Short communication: Detection of lameness in dairy cows using a grooming device

Effects of Using Mechanical Brushes on the Productive Performance of Dairy Cows

Intensive farming can reduce production costs and maximize animal production efficiency; however, it also causes many adverse effects on the welfare of dairy cows. A mechanical brush is an automated grooming device that promotes the grooming behavior of dairy cattle, thereby helping to alleviate stress. In the present study, we evaluated the effects of using mechanical brushes on the production performance of dairy cows by comprehensively analyzing their milk production, health status, and reproductive performance. The cows were assigned to 6 groups: 109 lactating dairy cows (brush treatment) and 105 controls (without brush treatment), 64 dry milk dairy cows (brush treatment) and 49 controls (without brush treatment), and 198 perinatal cows (brush treatment) and 65 controls (without brush treatment). We found an increasing trend in the daily utility time and usage frequency of mechanical brushes for each cow during the lactating period (7.73 ± 4.02 min/d and 2.90 ± 1.22 times/d, respectively), dry period (15.97 ± 14.16 min/d and 4.21 ± 2.91 times/d, respectively), and perinatal period (25.15 ± 19.05 min/d and 5.45 ± 3.83 times/d, respectively) (p < 0.01 and p < 0.05, respectively). The installation location of the mechanical brush significantly affected the frequency of its usage during the different periods. The head was the preferred body part for using the mechanical brush during the lactation and dry periods (59.32% and 44.54%, respectively), while the hip was the main preferred grooming part during the perinatal period (40.17%). Overall, the time, frequency, and preferred body part of dairy cows that used mechanical brushes varied across different physiological stages. Additionally, mechanical brush use in lactating and dry dairy cows significantly improved cleanliness of the body's surface (p < 0.05) and enhanced milk production of lactating cows (p < 0.01), particularly for cows with four and five parities. Thus, the use of mechanical brushes could improve the production performance of dairy cows and enhance sustainability of large-scale farms.

Improving Lameness Detection in Cows: A Machine Learning Algorithm Application

The deployment of diverse data-generating technologies in livestock farming holds the promise of early disease detection and improved animal well-being. In this paper, we combine routinely collected dairy farm and herd data with weather and high frequency sensor data from 6 farms to predict new lameness events in various future periods, spanning from the following day to 3 weeks. A Random Forest classifier, using input features selected by the Boruta Algorithm, was used for the prediction task; effects of individual features were further assessed using partial dependence plots. We achieve precision scores of up to 93% when predicting lameness for the next 3 weeks and when using information from the last 3 weeks, combined with a balanced accuracy of 79%. Removing sensor data results have tendency to reduce the precision for predictions, especially when using information from the last one,2 or 3 weeks. Moving to a larger data set (without sensor data) of 44 farms keeps the similar balanced accuracy but reduces precision by more than 30%, revealing a substantial a trade-off in model quality between false positives (false lameness alerts) and false negatives (missed lameness events). Sensor data holds promise to further improve the precision of these models, but can be partially compensated by high resolution data from other systems, such as automated milking systems.

Effects of feed energy density, daily milking frequency, and a single injection of cabergoline on behavior and welfare in dairy cows at dry-off

Drying off dairy cows may challenge animal welfare due to high milk yields. A total of 111 loose-housed Holstein cows yielding >15 kg/d of milk were included in a 2 × 2 × 2 factorial design during dry-off to investigate the effects of reduced feeding level (normal vs. reduced energy density), reduced milking frequency (twice vs. once daily), and administration of a dopamine agonist (saline i.m. injection vs. cabergoline i.m. injection) on behavior in the home pen. During the 7 d before dry-off, cows were fed and milked according to 1 of the 4 feeding level and milking frequency combinations. Within 3 h after the last milking, cows were injected i.m. with 5 mL of either saline or a dopamine agonist (5.6 mg of cabergoline; Velactis, Ceva Santé Animale, Libourne, France; labeled for use only with abrupt dry-off, i.e., no preceding reduction in feeding level or milking frequency before last milking). Cows' behavior during d -1, 0, and +1 relative to the last milking was recorded via video and leg-attached sensors. Cows on the reduced energy density diet spent more time feeding and showed more attempts to feed from other cows' bins on d -1. Throughout the period of observations, cows on the reduced diet spent a lower percentage of lying time with their head raised, a higher percentage of lying time with their legs bent, and less time standing in a vigilant posture than did cows on the normal lactation diet. Reducing the daily milking frequency from 2 to 1 did not result in any clear behavioral signs of discomfort. On d 0, cows injected with cabergoline lay down longer but had their head raised for a shorter percentage of time while lying, compared with cows injected with saline. Cows injected with cabergoline also spent less time feeding than cows injected with saline on d 0, and reduced the time spent drinking from d -1 to d 0. Finally, fewer cabergoline-injected cows used the brush for self-grooming, and, among cows that did use the brush, the cows injected with cabergoline reduced the time spent using the brush from d -1 to d 0. In conclusion, cows injected with cabergoline showed several behavioral changes compared with control cows injected with saline. The behavioral changes shown by cows injected with cabergoline may be indicative of malaise during the first 24 h after injection, raising concern for animal welfare. No behavioral evidence for reduced udder pain in cows injected with cabergoline compared with control cows injected with saline was found. Drying off by reducing the energy density of the diet caused behavioral changes indicative of hunger before dry-off, whereas reducing the milking frequency had no clear effects on behavior.

