edge devices 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 coronary band of the foot. It causes significant animal welfare and economic losses to the cattle industry. Early detection of DD can lead to prompt treatment and decrease lameness. Current detection and staging methods require a trained individual to evaluate the interdigital space on each foot for clinical signs of DD. Computer vision (CV), a type of artificial intelligence for image analysis, has demonstrated promising results on object detection tasks. However, farms require robust solutions that can be deployed in harsh conditions including dust, debris, humidity, precipitation, other equipment issues. The study aims to train, deploy, and benchmark DD detection models on edge devices. Images were collected from commercial dairy farms with the camera 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. Models were trained to detect and score DD lesions and embedded on an edge device. The Tiny YOLOv4 model deployed on a CV specific integrated camera module connected to a single board computer achieved a mean average precision (mAP) of 0.895, an overall prediction accuracy of 0.873, and a Cohen’s kappa of 0.830 for agreement between the computer vision model and the trained investigator. The model reached a final inference speed of 40 frames per second (FPS) and ran stably without any interruptions. The CV model was able to detect DD lesions on an edge device with high performance and speed. The CV tool can be used for early detection and prompt treatment of DD in dairy cows. Real-time detection of DD on edge device will improve health outcomes, while simultaneously decreasing labor costs. We demonstrate that the deployed model can be a low-power and portable solution for real-time detection of DD on dairy farms. This result is a step towards applying CV algorithms to veterinary medicine and implementing real-time detection of health outcomes in precision farming.

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.

Machine learning approaches to predict and detect early-onset of digital dermatitis in dairy cows using sensor data.

The present study aimed to employ machine learning algorithms based on sensor behavior data for (1) early-onset detection of digital dermatitis (DD) and (2) DD prediction in dairy cows. Our machine learning model, which was based on the Tree-Based Pipeline Optimization Tool (TPOT) automatic machine learning method, for DD detection on day 0 of the appearance of the clinical signs has reached an accuracy of 79% on the test set, while the model for the prediction of DD 2 days prior to the appearance of the first clinical signs, which was a combination of K-means and TPOT, has reached an accuracy of 64%. The proposed machine learning models have the potential to help achieve a real-time automated tool for monitoring and diagnosing DD in lactating dairy cows based on sensor data in conventional dairy barn environments. Our results suggest that alterations in behavioral patterns can be used as inputs in an early warning system for herd management in order to detect variances in the health and wellbeing of individual cows.

Efficacy of quaternary ammonium salt-based disinfectant or chelated copper-zinc footbath solution in the treatment of digital dermatitis on one research dairy farm in Taiwan.

Footbaths can be used to manage digital dermatitis (DD), a common cause of lameness in dairy cattle. Copper sulfate and chelated copper-zinc (CZS) solutions in footbaths are potentially harmful to the environment. To determine if a quaternary ammonium salt-based disinfectant (QASD) footbath is as effective as a chelated CZS solution in controlling DD in dairy cows. Fifty-one lactating Holstein cows were randomly assigned to one of two treatment groups, with DD status based on the M-stage scoring system and locomotion score balanced between treatment groups. The groups were treated with a 1% QASD or a 2.5% chelated CZS. Footbaths were performed once per week for 15 weeks. Logistic regression was used to analyse clinical improvement. All cows received appropriate medical treatment for DD and other hoof diseases. Clinical improvement rates were 67% in the QASD group and 38% in the CZS group (p = 0.03). Logistic regression analysis showed that the odds (95% confidence interval) for clinical improvement rate in the CZS group were 0.30 (0.095-0.948) times that of the QASD group (p = 0.04). The M0 score in the QASD and CZS groups increased significantly (p < 0.05) at the end of the 15 week study period. In the QASD group, the proportion of M2, M3 and M4 scores were significantly decreased (p < 0.05). Over a 15 week period, QASD for footbathing was associated with a lower prevalence of active DD lesions than when using CZS.

