Profiling Detection and Classification of Lameness Methods in British Dairy Cattle Research: A Systematic Review and Meta-Analysis

Global losses due to dairy cattle diseases: A comorbidity-adjusted economic analysis

An economic simulation was carried out over 183 milk-producing countries to estimate the global economic impacts of 12 dairy cattle diseases and health conditions: mastitis (subclinical and clinical), lameness, paratuberculosis (Johne's disease), displaced abomasum, dystocia, metritis, milk fever, ovarian cysts, retained placenta, and ketosis (subclinical and clinical). Estimates of disease impacts on milk yield, fertility, and culling were collected from the literature, standardized, meta-analyzed using a variety of methods ranging from simple averaging to random-effects models, and adjusted for comorbidities to prevent overestimation. These comorbidity-adjusted disease impacts were then combined with a set of country-level estimates for lactational incidence or prevalence or both, herd characteristics, and price estimates within a series of Monte Carlo simulations that estimated and valued the economic losses due to these diseases. It was estimated that total annual global losses are US$65 billion (B). Subclinical ketosis, clinical mastitis, and subclinical mastitis were the costliest diseases modeled, resulting in mean annual global losses of approximately US$18B, US$13B, and US$9B, respectively. Estimated global annual losses due to clinical ketosis, displaced abomasum, dystocia, lameness, metritis, milk fever, ovarian cysts, paratuberculosis, and retained placenta were estimated to be US$0.2B, US$0.6B, US$0.6B, US$6B, US$5B, US$0.6B, US$4B, US$4B, and US$3B, respectively. Without adjustment for comorbidities, when statistical associations between diseases were disregarded, mean aggregate global losses would have been overestimated by 45%. Although annual losses were greatest in India (US$12B), the United States (US$8B), and China (US$5B), depending on the measure of losses used (losses as a percentage of gross domestic product, losses per capita, losses as a percentage of gross milk revenue), the relative economic burden of these dairy cattle diseases across countries varied markedly.

Preliminary In Vitro Evaluation of Silver, Copper and Gold Nanoparticles as New Antimicrobials for Pathogens That Induce Bovine Locomotion Disorders

Lameness is a crucial problem in dairy farming. It worsens the welfare of cattle, reduces the milk yield, and causes economic losses. The etiology of lameness is varied and the cattle's condition may be infectious or non-infectious. The aim of this research was to analyze the biocidal properties of silver (AgNPs), gold (AuNPs), and copper (CuNPs) nanoparticles against bacteria causing lameness in cattle. The isolated pathogens used were Aerococcus viridans, Corynebacterium freneyi, Corynebacterium xerosis, and Trueperella pyogenes. The tested concentrations of nanoparticles were 50, 25, 12.5, 6.25, 3.125, and 1.56 mg/L. The methods used included the isolation of pathogens using standard microbiological procedures and their identification using mass spectrometry, physicochemical analysis, transmission electron microscopy, and cytotoxicity tests. Studies have shown that AgNPs at 3.125 and 1.56 mg/L concentrations, and CuNPs at 25 and 12.5 mg/L concentrations, have strong biocidal properties, while AuNPs have the weakest antimicrobial properties. The very limited number of in vivo studies focusing on lameness prevention in cattle indicate that new solutions need to be developed. However, further studies are necessary to evaluate if nanoparticles (NPs) may, in the future, become components of innovative biocides used to prevent lameness in dairy cattle.

Enhancing hoof health and locomotion in crossbred dairy cows: impact of recycled manure solids bedding on lameness incidence and gait kinematics

Recycled manure solids has emerged as a promising alternative for animal bedding, owing to its economic feasibility, ready availability on farms, and soft, non-abrasive nature. This research aimed to assess the impact of recycled manure solids (RMS) bedding, combined with a conditioner containing 7.5% lime and 6% sodium hydrosulphate, on dairy cow welfare and gait kinematics over three months. Hock and knee injury scores, lameness incidence, and gait kinematic parameters were evaluated for animals housed on cement flooring (Control), RMS bedding (Treatment I), and conditioner-added RMS bedding (Treatment II) on days 0, 45, and 90 of the experiment with six crossbred cows in each group. The results revealed a significant reduction (p < 0.05) in lameness scores (5-point scale) for animals in both the RMS and conditioner-added RMS groups, with scores of 1.09 ± 0.05 and 1.04 ± 0.03, respectively, compared to those on cement floors. Moreover, a noteworthy decrease (p < 0.05) in knee and hock injury scores (4-point scale) was observed in the RMS groups, indicating a potentially positive impact on joint health. Gait kinematic analysis demonstrated that animals in the RMS (1.03 ± 0.04 m/s) and conditioner-added RMS (1.02 ± 0.06 m/s) groups exhibited higher walking speeds and increased step angles (158.59 ± 4.82° and 149.58 ± 3.85°) compared to their cement-floor counterparts. No significant changes (p > 0.05) were observed in stride length, step asymmetry, step length, and step width. The study concluded that the conditioner incorporated recycled manure solids resulting in a substantial decrease in lameness incidence and a reduction in hock and knee injuries among dairy cows. Additionally, the improved gait kinematics observed in non-lame animals suggest that this bedding combination positively influences overall animal well-being. These findings underscore the potential of sustainable bedding practices to enhance both physical health and locomotor behaviour in dairy cattle.

