Associating cow characteristics with mobility scores in pasture-based dairy cows

Assessing lameness prevalence and associated risk factors in crossbred dairy cows across diverse management environments

BACKGROUND

A thorough understanding of lameness prevalence is essential for evaluating the impact of this condition on the dairy industry and assessing the effectiveness of preventive strategies designed to minimize its occurrence. Therefore, this cross-sectional study aimed to ascertain the prevalence of lameness and identify potential risk factors associated with lameness in Holstein Friesian crossbred cows across both commercial and smallholder dairy production systems in Bengaluru Rural District of Karnataka, India.

METHODS

The research encompassed six commercial dairy farms and 139 smallholder dairy farms, involving a total of 617 Holstein Friesian crossbred cattle. On-site surveys were conducted at the farms, employing a meticulously designed questionnaire. Lameness in dairy cattle was assessed subjectively using a locomotion scoring system. Both bivariate and binary logistic regression models were employed for risk assessment, while principal components analysis (PCA) was conducted to address the high dimensionality of the data and capture the underlying structure of the explanatory variables.

RESULTS

The overall lameness prevalence of 21.9% in commercial dairy farms and 4.6% in smallholder dairy farms. Various factors such as age, body weight, parity, body condition score (BCS), floor type, hock and knee injuries, animal hygiene, provision of hoof trimming, and the presence of hoof lesions were found to be significantly associated with lameness. Binary logistic regression analysis indicated that the odds of lameness in crossbred cows increased with higher parity, decreased BCS, presence of hard flooring, poor animal hygiene, and the existence of hoof lesions. These factors were identified as potential risk factors for lameness in dairy cows. Principal component analysis unveiled five components explaining 71.32% of the total variance in commercial farms and 61.21% in smallholder dairy farms. The extracted components demonstrated higher loadings of housing and management factors (such as hoof trimming and provision of footbath) and animal-level factors (including parity, age, and BCS) in relation to lameness in dairy cows.

CONCLUSIONS

The findings suggest that principal component analysis effectively reduces the dimensionality of risk factors. Addressing these identified risk factors for lameness is crucial for the strategic management of lameness in dairy cows. Future research in India should investigate the effectiveness of management interventions targeted at the identified risk factors in preventing lameness in dairy cattle across diverse environments.

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.

Effects of extending dairy cow longevity by adjusted reproduction management decisions on partial net return and greenhouse gas emissions: A dynamic stochastic herd simulation study

Prolonging dairy cattle longevity is regarded as one of the options to contribute to more sustainable milk production. Since failure to conceive is one of the main reasons for culling, this study investigates how adjustments in reproduction management affect partial net return at herd level and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of reproduction decisions that extend cattle longevity on milk yield, calving interval and pregnancy rate were derived from actual performance of Dutch commercial dairy cows over multiple lactations. The model simulated lactations, calving and health status events of individual cows for herds of 100 cows. Scenarios evaluated differed in the maximum number of consecutive artificial insemination (AI) attempts (4, 5 or 6 services), or the production threshold (20, 15, or 10 kg milk per day) at which cows that failed to conceive are culled (reproductive culling). Annual partial net return was computed from revenues of sold milk, calves and slaughtered cows, and the costs from feed consumption, rearing replacement heifers, AI services and treatment for clinical mastitis and lameness. Greenhouse gas emissions were computed for feed production, enteric fermentation, and manure management, and were expressed as total CO2 equivalents. Average age at culling increased with an increased maximum number of AI services. This increase was larger when going from a maximum of 4 to 5 AI attempts (108 d) than from a maximum of 5 to 6 attempts (47 d). Similarly, the average age at culling increased from 1,968 to 2,040 and 2,132 d when the threshold for reproductive culling decreased from 20, to 15 and 10 kg milk per day, respectively. Average annual partial net return increased by 1.1% from €165,850 per 100 cows at a maximum of 4 AIs to €167,670 per 100 cows at a maximum of 6 AIs, and increased by 4.3% from €161,210 per 100 cows at a reproductive culling threshold of 10 kg/day to €168,190 per 100 cows at a threshold of 20 kg/day. Greenhouse gas emissions decreased by 1.2% from 0.926 to 0.915 kg CO2 equivalents per kg fat-and-protein-corrected milk (FPCM) with an increase in a maximum number of AIs from 4 to 6 AIs. Conversely, greenhouse gas emissions increased by 0.2% from 0.926 kg at a threshold of reproductive culling of 20 kg/day to 0.928 kg CO2 equivalents per kg FPCM at a threshold of 10 kg/day. Although lowering the threshold for reproductive culling has the potential to extend cattle longevity more than increasing the maximum number of AI services, only the increase in AI services benefits a farm's partial net return, while reducing greenhouse gas emissions.