Farm-level risk factors for digital dermatitis in dairy cows in mountainous regions

Reduction of risk factors for bovine digital dermatitis (BDD) is crucial in current disease control. However, risk factors that might arise especially in mountainous regions are unknown until now, and an adapted BDD control program is consequently missing. The objective of this observational case-control study was to identify farm-level risk factors for BDD in dairy herds in mountainous regions. To investigate predictors for the occurrence of BDD, 100 farms were visited and information about herd characteristics and management practices, potentially relevant explanatory variables for either introduction or establishment of BDD, were gathered by completing a questionnaire with the farmer or herd manager. Within-herd prevalences of BDD assessed during 3 routine claw trimmings with an interval of 6 mo before the survey were used to define cases (BDD within-herd prevalence of ≥26% during each claw trimming) and controls (no BDD cases in each of the 3 routine claw trimmings before the survey). Data were analyzed using 2 separate binomial generalized linear models according to either establishment or introduction of BDD. After prescreening, 15 of 23 explanatory variables were included in the final analysis, which showed 3 variables related to introduction and establishment, each being significantly associated with the occurrence of BDD within a farm. Results of model 1 (i.e., aspects related to BDD introduction) revealed that access to mountain pastures during the summer season (odds ratio, 95% confidence interval: 0.12, 0.04-0.35), participation in dairy shows (0.32, 0.11-0.94), and the number of new animals introduced into the farm during the last 2 yr (1.28, 1.12-1.52) were significantly associated with the occurrence of BDD. Model 2 (i.e., aspects related to BDD establishment) showed that cows kept in freestalls were at higher risk for BDD compared with those kept in tiestalls (20.65, 1.59-649.37). Furthermore, number of days between diagnosis and treatment of a BDD lesion (10.31, 3.55-81.21) and the amount of concentrate feeding (median 5 kg) per cow and day (7.72, 2.46-6.47) were positively associated with BDD occurrence. In conclusion, the findings of this study provide a set of risk factors that are associated with BDD status within herds in mountainous regions. These results may help in development of adapted control programs for BDD in dairy cows.

Acute phase response of sole ulcer, white line disease and digital dermatitis in dairy cows

Hoof disorders cause lameness and welfare problems for dairy cattle. Acute phase proteins, including serum amyloid A and haptoglobin, with increased rectal temperature and interleukin-6 concentrations, are markers of acute phase response. This study assessed the inflammatory response of cows with either sole ulcer, white line disease or digital dermatitis compared to healthy cows. Another aim was to monitor the inflammatory response changes over time after diagnosis (at hoof trimming, seven and 14 days later) in cows with different hoof disorders.Serum amyloid A concentration in cows with sole ulcer was significantly higher compared with the control group (cows with no hoof lesions) within the two-week study period. Interleukin-6 and rectal temperature declined from day zero to day seven in the sole ulcer group. These results suggest that sole ulcers initiate a long lasting systemic inflammatory response in dairy cows.

Phenytoin: A promising non-antibiotic drug for the topical treatment of digital dermatitis in dairy cows.

Background and Aim:Digital dermatitis (DD) is one of the most common causes of lameness in dairy cattle. It is seen in nearly all dairy herds across the world and has substantial welfare and economic implications. In this study, we aimed to investigate the efficacy of phenytoin sodium topical treatment on painful ulcerative stage of bovine digital dermatitis (BDD).Materials and Methods:In total, 45 Holstein-Friesian dairy cows with DD were randomly assigned to one of the three topical treatment trials (15 each): Saline solution (first treatment, negative control), chlortetracycline spray (second treatment, positive control), or phenytoin sodium powder (third treatment, positive control) (third treatment). On day 0 (pre-treatment) and on days 7, 14, 21, and 28 post-treatment, the response of DD-affected cows to the medications used was evaluated by measuring lesion depth and size, as well as the total clinical score (lameness, pain, and discomfort).Results:The cure rate in cows treated with phenytoin (86.66%) on day 28 was significantly improved compared to cows treated with either chlortetracycline (60%) or normal saline (6.66 %).Conclusion:Our findings highlight the superiority of phenytoin over the commonly used antibacterial agent, chlortetracycline, in the topical treatment of BDD, and subsequently suggest that phenytoin should be considered a suitable alternative treatment option for the treatment of BDD.

Topical salicylic acid treatment of digital dermatitis in dairy cows

Salicylic acid (SA) provides similar treatment efficacy to tetracycline-class antibiotic drugs for the treatment of digital dermatitis (DD) in dairy cows. No milk withholding time following SA treatment has been established in the United States. The objective of this study was to generate data about drug residues in milk following topical treatment of DD lesions with SA. Cows with active (M2 stage) DD lesions were assigned to 1 of 3 treatments: salicylic acid paste, salicylic acid powder, or tetracycline powder. Lesions were photographed digitally and thermographically and scored using the M-stage scoring system before treatment and at 7 and 28 d post-treatment. Milk samples were collected before treatment and at 4 h, 8 h, 24 h, 36 h, and 48 h afterward. Most cows did not have detectable salicylic acid in their milk more than 24 hours after treatment; however, 3 cows had detectable levels of SA at 36 hours post treatment. Treatments did not differ in their effects on DD lesions. These data suggest that milk from treated cows should not be used or sold for at least 48 hours following the topical treatment of DD lesions with salicylic acid.