Evaluating machine learning algorithms to predict lameness in dairy cattle

Dairy cattle lameness represents one of the common concerns in intensive and commercial dairy farms. Lameness is characterized by gait-related behavioral changes in cows and multiple approaches are being utilized to associate these changes with lameness conditions including data from accelerometers, and other precision technologies. The objective was to evaluate the use of machine learning algorithms for the identification of lameness conditions in dairy cattle. In this study, 310 multiparous Holstein dairy cows from a herd in Northern Colorado were affixed with a leg-based accelerometer (Icerobotics® Inc, Edinburg, Scotland) to obtain the lying time (min/d), daily steps count (n/d), and daily change (n/d). Subsequently, study cows were monitored for 4 months and cows submitted for claw trimming (CT) were differentiated as receiving corrective claw trimming (CCT) or as being diagnosed with a lameness disorder and consequent therapeutic claw trimming (TCT) by a certified hoof trimmer. Cows not submitted to CT were considered healthy controls. A median filter was applied to smoothen the data by reducing inherent variability. Three different machine learning (ML) models were defined to fit each algorithm which included the conventional features (containing daily lying, daily steps, and daily change derived from the accelerometer), slope features (containing features extracted from each variable in Conventional feature), or all features (3 simple features and 3 slope features). Random forest (RF), Naive Bayes (NB), Logistic Regression (LR), and Time series (ROCKET) were used as ML predictive approaches. For the classification of cows requiring CCT and TCT, ROCKET classifier performed better with accuracy (> 90%), ROC-AUC (> 74%), and F1 score (> 0.61) as compared to other algorithms. Slope features derived in this study increased the efficiency of algorithms as the better-performing models included All features explored. However, further classification of diseases into infectious and non-infectious events was not effective because none of the algorithms presented satisfactory model accuracy parameters. For the classification of observed cow locomotion scores into severely lame and moderately lame conditions, the ROCKET classifier demonstrated satisfactory accuracy (> 0.85), ROC-AUC (> 0.68), and F1 scores (> 0.44). We conclude that ML models using accelerometer data are helpful in the identification of lameness in cows but need further research to increase the granularity and accuracy of classification.

Lameness in Cattle-Etiopathogenesis, Prevention and Treatment

The aim of this review was to analyse the health problem of lameness in dairy cows by assessing the health and economic losses. This review also presents in detail the etiopathogenesis of lameness in dairy cattle and examples of its treatment and prevention. This work is based on a review of available publications. In selecting articles for the manuscript, the authors focused on issues observed in cattle herds during their clinical work. Lameness in dairy cattle is a serious health and economic problem around the world. Production losses result from reduced milk yield, reduced feed intake, reproductive disorders, treatment costs, and costs associated with early culling. A significant difficulty in the control and treatment of lameness is the multifactorial nature of the disease; causes may be individual or species-specific and may be associated with the environment, nutrition, or the presence of concomitant diseases. An important role is ascribed to infectious agents of both systemic and local infections, which can cause problems with movement in animals. It is also worth noting the long treatment process, which can last up to several months, thus significantly affecting yield and production. Given the high economic losses resulting from lameness in dairy cows, reaching even >40% (depending on the scale of production), there seems to be a need to implement extensive preventive measures to reduce the occurrence of limb infections in animals. The most important effective preventive measures to reduce the occurrence of limb diseases with symptoms of lameness are periodic hoof examinations and correction, nutritional control, and bathing with disinfectants. A clean and dry environment for cows should also be a priority.