A new approach and insights on modelling the impact of production diseases on dairy cow welfare

Animal welfare is becoming an important consideration in animal health-related decision-making. Integrating considerations of animal welfare into the decision-making process of farmers involves recognising the significance of health disorder impacts in relation to animal welfare. Yet little research quantifies the impact, making it difficult to include animal welfare in the animal health decision-making process. Quantifying the impact of health disorders on animal welfare is incredibly challenging due to empirical animal-based data collection constraints. An approach to circumvent these constraints is to rely on expert knowledge whereby perceived welfare impairment weights are indicative of the negative welfare effect. In this research, we propose an expertise-based method to quantify the perceived impact of sub-optimal mobility (SOM) on the welfare of dairy cows, because of its welfare importance. We first quantified perceived welfare impairment weights of SOM by eliciting expert knowledge using adaptive conjoint analysis (ACA). Second, using the perceived welfare impairment weights, we derived the perceived welfare disutility (i.e., perceived negative welfare effect) of mobility scores 1-5 (1 = optimal mobility, 5 = severely impaired mobility). Third, using the perceived welfare disutility per mobility score, we quantified the perceived welfare impact at case- and herd-level of SOM for different SOM severity. Results showed that perceived welfare disutility increased with each increase in mobility score. However, the perceived welfare impact of SOM cases with lower mobility scores was higher compared to SOM cases with higher mobility scores. This was because of the longer-lasting duration of the SOM cases with lower mobility scores. Moreover, the perceived herd-level welfare impact was largely due to SOM cases with lower mobility scores because of the longer duration and more frequent incidence compared to the SOM cases with higher mobility scores. These results entail that better welfare of dairy cows with respect to SOM can be achieved if lower mobility scores are detected and treated sooner. Our research demonstrates a novel approach that quantifies the perceived impact of health disorders on animal welfare when empirical evidence is limited.

Associations of cow and farm characteristics with cow-level lameness using data from an extensive cross-sectional study across 3 structurally different dairy regions in Germany

The aim of the present study was to evaluate the associations between milk recording data, body condition score (BCS), housing factors, management factors, and lameness in freestall-housed dairy cows in 3 structurally different regions in Germany. These regions substantially vary regarding herd size, breeds, access to pasture, farm management (family run or company owned), and percentage of organic farms. The data used was collected in a large cross-sectional study from 2016 to 2019. A total of 58,144 cows from 651 farms in 3 regions of Germany (North, East, and South) was scored for locomotion and body condition. Additionally, data on milk yield, milk composition, breed, age, as well as information on housing and management were retrieved. One mixed-logistic regression model was fitted per region to evaluate the association of the data with the target variable "lame" and to allow for a comprehensive reflection across different kinds of farming types. In all regions, undercondition (BCS lower than recommended for the lactation stage; North: odds ratio [OR] 2.15, CI 1.96-2.34; East: OR 2.66, CI 2.45-2.88; South: OR 2.45, CI 2.01-2.98) and mid-lactation stage (102-204 d in milk; North: OR 1.15, CI 1.05-1.27; East: OR 1.24, CI 1.17-1.32; South: OR 1.38, CI 1.18-1.62) were associated with higher odds for lameness, whereas overcondition (BCS higher than recommended for the lactation stage; North: OR 0.51, CI 0.44-0.60; East: OR 0.51, CI 0.48-0.54; South: OR 0.65, CI 0.54-0.77) and parity of 1 or 2 was associated with lower odds (parity 1 = North: OR 0.32, CI 0.29-0.35; East: OR 0.19, CI 0.18-0.20; South: OR 0.28, CI 0.24-0.33; parity 2 = North: OR 0.51, CI 0.47-0.46; East: OR 0.41, CI 0.39-0.44; South: OR 0.49, CI 0.42-0.57), irrespective of the regional production characteristics. Low energy-corrected milk yield was associated with higher odds for lameness in South and North (North: OR 1.16, CI 1.05-1.27; South: OR 1.43, CI 1.22-1.69). Further factors such as pasture access for cows (North: OR 0.64, CI 0.50-0.82; and South: OR 0.65, CI 0.47-0.88), milk protein content (high milk protein content = North: OR 1.34, CI 1.18-1.52; East: OR 1.17, CI 1.08-1.28; low milk protein content = North: OR 0.79, CI 0.71-0.88; East: OR 0.84, CI 0.79-0.90), and breed (lower odds for "other" [other breeds than German Simmental and German Holstein] in East [OR 0.47, CI 0.42-0.53] and lower odds both for German Holstein and "other" in South [German Holstein: OR 0.62, CI 0.43-0.90; other: OR 0.46, CI 0.34 - 0.62]) were associated with lameness in 2 regions, respectively. The risk of ketosis (higher odds in North: OR 1.11, CI 1.01-1.22) and somatic cell count (higher odds in East: increased (>39.9 cells × 1,000/mL): OR 1.10; CI 1.03-1.17; high (>198.5 cells × 1,000/mL): OR 1.08; CI 1.01-1.06) altered the odds for lameness in 1 region, respectively. Cows from organic farms had lower odds for lameness in all 3 regions (North: OR 0.18, CI 0.11-0.32; East: OR 0.39, CI 0.28-0.56; South: OR 0.45, CI 0.29-0.68). As the dairy production systems differed substantially between the different regions, the results of this study can be viewed as representative for a wide variety of loose-housed dairy systems in Europe and North America. The consistent association between low BCS and lameness in all regions aligns with the previous literature. Our study also suggests that risk factors for lameness can differ between geographically regions, potentially due to differences in which dairy production system is predominantly used and that region-specific characteristics should be taken into account in comparable future projects.

