Maher Alsaaod

Development and validation of a novel pedometer algorithm to quantify extended characteristics of the locomotor behavior of dairy cows

Behavior is one of the most important indicators for assessing cattle health and well-being. The objective of this study was to develop and validate a novel algorithm to monitor locomotor behavior of loose-housed dairy cows based on the output of the RumiWatch pedometer (ITIN+HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Data of locomotion were acquired by simultaneous pedometer measurements at a sampling rate of 10 Hz and video recordings for manual observation later. The study consisted of 3 independent experiments. Experiment 1 was carried out to develop and validate the algorithm for lying behavior, experiment 2 for walking and standing behavior, and experiment 3 for stride duration and stride length. The final version was validated, using the raw data, collected from cows not included in the development of the algorithm. Spearman correlation coefficients were calculated between accelerometer variables and respective data derived from the video recordings (gold standard). Dichotomous data were expressed as the proportion of correctly detected events, and the overall difference for continuous data was expressed as the relative measurement error. The proportions for correctly detected events or bouts were 1 for stand ups, lie downs, standing bouts, and lying bouts and 0.99 for walking bouts. The relative measurement error and Spearman correlation coefficient for lying time were 0.09% and 1; for standing time, 4.7% and 0.96; for walking time, 17.12% and 0.96; for number of strides, 6.23% and 0.98; for stride duration, 6.65% and 0.75; and for stride length, 11.92% and 0.81, respectively. The strong to very high correlations of the variables between visual observation and converted pedometer data indicate that the novel RumiWatch algorithm may markedly improve automated livestock management systems for efficient health monitoring of dairy cows.

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.

Use of Extended Characteristics of Locomotion and Feeding Behavior for Automated Identification of Lame Dairy Cows

This study was carried out to detect differences in locomotion and feeding behavior in lame (group L; n = 41; gait score ≥ 2.5) and non-lame (group C; n = 12; gait score ≤ 2) multiparous Holstein cows in a cross-sectional study design. A model for automatic lameness detection was created, using data from accelerometers attached to the hind limbs and noseband sensors attached to the head. Each cow’s gait was videotaped and scored on a 5-point scale before and after a period of 3 consecutive days of behavioral data recording. The mean value of 3 independent experienced observers was taken as a definite gait score and considered to be the gold standard. For statistical analysis, data from the noseband sensor and one of two accelerometers per cow (randomly selected) of 2 out of 3 randomly selected days was used. For comparison between group L and group C, the T-test, the Aspin-Welch Test and the Wilcoxon Test were used. The sensitivity and specificity for lameness detection was determined with logistic regression and ROC-analysis. Group L compared to group C had significantly lower eating and ruminating time, fewer eating chews, ruminating chews and ruminating boluses, longer lying time and lying bout duration, lower standing time, fewer standing and walking bouts, fewer, slower and shorter strides and a lower walking speed. The model considering the number of standing bouts and walking speed was the best predictor of cows being lame with a sensitivity of 90.2% and specificity of 91.7%. Sensitivity and specificity of the lameness detection model were considered to be very high, even without the use of halter data. It was concluded that under the conditions of the study farm, accelerometer data were suitable for accurately distinguishing between lame and non-lame dairy cows, even in cases of slight lameness with a gait score of 2.5.

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.

The cow pedogram-Analysis of gait cycle variables allows the detection of lameness and foot pathologies.