Invited review: Prevalence, risk factors, treatment, and barriers to best practice adoption for lameness and injuries in dairy cattle-A narrative review

Lameness and leg injuries are both painful and prevalent across the dairy industry, and are a major welfare concern. There has been a considerable amount of research focused on investigating the risk factors associated with lameness and injuries and how they might be prevented and treated. The objectives of this narrative review were to summarize herd-level prevalence estimates, risk factors, strategies for prevention, control, and treatment of these conditions, and the barriers to best practice adoption for lameness and injuries on dairy farms. There is a relatively high within-herd prevalence of lameness on dairy farms globally, with a recent systematic review estimating the mean prevalence at 22.8%. Similarly, there is a relatively high prevalence of hock injuries, with within-herd estimates ranging from 12% to 81% of cows affected. Knee and neck injuries have been reported to be less common, with 6% to 43% and 1% to 33%, respectively. Numerous risk factors have been associated with the incidence of lameness, notably housing (e.g., access to pasture, bedding depth, bedding type, flooring type, stall design), management (e.g., stall cleanliness, frequency of trimming, holding times, stocking density), and cow-level (e.g., body condition, parity, injured hocks) factors. Risk factors associated with hock injuries can be similarly classified into housing (e.g., bedding type and depth, outdoor access, parlor type, stall design), management (e.g., bedding depth, cleanliness), and cow (e.g., parity, days in milk, lameness) factors. Key preventative approaches for lameness include routine preventative and corrective hoof trimming, improving hoof cushioning and traction through access to pasture or adding rubber flooring, deep-bedded stalls, sand bedding, ensuring appropriate stocking densities, reduced holding times, and the frequent use of routine footbaths. Very little research has been conducted on hock, knee, and neck injury prevention and recovery. Numerous researchers have concluded that both extrinsic (e.g., time, money, space) and intrinsic (e.g., farmer attitude, perception, priorities, and mindset) barriers exist to addressing lameness and injuries on dairy farms. There are many diverse stakeholders in lameness and injury management including the farmer, farm staff, veterinarian, hoof trimmer, nutritionist, and other advisors. Addressing dairy cattle lameness and injuries must, therefore, consider the people involved, as it is these people who are influencing and implementing on-farm decisions related to lameness prevention, treatment, and control.

Sensitivity and specificity of mobility scoring for the detection of foot lesions in pasture-based Irish dairy cows

Lameness is an important production disease in dairy cows worldwide and has detrimental effects on cows' welfare, production, and reproductive performance, thus affecting the sustainability of dairy farming. Timely and effective detection of lameness allows for effective treatment, minimizing progression of disease, and maximizing the prognosis of recovery. Mobility scoring (MSc) is a 4 point (0-3) visual lameness scoring system that is the industry standard in several countries. However, few studies have examined the sensitivity (Se) and specificity (Sp) of MSc to detect foot lesions. The aim of this observational study was to determine the Se and Sp of MSc to detect foot lesions in dairy cattle in a pasture-based system. Five hundred ninety-five primi- and multiparous cows were randomly selected from 12 commercial Irish dairy farms and recruited for the study. Recruited cows were mobility scored and passed through a foot-paring crate where all 4 feet were lifted for examination. The team recorded the anatomical location and severity of any foot lesions present based on appearance only. Then, based on the type and severity of the lesions present, cows were classified according to 3 case definitions case definition 1: Any lesion present; case definition 2: Moderate lesions present (excluding minor lesions expected to have a low probability of affecting gait); and case definition 3: Severe lesions present (only including lesions most likely to result in a detectable gait abnormality). Sensitivity and Sp of MSc was calculated based on a threshold of MSc ≥2, defined as impaired (MSc = 2) or severely impaired (MSc = 3) mobility for each of the 3 case definitions, at the overall level and disaggregated by parity. The overall cow-level lesion prevalence based on the case definition 1 was 0.54 with significant between-herd variation. The overall Se and Sp of MSc for the detection of foot lesions were 0.18 and 0.96, 0.35 and 0.94, 0.43 and 0.94 for the case definitions 1, 2, and 3, respectively. Our findings showed poor Se, but high Sp of MSc for the detection of cows with foot lesions in a pasture-based system.

Unlocking insights: text mining analysis on the health, welfare, and behavior of cows in automated milking systems