Bayesian assessment of diagnostic accuracy of a commercial borescope and of trimming chute exams for diagnosing digital dermatitis in dairy cows

Digital dermatitis (DD) is a worldwide infectious disease of cattle that causes lameness, discomfort, and economic losses. The reference standard test to diagnose DD is visual observation in a trimming chute, which cannot be practically performed daily on dairy farms. Moreover, some lesion misclassification may occur using this standard diagnostic method. The possibility of misclassification makes the use of a trimming chute debatable as a perfect reference standard test. The objective of this study was, therefore, to assess the diagnostic accuracy of a commercial borescope and trimming chute exam. The accuracy (sensitivity and specificity) of the tests and DD prevalence were investigated using Bayesian latent class analyses. Our hypothesis was that a commercial borescope can be routinely used to diagnose DD in a milking parlor without previous feet cleaning. A cross-sectional study was performed in a freestall facility. The lesions were scored (M0, M1, M2, M3, M4, M4.1) in the milking parlor with a borescope, followed by an examination in the trimming chute 48 to 72 h after the borescope exam. A total of 870 hind feet were scored during 2 sessions of trimming chute exams and borescope exams in the milking parlor. The data were analyzed in 2 ways. First, data were dichotomized into DD lesions (M1, M2, M3, M4, M4.1) and absence of DD lesions (M0). Second, data were dichotomized into active DD lesions (M1, M2, M4.1) and inactive lesions (M0, M3, M4). A Bayesian latent class model allowing for conditional dependence between tests was used to estimate tests' accuracy, likelihood ratio, and DD prevalence. When the data were dichotomized into DD lesions (M1-M4.1) versus absence of DD (M0) lesions, the sensitivity and specificity of the borescope was 55% [95% credible interval (CrI) 40-71%] and 81% (95% CrI 75-88%). The sensitivity of trimming chute exams was 79% (95% CrI 68-88%), and specificity was 80% (95% CrI 71-89%). When the data were dichotomized into active lesions (M1, M2, M4.1) versus inactive lesions or absence of lesions (M3, M4, M0), the sensitivity and specificity of the borescope were, respectively, 32% (95% CrI 13-58%) and 91% (95% CrI 88-95%). The sensitivity and specificity of trimming chute exams were 91% (95% CrI 81-97%) and 81% (95% CrI 75-89%), respectively. In conclusion, it is possible to use the borescope in the milking parlor without cleaning the feet to monitor prevalence of DD lesions. However, an isolated borescope examination, especially for diagnosing active DD lesions, has low sensitivity for use as a surveillance method. For such use, the sensitivity could be improved by repeating the borescope exam on a regular basis.

Randomised clinical trial showing the curative effect of bandaging on M2-stage lesions of digital dermatitis in dairy cows

Objectives and designThis trial evaluated the effect of bandaging of acute painful ulcerative bovine digital dermatitis (DD) lesion (stage M2) in dairy cows, tested using two different topical treatments.DesignRandomised clinical...

Assessment of a commercial borescope to evaluate the presence of lesions of digital dermatitis in dairy cows

Digital dermatitis (DD) is a worldwide infectious disease of cattle with high prevalence in dairy herds. It is a painful disease with welfare issues causing economical losses. Identifying the affected animals is crucial to establish early treatment and evaluate the efficacy of a control strategy. The "gold standard" diagnosis of DD is the direct observation of DD lesions in a trimming chute. However, the use of a trimming chute for daily diagnosis of DD in all cows is not possible. To facilitate DD monitoring between trimming sessions, lesions could be identified in the parlor during milking. Therefore, we evaluated the use of a commercial borescope in a rotary milking parlor. Our hypothesis was that a borescope is an adequate alternative to evaluate DD lesions between trimming sessions. Our objective was to assess the sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) of a borescope for the diagnosis of DD in the milking parlor as compared to direct observation in a trimming chute, and to quantify the agreement between both techniques.