Changes in gait characteristics are important indicators in assessing the health and welfare of cattle. The aim of this study was to detect unilateral hind limb lameness and foot pathologies in dairy cows using 2 high-frequency accelerometers (400 Hz). The extracted gait cycle variables included temporal events (kinematic outcome = gait cycle, stance phase, and swing phase duration) and several peaks (kinetic outcome = foot load, toe-off). The study consisted of 2 independent experiments. Experiment 1 was carried out to compare the pedogram variables between the lateral claw and respective metatarsus (MT; n = 12) in sound cows (numerical rating system <3, n = 12) and the differences of pedogram variables across limbs within cows between lame cows (numerical rating system ≥3, n = 5) and sound cows (n = 12) using pedogram data that were visually compared with the synchronized cinematographic data. Experiment 2 was carried out to determine the differences across limbs within cows between cows with foot lesions (n = 12) and without foot lesions (n = 12) using only pedogram data. A receiver operator characteristic analysis was used to determine the performance of selected pedogram variables at the cow level. The pedogram of the lateral claw of sound cows revealed similarities of temporal events (gait cycle duration, stance and swing phases) but higher peaks (toe-off and foot load) as compared with the pedogram of the respective MT. In both experiments, comparison of the values between groups showed significantly higher values in lame cows and cows with foot lesions for all gait cycle variables. The optimal cutoff value of the relative stance phase duration for identifying lame cows was 14.79% and for cows with foot lesions was 2.53% with (both 100% sensitivity and 100% specificity) in experiments 1 and 2, respectively. The use of accelerometers with a high sampling rate (400 Hz) at the level of the MT is a promising tool to indirectly measure the kinematic variables of the lateral claw and to detect unilateral hind limb lameness and hind limb pathologies in dairy cows and is highly accurate.

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.

Invited review: Genetics and claw health: Opportunities to enhance claw health by genetic selection

Routine recording of claw health status at claw trimming of dairy cattle has been established in several countries, providing valuable data for genetic evaluation. In this review, we examine issues related to genetic evaluation of claw health; discuss data sources, trait definitions, and data validation procedures; and present a review of genetic parameters, possible indicator traits, and status of genetic and genomic evaluations for claw disorders. Different sources of data and traits can be used to describe claw health. Severe cases of claw disorders can be identified by veterinary diagnoses. Data from lameness and locomotion scoring, activity information from sensors, and feet and leg conformation traits are used as auxiliary traits. The most reliable and comprehensive information is data from regular hoof trimming. In genetic evaluation, claw disorders are usually defined as binary traits, based on whether or not the claw disorder was present (recorded) at least once during a defined time period. The traits can be specific disorders, composite traits, or overall claw health. Data validation and editing criteria are needed to ensure reliable data at the trimmer, herd, animal, and record levels. Different strategies have been chosen, reflecting differences in herd sizes, data structures, management practices, and recording systems among countries. Heritabilities of the most commonly analyzed claw disorders based on data from routine claw trimming were generally low, with ranges of linear model estimates from 0.01 to 0.14, and threshold model estimates from 0.06 to 0.39. Estimated genetic correlations among claw disorders varied from -0.40 to 0.98. The strongest genetic correlations were found among sole hemorrhage (SH), sole ulcer (SU), and white line disease (WL), and between digital/interdigital dermatitis (DD/ID) and heel horn erosion (HHE). Genetic correlations between DD/ID and HHE on the one hand and SH, SU, or WL on the other hand were, in most cases, low. Although some of the studies were based on relatively few records and the estimated genetic parameters had large standard errors, there was, with some exceptions, consistency among studies. Various studies evaluate the potential of various data soureces for use in breeding. The use of hoof trimming data is recommended for maximization of genetic gain, although auxiliary traits, such as locomotion score and some conformation traits, may be valuable for increasing the reliability of genetic evaluations. Routine genetic evaluation of direct claw health has been implemented in the Netherlands (2010); Denmark, Finland, and Sweden (joint Nordic evaluation; 2011); and Norway (2014), and other countries plan to implement evaluations in the near future.