Automated Milking Systems (AMS) have undergone significant evolution over the past 30 yr, and their adoption continues to increase, as evidenced by the growing scientific literature. These systems offer advantages such as a reduced milking workload and increased milk yield per cow. However, given concerns about the welfare of farmed animals, studying the effects of AMS on the health and welfare of animals becomes crucial for the overall sustainability of the dairy sector. In the last few years, some analysis conducted through text mining (TM) and topic analysis (TA) approaches have become increasingly widespread in the livestock sector. The aim of the study was to analyze the scientific literature on the impact of AMS on dairy cow health, welfare, and behavior: the paper aimed to produce a comprehensive analysis on this topic using TM and TA approaches. After a preprocessing phase, a dataset of 427 documents was analyzed. The abstracts of the selected papers were analyzed by TM and a TA using Software R 4.3.1. A Term Frequency-Inverse Document Frequency (TFIDF) technique was used to assign a relative weight to each term. According to the results of the TM, the ten most important terms, both words and roots, were feed, farm, teat, concentr, mastiti, group, SCC (somatic cell count), herd, lame and pasture. The 10 most important terms showed TFIDF values greater than 3.5, with feed showing a value of TFIDF of 5.43 and pasture of 3.66. Eight topics were selected with TA, namely: 1) Cow traffic and time budget, 2) Farm management, 3) Udder health, 4) Comparison with conventional milking, 5) Milk production, 6) Analysis of AMS data, 7) Disease detection, 8) Feeding management. Over the years, the focus of documents has shifted from cow traffic, udder health and cow feeding to the analysis of data recorded by the robot to monitor animal conditions and welfare and promptly identify the onset of stress or diseases. The analysis reveals the complex nature of the relationship between AMS and animal welfare, health, and behavior: on one hand, the robot offers interesting opportunities to safeguard animal welfare and health, especially for the possibility of early identification of anomalous conditions using sensors and data; on the other hand, it poses potential risks, which requires further investigations. TM offers an alternative approach to information retrieval in livestock science, especially when dealing with a substantial volume of documents.

Routine hoof-trimming data provides insight into the occurrence of claw lesions in Holstein herds in the central region of South Africa

Claw lesions in dairy cows contribute significantly to lameness, causing distress and discomfort for affected cows and raising welfare concerns. Despite increased awareness, lameness incidence continues to rise. Defining and recording claw traits are particularly problematic. In South Africa (SA), claw data is limited to paper-based records kept by private hoof trimmers. This research analysed claw-trimming data from five dairy farms over 6 years to examine the occurrence and recording of claw lesions in SA Holstein cattle. Lesion identification followed the Claw Lesion Identification in Dairy Cattle brochure. Among the recorded lesions, digital dermatitis (DD) had the highest prevalence (64.02%), followed by sole ulcers (SU; 8.59%), white line disease (WLD; 6.27%), and sole haemorrhage (SH; 4.28%), and most lesions occurred in the rear feet. Chi-square tests and correspondence analysis (CA) were employed to explore the relationships between lesions, feet, and housing. Results indicated that the prevalence of SU and SH showed high similarity for foot and lesion association, and that these were more highly associated with the rear feet. Additionally, the prevalence of DD and interdigital phlegmon were strongly associated, and closely associated with SU, and all these lesions were associated with both dirt lot and free-stall housing systems. CA further confirmed a close association between WLD and SH, and the prevalence of these lesions in the combination housing system. Results of this study highlight the complexity of lesion data and that specific associations between lesions could lead to simplifying the recording thereof. Consolidating the most informative claw lesions into categories will aid in the practical prevention, management, and treatment of lameness on-farm.

Prevalence of lameness on pasture-based New Zealand dairy farms: An observational study

To understand the current impact of lameness on a system, it is important to define lameness prevalence across a range of dairy farms in that system. Prevalence estimates from dairy systems where cows are permanently managed at pasture are uncommon, although the limited data suggest that they have a lower lameness prevalence than housed cattle. One hundred and 20 farms from eight of the major dairying regions of New Zealand were randomly enrolled into a cross-sectional lameness prevalence study. On each of the farms, trained observers lameness scored cattle on two occasions, between October-December (spring, coinciding with peak lactation for most farms) and between January-March (summer, late lactation for most farms). At each visit, all lactating animals were scored using a four-point 0-3 scoring system, and included animals that had previously been identified as lame by the farmer. Animals with a lameness score (LS) ≥2 were defined as lame. Mixed logistic regression models assessed the interaction between region and season and island and season, respectively, and differences between the lameness prevalence within farm across the two seasons reported descriptively. A total of 116,317 locomotion scores over two events were conducted across the 120 farms. At the spring scoring event, 2128/60,007 (3.5 %) cows had a LS ≥2 and 1868/56,310 (3.3 %) cows had a LS ≥ 2 at the summer scoring event. At the farm level, across both scoring events, median lameness prevalence was 2.8 (interquartile range 1.5 - 4.5) %, with a range of 0.0-17.0 %. The median farm-level prevalence of LS = 3 was 0.5 % with a range of 0-4.6 %. The effect of timing of scoring was modified by region (p < 0.001), and island (p = 0.006) and at the individual farm level, differences between spring and summer farm level lameness prevalence were generally small (interquartile range: -1.8 to 1.0 %) but potentially large on individual farms (range from -12.3 % to 7.6 %). The median farm-level lameness prevalence estimate of 2.8 % across a random representative sample of New Zealand dairy farms give confidence that the overall prevalence of cattle lameness on New Zealand dairy farms is low. This adds to the growing evidence that pasture is a good management system with respect to hoof health. The evidence of strong seasonality of lameness was lacking. Instead of using lameness scoring to identify farms with large lameness problems, lameness scoring should be encouraged to farmers as a tool to improve the identification of lame animals.