Bovine lameness and digital dermatitis in dairy cows: updates on control and diagnostics approaches

Sound feet and legs of dairy cows are essential for the animal health, productivity, and welfare. Bovine lameness is one of the major causes of economic losses in dairy production systems [1]. It ranks fourth after mastitis, infertility and metabolic diseases [2]. The disease poses a major welfare and economic problem for dairy cattle, which results in reduced milk yield, reduced feed intake, weight loss, high treatment costs, high culling rate, and reduced fertility of affected animals [3,4]. Claw disorders have been found to be the cause of more than 90% of all lameness cases observed in dairy cattle [5]. Digital dermatitis (DD) is an important ulcerative infectious disease affecting the bovine foot worldwide, and may affect over 80% of cows within a herd [6,7]. The prevalence of DD varies from country to another based on the risk factors related to the animal, environment and managerial conditions [6].

Single Nucleotide Polymorphisms in IL8 and TLR4 Genes as Candidates for Digital Dermatitis Resistance/Susceptibility in Holstein Cattle

ABSTRACTRelatedness between single nucleotide polymorphisms in IL8 and TLR4 genes and digital dermatitis resistance/susceptibility was investigated in seventy Holstein dairy cows. Animals were assigned into two groups, affected group (n = 35) and resistant group (n = 35) based on clinical signs and previous history of farm clinical records. Blood samples were collected for DNA extraction to ampliy fragments of 267-bp and 382-bp for IL8 and TLR4 genes, respectively. PCR-DNA sequencing revealed three SNPs in each of IL8 and TLR4 genes. The identified SNPs associated with digital dermatitis resistance were C94T, A220G, and T262A for IL8 and C118T for TLR4. However, the G349C and C355A SNPs in TLR4 gene were associated with digital dermatitis susceptibility. Chi-square analysis for comparison the distribution of all identified SNPs in both IL8 and TLR4 genes between resistant and affected animals showed no significant variation among the identified SNPs in IL8 gene. Meanwhile, there was a significant variation in case of TLR4 gene. As a pilot study, the present results revealed that identified SNPs in IL8 and TLR4 genes can be used as a genetic marker and predisposing factor for resistance/susceptibility to digital dermatitis in dairy cows. However, TLR4 gene may be a potential candidate for such disease.

Digital Dermatitis in Dairy Cows: A Review of Risk Factors and Potential Sources of Between-Animal Variation in Susceptibility.

Simple SummaryDairy cow lameness is a major problem for the industry, causing reduced animal welfare and economic loss. Digital dermatitis (DD) is a bacterial disease causing painful lesions, generally on the heels of the rear feet, and is an important cause of lameness. There appears to be individual variation between animals in susceptibility to this disease. Particular physical, physiological and behavioural factors might influence individual susceptibility, but further work is required to clarify the influence of these factors and to determine how this information could be used to develop breeding and management strategies to reduce DD prevalence.Digital dermatitis (DD) is a bacterial disease that primarily affects the skin on the heels of cattle. It is a major cause of lameness in dairy cows and a significant problem for the dairy industry in many countries, causing reduced animal welfare and economic loss. A wide range of infection levels has been found on infected farms, prompting investigations into both farm level and animal level risk factors for DD occurrence. There also appears to be individual variation between animals in susceptibility to the disease. The identification of factors affecting individual variation in susceptibility to DD might allow changes in breeding policies or herd management which could be used to reduce DD prevalence. Factors mentioned in the literature as possibly influencing individual variation in susceptibility to DD include physical factors such as hoof conformation and properties of the skin, physiological factors such as the efficacy of the immune response, and behavioural factors such as standing half in cubicles. Further work is required to determine the influence of these factors, identify the genetic basis of variation, clarify the level of heritability of DD susceptibility and to determine how this is correlated with production and health traits currently used in breeding programmes.

Effect of a tea tree oil and organic acid footbath solution on digital dermatitis in dairy cows