Technical note: Validation of a semi-automated software tool to determine gait-cycle variables in dairy cows

This paper presents the validation of a software tool called Cow-Gait-Analyzer (University of Bern, Switzerland) to determine gait-cycle variables in lame and non-lame dairy cows using features derived from low-cost, stand-alone 3-dimensional accelerometers (400 Hz). The Cow-Gait-Analyzer automatically extracts the relevant gait events of foot load and toe off, which characterize gait-cycle duration, stance phase, and swing phase during walking. A nonautomatic step is visual inspection of the pedograms. If the software does not automatically choose the right peaks according to pedogram definitions, peaks can be manually chosen. We validated the algorithms by comparing the accelerometer data (pedogram) with the synchronized video data, which we used as a gold standard. We carried out the measurements at the metatarsal level of paired hind limbs during walking. We included 12 non-lame cows and 5 lame cows and expressed overall differences between the Cow-Gait-Analyzer and the gold standard as relative measurement error (RME). We analyzed 34 hind limbs with a mean of 9 gait cycles. The median RME for gait-cycle duration and stance phases were 0 and 1.69%, respectively. The peaks of gait-cycle variables showed RME of 0.67 and 0.24% for foot load and toe off, respectively. The semi-automated Cow-Gait-Analyzer can accurately determine gait-cycle variables in both lame and non-lame cows, and could be used to assess gait patterns in routine clinical and research practice focusing on individual cows.

Locomotion characteristics of dairy cows walking on pasture and the effect of artificial flooring systems on locomotion comfort.

The locomotion comfort of dairy cows depends on the floor of the walking alleys. Optimal locomotion comfort is given when cows walk on pasture, allowing freedom from discomfort and pain and the expression of normal behavior. This study examined the characteristics of locomotion behavior on pasture (gold standard with optimal locomotion comfort) and compared it with behaviors of cows walking on mastic asphalt or solid rubber mats before and after a routine claw trimming session. Our hypotheses were (1) that gait variables were different on pasture versus mastic asphalt and on mastic asphalt versus rubber, and (2) that claw trimming had an effect on gait variables of cows walking on mastic asphalt. Twenty-four dairy cows kept in a tiestall facility were enrolled in this experimental trial. The pedogram was measured using 2 standalone 3-dimensional accelerometers (400 Hz), attached to the metatarsus of both hind limbs. The extracted pedogram variables included temporal events (kinematic outcome = gait cycle and stance-phase and swing-phase durations) and peaks (kinetic outcome = foot load, toe-off). The cows were further video-recorded to calculate walking speed and stride length. Locomotion score was performed on mastic asphalt to enroll only nonlame cows (locomotion score <3). For comparison between different floor types, repeated-measures ANOVA was performed with the cow as a subject variable, session time of measurement as within-subject variable, and flooring type as a fixed effect. Three separate analyses were performed: pasture versus mastic asphalt (analysis I), solid rubber versus mastic asphalt (analysis II), and the effect of claw trimming on the kinematic and kinetic variables on mastic asphalt (analysis III). All tested gait variables were significantly different between pasture and mastic asphalt floor. The optimal characteristics of locomotion comfort on pasture included shorter duration of gait cycle, longer stance-phase duration, shorter swing-phase duration, higher walking speed, longer stride length, and higher peaks of foot load and toe-off. However, gait variables of cows walking on rubber mats did not show any significant difference compared with the mastic asphalt floor; only stride length tended to be longer on rubber mats. In addition, the stance- and swing-phase durations significantly improved shortly after trimming. The left-right differences of the stance- and swing-phase durations tended to decrease after claw trimming when cows walked on asphalt floor. The results of this study show that solid rubber flooring does not result in significant improvement of the evaluated variables of locomotion comfort compared with mastic asphalt.

Validation of a pedometer algorithm as a tool for evaluation of locomotor behaviour in dairy Mediterranean buffalo

This research communication validates an algorithm to monitor natural occurrence of locomotor behaviours in dairy Mediterranean buffalo based on the output of a 3-dimensional accelerometer (RumiWatch®, pedometer). Several characteristics of the locomotor behaviour were detected with a very high (up-right, lying and standing time) or high degree of correlation (walking time and number of strides) and a low mean difference with the video recording. The proportion of correctly detected events exceeded 99 % for the following variables: stand up and lie down events, as well as number of lying, standing or walking bouts. The mean relative measurement error was less than 10 % for the variables: lying, standing, up-right times and number of strides as compared with gold standard. This new algorithm may represent the base for a future early and real-time disease warning system aiming to gain higher health standard in these ruminants.