Crowd sourcing remote comparative lameness assessments for dairy cattle

Lameness assessments are rarely conducted routinely on dairy farms and when completed typically underestimate lameness prevalence, hampering early diagnosis and treatment. A well-known feature of many perceptual tasks is that relative assessments are more accurate than absolute assessments, suggesting that creating methods that allow for the relative scoring of which cow is more lame will allow for reliable lameness assessments. Here we developed and tested a remote comparative lameness assessment method: we recruited nonexperienced crowd workers via an online platform and asked them to watch 2 videos side-by-side, each showing a cow walking, and to identify which cow was more lame and by how much (on a scale of -3 to 3). We created 11 tasks, each with 10 video pairs for comparison, and recruited 50 workers per task. All tasks were also completed by 5 experienced cattle lameness assessors. We evaluated data filtering and clustering methods based on worker responses and determined the agreement among workers, among experienced assessors, and between these groups. A moderate to high interobserver reliability was observed (intraclass correlation coefficient, ICC = 0.46 to 0.77) for crowd workers and agreement was high among the experienced assessors (ICC = 0.87). Average crowd-worker responses showed excellent agreement with the average of experienced assessor responses (ICC = 0.89 to 0.91), regardless of data processing method. To investigate if we could use fewer workers per task while still retaining high agreement with experienced assessors, we randomly subsampled 2 to 43 (1 less than the minimum number of workers retained per task after data cleaning) workers from each task. The agreement with experienced assessors increased substantially as we increased the number of workers from 2 to 10, but little increase was observed after 10 or more workers were used (ICC > 0.80). The proposed method provides a fast and cost-effective way to assess lameness in commercial herds. In addition, this method allows for large-scale data collection useful for training computer vision algorithms that could be used to automate lameness assessments on farm.

A cross-sectional study of the prevalence of lameness and digital dermatitis in dairy cattle herds in Egypt

BACKGROUND

Lameness is a significant problem for the dairy industry worldwide. No previous studies have evaluated the prevalence of lameness or digital dermatitis (DD) in dairy cattle herds in Egypt. A total of 16,098 dairy cows from 55 dairy herds in 11 Egyptian governorates underwent visual locomotion scoring using a 4-point scoring system. Cows that had a lameness score ≥ 2 were considered clinically lame. Following manure removal with water and using a flashlight, the cows' hind feet were examined in the milking parlour to identify DD lesions and classify with M-score. Furthermore, each cow was assigned a hock score (a 3-point scale) and a hygiene score (a 4-point scale). The cow-, within-and between-herd prevalence of lameness and DD and associated 95% confidence intervals (CI) were calculated. The prevalence of hock lesions and poor cow hygiene was also calculated.

RESULTS

Of the examined cows, 6,883 were found to be clinically lame (42.8%, 95% CI = 42.0-43.5%). The average within-herd prevalence of lameness was 43.1% (95% CI = 35.9-50.3%). None of the dairy herds recruited into the study were found to be free from clinical lameness. The average within-herd prevalence of DD was 6.4% (95% CI = 4.9-8.0%). The herd-level prevalence of DD was 92.7% (95% CI = 85.9-99.6%). Active DD lesions (M1, M2, M4.1) were identified in 464 cows (2.9%) while inactive lesions (M3, M4) were identified in 559 cows (3.5%). The within-herd prevalence of hock lesions (score 2 or 3) was 12.6% (95% CI = 4.03-21.1%) while a severe hock lesion had within-herd prevalence of 0.31% (95% CI = 0.12-0.51%). Cow-level prevalence of hock lesions was 6.2% (n = 847, 95% CI = 5.8-6.2%). The majority of examined cows had a hygiene score of 4 (n = 10,814, prevalence = 70.3%, 95% CI = 69.5-71%).

CONCLUSIONS

The prevalence of lameness was higher than prevalence estimates reported for other countries which could be due to differing management and/or environmental factors. DD was identified at lower prevalence in most herds but with high herd-level prevalence. Poor cow hygiene was notable in most herds. Measures to reduce the prevalence of lameness and to improve cow hygiene in dairy cattle herds in Egypt are therefore needed.