Copper sulfate is the industry gold standard footbath ingredient for controlling dairy cow digital dermatitis. However, when used footbath solutions are deposited on soil, high levels of copper in the soil may result, which can have toxic and negative effects on plant growth. An alternative to copper sulfate is Provita Hoofsure Endurance (Provita Eurotech Ltd., Omagh, UK), which is a biodegradable solution containing organic acids, tea tree oil, and wetting agents. The objective of this study was to quantify changes in digital dermatitis frequency when using Provita Hoofsure Endurance and copper sulfate in a split footbath in 3 commercial dairy herds. This study was conducted from January 5, 2012, to March 19, 2012, in 3 commercial Kentucky dairies with 120, 170, and 200 milking Holstein cows. None of the herds was using a footbath for digital dermatitis control before the study. Footbath solutions were delivered using a split footbath. During the study, a 3% Hoofsure Endurance solution for the left hooves and a 5% copper sulfate solution for the right hooves was used. Digital dermatitis was scored every 3wk using the M0 to M4 system, where M0=a claw free of signs of digital dermatitis; M1=a lesion <2cm that is not painful; M2=the ulcerative stage, with lesion diameter of >2cm, and painful to the touch; M3=the healing stage and covered by a scab; and M4=the chronic stage and characterized by dyskeratosis or proliferation of the surface that is generally not painful. McNemar’s test statistic suggested that a statistically significant difference existed in the proportions of M1 and M2 lesions between the beginning and end of the study for both treatments. This indicates that each solution was effective in decreasing the proportion of M1 or M2 lesions from baseline to the last time point. A chi-square test calculated using PROC FREQUENCY of SAS (SAS Institute Inc., Cary, NC) indicated that no statistically significant relationship existed between the treatments among changes in digital dermatitis frequency from the baseline to the end of the study. Performance of the 2 footbath solutions was comparable throughout the study. No significant differences were observed between the copper sulfate and Provita Hoofsure Endurance.

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

Infrared thermography (IRT) was used to detect digital dermatitis (DD) prior to routine claw trimming. A total of 1192 IRT observations were collected from 149 cows on eight farms. All cows were housed in tie-stalls. The maximal surface temperatures of the coronary band (CB) region and skin (S) of the fore and rear feet (mean value of the maximal surface temperatures of both digits for each foot separately, CBmax and Smax) were assessed. Grouping was performed at the foot level (presence of DD, n=99; absence, n=304), or at the cow level (all four feet healthy, n=24) or where there was at least one DD lesion on the rear feet, n=37). For individual cows (n=61), IRT temperature difference was determined by subtracting the mean sum of CBmax and Smax of the rear feet from that of the fore feet.Feet with DD had higher CBmax and Smax (P<0.001) than healthy feet. Smax was significantly higher in feet with infectious DD lesions (M-stage: M2+M4; n=15) than in those with non-infectious M-lesions (M1+M3; n=84) (P=0.03), but this was not the case for CBmax (P=0.12). At the cow level, an optimal cut-off value for detecting DD of 0.99°C (IRT temperature difference between rear and front feet) yielded a sensitivity of 89.1% and a specificity of 66.6%. The results indicate that IRT may be a useful non-invasive diagnostic tool to screen for the presence of DD in dairy cows by measuring CBmax and Smax.

Short communication: Automatic washing of hooves can help control digital dermatitis in dairy cows

The objectives of this study were to develop and test a system for automatic washing of the hooves of dairy cows and to evaluate the effect of frequent automatic washing on the prevalence of digital dermatitis (DD). An automatic hoof washer was developed in an experimental dairy herd and tested in 6 commercial dairy herds in 2 experiments (1 and 2). In the experimental herd, automatic hoof washing resulted in cleaner hooves. In experiments 1 and 2, cows were washed after each milking on the left side only, leaving the right side unwashed as a within-cow control. In experiment 1, hooves were washed with a water and 0.4% soap solution. In experiment 2, hooves were washed with water only. In each experiment, DD was scored in a hoof-trimming chute approximately 60 d after the start of hoof washing. Data were analyzed using a generalized linear mixed model. The outcome was the DD status of each leg (DD positive or DD negative). Herd and cow within herd were included as random effects, and treatment (washing or control) was included as a fixed effect. The statistical analyses showed that the odds ratio of having DD was 1.48 in the control leg compared with the washed leg in experiment 1. In experiment 2, the odds ratio of having DD was 1.27 in the control leg compared with the washed leg. We concluded that automatic washing of hooves with water and soap can help decrease the prevalence of DD in commercial dairy herds.

The effect of an acidified, ionized copper sulphate solution on digital dermatitis in dairy cows

Digital dermatitis (DD) is the most important infectious claw disorder in dairy cattle and herd-based foot bathing with antibacterials, such as 4% formalin, is often used to prevent it. However, there is a lack of long-term studies of the effectiveness of such regimes and in this study the preventive and curative effect of 4% formalin was compared with that of an acidified, ionized copper sulphate solution over a 4-month period on a commercial 120-cow dairy farm. The cows were walked through a split-leg footbath where left claws were treated with an acidified copper solution twice daily for 5 days/week, while right claws were treated with 4% formalin twice daily for 1 day/every second week. Hind claws were scored for the presence and severity of DD in a trimming chute at the start of the study and every 4 weeks throughout the study period. At the start of the study 21/110 cows had ulcerative DD lesions with 10 on the left hind foot, 8 on the right and 3 on both. These lesions, as well as any new lesions which arose during the study, were treated with chlortetracycline spray. During the study 440 observations were made and seven new DD lesions were recorded on left feet (copper treated) and 20 on right feet (formalin treated). Based on survival analysis, the risk of developing a new ulcerative DD lesion on copper-treated (left hind) feet was almost three times less (RR=0.37, 95% CI 0.16-0.91) than formalin-treated (right hind) feet. Cure rates of DD lesions were not different between copper and formalin.