Welfare of dairy cows

This Scientific Opinion addresses a European Commission's mandate on the welfare of dairy cows as part of the Farm to Fork strategy. It includes three assessments carried out based on literature reviews and complemented by expert opinion. Assessment 1 describes the most prevalent housing systems for dairy cows in Europe: tie-stalls, cubicle housing, open-bedded systems and systems with access to an outdoor area. Per each system, the scientific opinion describes the distribution in the EU and assesses the main strengths, weaknesses and hazards potentially reducing the welfare of dairy cows. Assessment 2 addresses five welfare consequences as requested in the mandate: locomotory disorders (including lameness), mastitis, restriction of movement and resting problems, inability to perform comfort behaviour and metabolic disorders. Per each welfare consequence, a set of animal-based measures is suggested, a detailed analysis of the prevalence in different housing systems is provided, and subsequently, a comparison of the housing systems is given. Common and specific system-related hazards as well as management-related hazards and respective preventive measures are investigated. Assessment 3 includes an analysis of farm characteristics (e.g. milk yield, herd size) that could be used to classify the level of on-farm welfare. From the available scientific literature, it was not possible to derive relevant associations between available farm data and cow welfare. Therefore, an approach based on expert knowledge elicitation (EKE) was developed. The EKE resulted in the identification of five farm characteristics (more than one cow per cubicle at maximum stocking density, limited space for cows, inappropriate cubicle size, high on-farm mortality and farms with less than 2 months access to pasture). If one or more of these farm characteristics are present, it is recommended to conduct an assessment of cow welfare on the farm in question using animal-based measures for specified welfare consequences.

The Effect of Placement and Group Size on the Use of an Automated Brush by Groups of Lactating Dairy Cattle

Mechanical brushes are often provided on dairy farms to facilitate grooming. However, current brush designs do not provide data on their use, and thus little is known about the effects of group size and placement of brushes within the pen. The objectives of this study were to automatically detect brush use in cow groups and to investigate the influence of (1) group size and the corresponding cow-to-brush ratio and (2) brush placement in relation to the lying stalls and the feeding and drinking areas. We measured brush use in groups of 60, 48, 36, and 24 cows, with the brush placed either in the alley adjacent to the feed bunk and water trough or in the back alley. Cows used the brush for longer when it was placed in the feed/water alley compared to when placed in the back alley. Average brush use per cow increased when cows were housed in smaller groups, but the brush was never in use more than 50% of the day, regardless of group size. We conclude that brush use increases when availability is increased and when the brush is placed closer to the feed and water.

Effects of feeding level and milking frequency on behavior of dairy cows before dry-off