Single-step genome-wide association analyses of claw horn lesions in Holstein cattle using linear and threshold models

BACKGROUND

Lameness in dairy cattle is primarily caused by foot lesions including the claw horn lesions (CHL) of sole haemorrhage (SH), sole ulcers (SU), and white line disease (WL). This study investigated the genetic architecture of the three CHL based on detailed animal phenotypes of CHL susceptibility and severity. Estimation of genetic parameters and breeding values, single-step genome-wide association analyses, and functional enrichment analyses were performed.

RESULTS

The studied traits were under genetic control with a low to moderate heritability. Heritability estimates of SH and SU susceptibility on the liability scale were 0.29 and 0.35, respectively. Heritability of SH and SU severity were 0.12 and 0.07, respectively. Heritability of WL was relatively lower, indicating stronger environmental influence on the presence and development of WL than the other two CHL. Genetic correlations between SH and SU were high (0.98 for lesion susceptibility and 0.59 for lesion severity), whereas genetic correlations of SH and SU with WL also tended to be positive. Candidate quantitative trait loci (QTL) were identified for all CHL, including some on Bos taurus chromosome (BTA) 3 and 18 with potential pleiotropic effects associated with multiple foot lesion traits. A genomic window of 0.65 Mb on BTA3 explained 0.41, 0.50, 0.38, and 0.49% of the genetic variance for SH susceptibility, SH severity, WL susceptibility, and WL severity, respectively. Another window on BTA18 explained 0.66, 0.41, and 0.70% of the genetic variance for SH susceptibility, SU susceptibility, and SU severity, respectively. The candidate genomic regions associated with CHL harbour annotated genes that are linked to immune system function and inflammation responses, lipid metabolism, calcium ion activities, and neuronal excitability.

CONCLUSIONS

The studied CHL are complex traits with a polygenic mode of inheritance. Most traits exhibited genetic variation suggesting that animal resistance to CHL can be improved with breeding. The CHL traits were positively correlated, which will facilitate genetic improvement for resistance to CHL as a whole. Candidate genomic regions associated with lesion susceptibility and severity of SH, SU, and WL provide insights into a global profile of the genetic background underlying CHL and inform genetic improvement programmes aiming at enhancing foot health in dairy cattle.

Genetic parameters of sole lesion recovery in Holstein cows

Sole hemorrhage and sole ulcers, referred to as sole lesions, are important causes of lameness in dairy cattle. The objective of this study was to estimate the genetic parameters of a novel trait reflecting how well cows recovered from sole lesions and the genetic correlation of this trait with overall susceptibility to sole lesions. A cohort of Holstein dairy cows was prospectively enrolled on 4 farms and assessed at 4 timepoints: before calving, immediately after calving, in early lactation, and in late lactation. At each timepoint, sole lesions were recorded at the claw level by veterinary surgeons and used to define 2 binary traits: (1) susceptibility to sole lesions-whether animals were affected with sole lesions at least once during the study or were unaffected at every assessment, and (2) sole lesion recovery-whether sole lesions healed between early and late lactation. Animals were genotyped and pedigree details extracted from the national database. Analyses were conducted with BLUPF90 software in a single-step framework; genetic parameters were estimated from animal threshold models using Gibbs sampling. The genetic correlation between both traits was approximated as the correlation between genomic estimated breeding values, adjusting for their reliabilities. A total of 2,025 animals were used to estimate the genetic parameters of sole lesion susceptibility; 44% of animals recorded a sole lesion at least once during the study period. The heritability of sole lesion susceptibility, on the liability scale, was 0.25 (95% highest density interval = 0.16-0.34). A total of 498 animals were used to estimate the genetic parameters of sole lesion recovery; 71% of animals had recovered between the early and late lactation assessments. The heritability of sole lesion recovery, on the liability scale, was 0.27 (95% highest density interval = 0.02-0.52). The approximate genetic correlation between each trait was -0.11 (95% confidence interval = -0.20 to -0.02). Our results indicate that recovery from sole lesions is heritable. If this finding is corroborated in further studies, it may be possible to use selective breeding to reduce the frequency of chronically lame cows. As sole lesion recovery appears to be weakly genetically related to sole lesion susceptibility, successful genetic improvement of sole lesion recovery would benefit from selection on this trait directly.

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.