Effectiveness of different footbathing frequencies using copper sulfate in the control of digital dermatitis in dairy cows

Two experiments were conducted to test the effectiveness of different footbathing frequencies using CuSO4 in the control of digital dermatitis (DD) in groups of dairy cows with low and high DD prevalence in an endemically infected herd. During the study, groups of cows walked through allocated footbath solutions after milking on 4 consecutive milkings each week, 2 wk, or monthly, depending on treatment. The footbath solutions were changed either after 200 cows had passed through the footbath or within 24h. All cows were scored weekly during milking for DD lesion stage on the hind feet using a 5-point nominal scale. A transition grade was assigned based on whether the DD lesions improved (1) or deteriorated or did not improve (0) from week to week, and was averaged for all cows in the group. Furthermore, from the longitudinal study data, all transitions between different DD lesion stages between the different time points were used in a discrete, first-order Markov chain (state transition matrix) model. In experiment 1, 70 Holstein-Friesian cows with DD lesions present on at least one of their hind feet were allocated to 1 of 2 footbath treatments for 14 wk: (1) 5% CuSO4 each week or (2) 5% CuSO4 every 2 wk. At the end of the study, no active DD lesions were observed in cows in either treatment group, but significantly more cows had no DD lesions (0.48±0.097 vs. 0.24±0.094) and fewer cows had lesions in the healing stage (0.52±0.104 vs. 0.77±0.090) for the weekly compared with the 2-wk footbathing regimen. The number of active DD lesions that the transition matrix model predicted over time was 3 and 8% for weekly and every 2 wk footbathing treatments, respectively. In experiment 2, 64 cows with no DD lesions on either of their hind feet were allocated to 1 of 2 footbath treatment regimens for 14 wk: (1) 5% CuSO4 every 2 wk or (2) 5% CuSO4 each month. At the end of the trial, significantly more cows had no DD (0.80±0.088 vs. 0.65±0.102) and fewer cows had DD lesions in the healing stage (0.20±0.088 vs. 0.35±0.102) in the every 2 wk regimen than in the monthly footbathing regimen. The number of active DD lesions that the transition matrix model predicted over time was low for both footbathing interventions (1 and 4%, respectively). Increasing the interval between footbaths does not appear the most appropriate mechanism for reducing CuSO4 usage.

A simple method to score digital dermatitis in dairy cows in the milking parlor

The diagnosis of digital dermatitis (DD) in cows is crucial for researchers to evaluate the effectiveness of control measures. The objective of this study was to evaluate intra- and inter-observer agreement and accuracy of a simple method to score DD lesions that is based on the inspection of cleaned feet in the milking parlor with a swiveling mirror and a powerful headlamp. The hind feet of 242 Holstein cows from 4 farms were inspected concurrently by 5 observers (to assess inter-observer agreement) during 2 consecutive milkings (to assess intra-observer agreement). This inspection was followed by an inspection of the feet in a trimming chute, considered to be the gold standard test, to test for accuracy. The reliability of the method was assessed using both the 5 M-stages scoring system (M0 to M4, M standing for Mortellaro) and a simplified M-stages scoring system in which the M3 and M4 stages are merged. As most disagreements concerned the M3 and M4 stages, performance was improved with the simplified M-stages scoring system. With this simplified system, the method had good intra-observer agreement [percent of overall raw agreement (PA)=80%, weighted kappa (κw)=0.71, and good inter-observer agreement (PA=77%, κw=0.66)]. The agreement with the gold standard test was moderate (PA=69%, κw=0.58). Considering absence versus presence of a DD lesion on a foot, the method had good sensitivity (0.90) and specificity (0.80). The time spent for inspection varied from 30 to 60s per cow. Inspection of cleaned feet with a swiveling mirror and a powerful headlamp in the milking parlor is a reliable, cost- and time-friendly method, which may be useful for both farmers and researchers, especially when the DD status of many dairy cows has to be evaluated concomitantly. The reliability of this method might be improved by using more precise descriptive criteria for the discrimination of each M-stage.