Drying-off may challenge the welfare of especially high-yielding dairy cows. In this study, 119 loose-housed Holstein cows yielding ≥20 kg milk/d were enrolled in a 2 × 2 factorial design aiming to investigate effects of changes in diet energy density and daily milking frequency on behavior. The last 7 d before the dry-off day, cows were milked either twice or once daily, and were fed either a lactation diet or the same diet diluted with 30% barley straw, both offered in individual bins for ad libitum intake. All cows were fitted with sensors to record lying time and activity, and data from 109 of these cows were used together with behavioral observations obtained from video recordings of 52 of the cows. Data from activity sensors and video recordings were obtained during 24 h on d -6, -3, and -1 relative to the dry-off day (i.e., the day of the last milking). Across all days of observation, cows milked once daily spent more time feeding (149 vs. 130 min/d) than cows milked twice daily. Cows on the reduced diet and milked twice daily had a shorter lying time compared with cows on the normal diet and milked twice (759 vs. 837 min/d), whereas lying times of cows on the remaining 2 treatments were intermediate. Among cows on the lactation diet, reduced milking frequency increased time spent perching (from 11.1 to 28.7 min/d). Cows fed the energy-reduced diet spent more time feeding (154 vs. 124 min/d), showed more attempts to feed from unassigned feed bins (31.7 vs. 15.4 attempts daily), and spent less time using a mechanical brush (6.5 vs. 9.2 min/d) than cows fed the lactation diet. These results show that several aspects of cows' behavior, including main activities such as lying and feeding, but also behaviors of low resilience such as brush use, and to some extent more subtle and complex behaviors such as perching and attempts to feed from unassigned feed bins, are sensitive to management changes typically applied during the days before dry-off. The behavioral effects of the reduced feed energy level support earlier findings suggesting that qualitative feed restriction renders cows hungry. The effects of the reduced milking frequency on behavior were generally less pronounced, but 2 noteworthy interactions between milking frequency and diet were seen. First, cows milked twice daily and fed the energy-reduced diet spent less time lying, which is possibly related to increased energy demand and hunger. Second, cows milked once daily and fed the lactation diet spent more time perching, which may be related to udder discomfort. However, these more complex findings warrant further study. Taken together, the results of this study show that a dry-off procedure involving reduced energy supply induces behavioral changes indicating a higher degree of compromised welfare compared with reduced milking frequency.

Beef Cattle Preference and Usage of Environmental Enrichments Provided Simultaneously in a Pasture-Based Environment

Environmental enrichment can improve livestock welfare through increasing environmental complexity to promote a greater range of natural behaviours. However, there is limited understanding of the need for and impacts of enrichments for extensively managed beef cattle that can sometimes be kept in grassed paddocks devoid of additional natural and artificial features, i.e., ‘barren pastures’. This trial assessed which enrichments beef cattle preferred and utilised in a barren paddock environment. Eight groups of seven Angus steers housed on pastured paddocks devoid of natural or artificial features were observed during daylight hours for two days a week over a period of three weeks, after being presented with four enrichments simultaneously: a cattle brush, a piece of hanging rope, a tree stump, and a woodchip pile. Although enrichment use generally decreased over time, the brush, stump, and woodchip maintained a higher level of use than the rope, based on the frequency of interactions and number of displacements around the enrichments (both p < 0.001). This suggests that the brush, stump, and woodchip pile were more valuable resources to the cattle, allowing for grooming and lying behaviours, although oral manipulations also occurred on the stump, woodchip, and rope. The inclusion of these enrichments can increase the complexity of barren pasture environments and allow for the increased expression of natural behaviours, potentially contributing to improved welfare.

Positive Welfare Indicators in Dairy Animals

Nowadays, there is growing interest in positive animal welfare not only from the view of scientists but also from that of society. The consumer demands more sustainable livestock production, and animal welfare is an essential part of sustainability, so there is interest in incorporating positive welfare indicators into welfare assessment schemes and legislation. The aim of this review is to cite all the positive welfare indicators that have been proposed for dairy animals in theory or practice. In total, twenty-four indicators were retrieved. The most promising are exploration, access to pasture, comfort and resting, feeding, and behavioral synchronicity. Qualitative behavioral assessment (QBA), social affiliative behaviors, play, maternal care, ear postures, vocalizations, visible eye white, nasal temperature, anticipation, cognitive bias, laterality, and oxytocin have been also studied in dairy ruminants. QBA is the indicator that is most often used for the on-farm welfare assessment. Among all dairy animals, studies have been performed mostly on cattle, followed by sheep and goats, and finally buffaloes. The research on camel welfare is limited. Therefore, there is a need for further research and official assessment protocols for buffaloes and especially camels.

Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions

Precision livestock farming (PLF) has spread to various countries worldwide since its inception in 2003, though it has yet to be widely adopted. Additionally, the advent of Industry 4.0 and the Internet of Things (IoT) have enabled a continued advancement and development of PLF. This modern technological approach to animal farming and production encompasses ethical, economic and logistical aspects. The aim of this review is to provide an overview of PLF and Industry 4.0, to identify current applications of this rather novel approach in different farming systems for food producing animals, and to present up to date knowledge on the subject. Current scientific literature regarding the spread and application of PLF and IoT shows how efficient farm animal management systems are destined to become. Everyday farming practices (feeding and production performance) coupled with continuous and real-time monitoring of animal parameters can have significant impacts on welfare and health assessment, which are current themes of public interest. In the context of feeding a rising global population, the agri-food industry and industry 4.0 technologies may represent key features for successful and sustainable development.

The effects of cow dominance on the use of a mechanical brush

An animal's social position within a group can influence its ability to perform important behaviours like eating and resting, but little is known about how social position affects the ability to express what are arguably less important but still rewarding behaviors, such as grooming. We set out to assess if dominance measured at the feeder is associated with increased use of a mechanical brush. Over a 2-year period, 161 dry cows were enrolled in a dynamically changing group of 20 individuals with access to a mechanical brush. We determined dominance using agonistic behaviors at the feeder and retrospectively analyzed brush use for the 12 most, and 12 least dominant individuals during the week before calving. Cows that were more dominant at the feeder used the brush more, especially during peak feeding times. Agonistic interactions at the brush did not differ between dominants and subordinates and were not related to brushing duration. These findings indicate that social position, calculated using competition for feed, affects mechanical brush access such that subordinates use the brush less than dominant cows independent of competition or time of day.

Postpartum Stressors Cause a Reduction in Mechanical Brush Use in Dairy Cows

Dairy cows are often subjected to multiple post-partum stressors but how these stressors impact cows' affective states remain poorly understood. Negative affective states are often associated with reduced expression of low-resilience behaviors, so we explored whether cows would reduce their use of a brush after calving. Before calving, cows were offered the opportunity to use a mechanical brush once a week for 10 min. In Experiment 1, we explored whether cows reduced their use of a mechanical brush after parturition (compared to prepartum values) when subjected to the myriad of stressors typically experienced by cows at this time. In Experiment 2, we assessed the effect of cow-calf separation. Results from Experiment 1 showed that cows displayed a reduced brush use following parturition compared to the week before calving. In Experiment 2, we showed that cows given more time to bond with their calf, and who were separated more recently from their calf, showed a more pronounced reduction in brush use. Cows provided part-time contact with their calf for 29 days also reduced their brush use when they were permanently separated from their calf on day 30 after calving. These results suggest that cows experienced anhedonia and point to new directions for research on dairy cow affective states.

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.

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.

Prioritisation of animal welfare issues in the UK using expert consensus

BACKGROUND

The welfare of all animals under human management is an area of consistent public concern, but strategies to improve welfare may vary across species. In this study, expert consensus, using a modified Delphi approach, was used to prioritise welfare issues of farmed and companion animals in the UK.

METHODS

The study involved 117 experts, divided between eight species groups. Experts were recruited from a broad range of disciplines. Two rounds of online surveys were conducted using the online survey tool, and the final round was an in-person workshop with a subsection of experts (n=21). The experts agreed that welfare issues should be ranked considering three categories: (1) severity, (2) duration and (3) perceived prevalence.

RESULTS

A comprehensive list of welfare issues was generated for each species by discussion boards (cats, rabbits and horses) or by literature review (dogs, pigs, poultry, cattle and small ruminants). In the first online survey, the experts scored each welfare issue using the three categories (severity, duration and prevalence) on a 6-point Likert scale, where 1=never/none and 6=always/high. Lists of welfare issues were reduced to 25 per cent-59 per cent of the total number, by determining mean ranks from expert ratings. In round 2, experts were asked whether they agreed or disagreed with the rankings. In the final stage, during the workshop, the top-ranking welfare issues for animals were determined for individual animals (considering the greatest severity and duration, in the expert's opinion) and for perceived prevalence.

CONCLUSIONS

Overall, prioritised welfare issues included lack of knowledge of welfare needs, social behaviour issues, problem behaviours, inappropriate diet and environment, lack of veterinary care, consequences from breeding decisions, poor pain management, delayed euthanasia and chronic ill health. The Delphi process resulted in consensus on the most significant welfare challenges of animals in the UK and can help to guide future research and education priority decisions.

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.