Estimating the burden of multiple endemic diseases and health conditions using Bayes’ Theorem: A conditional probability model applied to UK dairy cattle

The Global Burden of Animal Diseases (GBADs) is an international collaboration aiming, in part, to measure and improve societal outcomes from livestock. One GBADs objective is to estimate the economic impact of endemic diseases in livestock. However, if individual disease impact estimates are linearly aggregated without consideration for associations among diseases, there is the potential to double count impacts, overestimating the total burden. Accordingly, the authors propose a method to adjust an array of individual disease impact estimates so that they may be aggregated without overlap. Using Bayes’ Theorem, conditional probabilities were derived from inter-disease odds ratios in the literature. These conditional probabilities were used to calculate the excess probability of disease among animals with associated conditions, or the probability of disease overlap given the odds of coinfection, which were then used to adjust disease impact estimates so that they may be aggregated. The aggregate impacts, or the yield, fertility, and mortality gaps due to disease, were then attributed and valued, generating disease-specific losses. The approach was illustrated using an example dairy cattle system with input values and supporting parameters from the UK, with 13 diseases and health conditions endemic to UK dairy cattle: cystic ovary, disease caused by gastrointestinal nematodes, displaced abomasum, dystocia, fasciolosis, lameness, mastitis, metritis, milk fever, neosporosis, paratuberculosis, retained placenta, and subclinical ketosis. The diseases and conditions modelled resulted in total adjusted losses of £ 404/cow/year, equivalent to herd-level losses of £ 60,000/year. Unadjusted aggregation methods suggested losses 14–61% greater. Although lameness was identified as the costliest condition (28% of total losses), variations in the prevalence of fasciolosis, neosporosis, and paratuberculosis (only a combined 22% of total losses) were nearly as impactful individually as variations in the prevalence of lameness. The results suggest that from a disease control policy perspective, the costliness of a disease may not always be the best indicator of the investment its control warrants; the costliness rankings varied across approaches and total losses were found to be surprisingly sensitive to variations in the prevalence of relatively uncostly diseases. This approach allows for disease impact estimates to be aggregated without double counting. It can be applied to any livestock system in any region with any set of endemic diseases, and can be updated as new prevalence, impact, and disease association data become available. This approach also provides researchers and policymakers an alternative tool to rank prevention priorities.

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Three approaches to impact aggregation for multiple endemic diseases explored.

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Flexible method proposed to avoid double counting impacts within a livestock system.

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Illustrated using 13 endemic diseases and health conditions in UK dairy cattle.

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Provides an alternative perspective on ranking disease prevention priorities.

Association between a genetic index for lameness resistance and the incidence of claw horn lesions in Holstein cows

BACKGROUND

This study aimed to determine the association between the lameness advantage genetic index and four outcomes: sole haemorrhage (SH), sole ulcers (SU), white line lesions (WL), and lameness during mobility scoring.

METHODS

We enrolled 2352 Holstein cows from four predominantly housed dairy herds in the UK. Cows were mobility scored and foot lesions recorded at four time points from before calving to late lactation. Cows were genotyped and genetic indexes were assigned to each cow following national genetic evaluations. Lameness records and genetic indexes were matched for 2107 cows. Four separate multivariable logistic regression models, which included farm and parity as covariables, were used to quantify the association between the lameness advantage index and whether animals were affected by SH, SU, WL, or lameness.

RESULTS

The odds ratios (95% confidence intervals) for one-point increases in the lameness advantage index were 0.79 (0.72-0.86), 0.68 (0.59-0.78), 0.94 (0.84-1.04), and 0.82 (0.74-0.91) for SH, SU, WL, and lameness, respectively. The same trends were present when the sire's lameness advantage index was evaluated in place of the animal's own, although the strength of this association was generally weaker.

CONCLUSION

The lameness advantage index is associated with SH, SU, and lameness, therefore selection on the lameness advantage index could be considered in herds aiming to reduce lameness. Where genomic testing of heifers is not conducted, sire lameness advantage index may still be effective to reduce SH and SU incidence.

Lameness in Dairy Cow Herds: Disease Aetiology, Prevention and Management

As livestock production systems have changed to intensive commercial structures to meet the increasing demand for animal-based products, there has been an increase in food production diseases, subsequently resulting in animal welfare issues. After mastitis and infertility, lameness is one of the three major issues affecting dairy cattle globally, resulting in reduced productivity, economic losses, and animal welfare problems. Lameness is associated with reduced milk yield, lack of weight gain, poor fertility, and frequently, animal culling. Environmental (temperature, humidity) and animal risk factors contribute to disease severity, making this multifaceted disease difficult to eradicate and control. As such, prevalence rates of lameness in dairy herds ranges from 17% to 35% globally. Clinical lameness is often treated with antibiotic therapy, which is undesirable in food-producing animals, as outlined in the One Health and the European Farm to Fork food sustainability goals. Lameness is not a single disease in dairy cows but is the manifestation a range of issues, making lameness control one of the greatest challenges in dairy farming. Lameness prevention, therefore, must be a key focus of farm management and sustainable food production. There is an urgent need to establish farm-level aetiology of disease, promote the recognition of lameness, and implement effective control measures to lower incidence and transmission of disease within herds.

The estimation and interpretation of ordered logit models for assessing the factors connected with the productivity of Holstein-Friesian dairy cows in Egypt

The incorporation of novel technologies such as artificial intelligence, data mining, and advanced statistical methodologies have received wide responses from researchers. This study was designed to model the factors impacting the actual milk yield of Holstein-Friesian cows using the proportional odds ordered logit model (OLM). A total of 8300 lactation records were collected for cows calved between 2005 and 2019. The actual milk yield, the outcome variable, was categorized into three levels: low (< 4500 kg), medium (4500-7500 kg), and high (> 7500 kg). The studied predictor variables were age at first calving (AFC), lactation order (LO), days open (DO), lactation period (LP), peak milk yield (PMY), and dry period (DP). The proportionality assumption of odds using the logit link function was verified for the current datasets. The goodness-of-fit measures revealed the suitability of the ordered logit models to datasets structure. Results showed that cows with younger ages at first calving produce two times higher milk quantities. Also, longer days open were associated with higher milk yield. The highest amount of milk yield was denoted by higher lactation periods (> 250 days). The peak yield per kg was significantly related to the actual yield (P < 0.05). Moreover, shorter dry periods showed about 1.5 times higher milk yield. The greatest yield was observed in the 2nd and 4th parities, with an odds ratio (OR) equal to 1.75, on average. In conclusion, OLM can be used for analyzing dairy cows' data, denoting fruitful information as compared to the other classical regression models. In addition, the current study showed the possibility and applicability of OLM in understanding and analyzing livestock datasets suited for planning effective breeding programs.

Preventive Hoof Trimming and Animal-Based Welfare Measures Influence the Time to First Lameness Event and Hoof Lesion Prevalence in Dairy Cows

Background: The objectives of this study were to, (1) investigate the impact of the Dutch five-step hoof trimming (HT) technique on time to lameness and hoof lesion prevalence in grazing (GR) and non-grazing (NGR) dairy cows, and (2) determine the association between potential benefits of HT and animal-based welfare measures during lactation. A total of 520 non-lame cows without hoof lesions from 5 dairy farms (GR = 2, NGR = 3) were enrolled at early (within 30 days in milk; DIM) and late lactation (above 200 DIM), and randomly allocated to either trimmed (HGR or HNGR) or control groups (CON-GR and CON-NGR). Locomotion scores, body condition, hock condition, leg hygiene, and hoof health were assessed at monthly intervals until the following 270 days in milk. The data were analyzed using Kaplan-Meier survival analysis, multivariable Cox, and logistic regression models. The overall incidence rate of lameness was 36.2 cases/100 cows/month, with corresponding rates of 27.4, 31.9, 48.4, and 45.8 cases/100 cows/month in HGR, HNGR, CON-GR, and CON-NGR, respectively. Time to first lameness event was significantly higher in HGR (mean ± S.E; 8.12 ± 0.15) compared to CON-GR (7.36 ± 0.26), and in HNGR (8.05 ± 0.16) compared to CON-NGR (7.39 ± 0.23). The prevalence of hoof lesions in the enrolled cows was 36.9%, with a higher occurrence in CON-GR (48.8%) than HGR (23.2%), and in CON-NGR (52.6%) compared to HNGR (32.2%). The majority of hoof lesions were non-infectious in grazing (HGR vs. CON-GR; 21.3 vs. 33.3%) and non-grazing herds (HNGR vs. CON-NGR; 25.0 vs. 40.4%). The risk of lameness was higher in underconditioned cows (Hazard ratio; HR = 3.1, 95% CI 1.2-7.4), presence of hoof lesion (HR = 33.1, 95% CI 17.6-62.5), and there was variation between farms. Aside HT, lower parity (OR = 0.4, 95% CI 0.2-0.8), normal hock condition (OR = 0.06; 95% 0.01-0.29), and absence of overgrown hoof (OR = 0.4; 95% 0.2-0.7) were protective against non-infectious hoof lesions. Functional HT is beneficial as a lameness preventive strategy during lactation; however, ensuring older cows are in good body condition and free from hock injuries are equally important.