Evaluation of blood serum iron concentration as an alternative biomarker for inflammation in dairy cows

This study aimed to clarify the relationship between acute phase protein (APP) concentrations and serum Fe concentrations to determine whether serum iron (Fe) can be clinically applied as a substitute for APPs in cows. One hundred five Holstein-Friesian breed lactating dairy cows were enrolled in this study. Cows with inflammatory diseases were 16 subclinical, and 15 severe mastitis cows, in addition to 15 mild and 16 severe sole ulcer cows. The plasma haptoglobin (HPT), alpha-1 acid glycoprotein (AGP), SAA, serum Fe levels, and other biochemical parameters in the cows were measured. The two-sample t-tests and multiple logistic regression analysis were used to compare the control and inflammatory disease groups. ROC analysis was used to evaluate the ability to diagnose inflammation disease. From the results, the proposed diagnostic cutoff value for plasma SAA and serum Fe concentrations to identify dairy cows with inflammatory diseases based on analyses of ROC curves were set at > 3.65 mg/l and < 120.50 µg/dl, respectively. Therefore, instead of using expensive inflammatory markers to evaluate the inflammatory state at the first treatment day for inflammatory diseases in cow, it shows the useful for screening with serum Fe concentration that can be measured easily and inexpensively as alternative inflammatory biomarkers.

Effects of increased grazing intensity during the early and late grazing periods on the welfare of spring-calving, pasture-based dairy cows

The objective of this study was to identify potential effects of increased grazing intensity, characterized by differing pasture availability and stocking rate, on indicators of welfare during both early and late grazing periods. Seventy spring-calving, pasture-based Holstein-Friesian and cross-bred dairy cows, averaging 35 ± 16 d in milk on the first day of data collection, were assigned to 3 treatments (20-26 cows/treatment) representing a range in grazing intensity: LO (high pasture availability, 980 kg DM/ha opening cover, 2.75 cows/ha, 90:10% pasture:concentrate diet), MOD (medium pasture availability, 720 kg DM/ha opening cover, 2.75 cows/ha, 90:10% pasture:concentrate diet), and HI (low pasture availability, 570 kg DM/ha opening cover, 3.25 cows/ha, 80:20% pasture:concentrate diet); representative of current, best practice and proposed production levels respectively for this system. Welfare indicators were locomotion score, digital dermatitis and white line disease, rumen fill, ocular and nasal discharge, integument damage to the neck-back and hock regions, and lying time. Data were collected during a 5-wk early grazing period in spring (EG) and a 7-wk late grazing period in autumn (LG). Average daily lying time was recorded for 8 to 10 focal cows per treatment. Results demonstrated only minor treatment effects. Cows on MOD [odds ratio (OR) = 3.11] and HI (OR = 1.95) were more likely to display nasal discharge compared with LO. Cows on MOD tended to have more damage to the skin on the neck-back region than LO (OR = 4.26). Total locomotion score (maximum = 25) was greater on LOW (7.1 ± 0.20) compared with HI (6.5 ± 0.19). Average lame cow prevalence for EG and LG respectively was 15.3 ± 3.12% and 39.2 ± 3.00% (LO), 20.0 ± 2.58% and 24.2 ± 5.69% (MOD), and 14.9 ± 4.79% and 17.0 ± 3.44% (HI). Cows on HI were less likely to have impaired walking speed than either LO (OR = 0.24) or MOD (OR = 0.29). Cows on both HI (OR = 0.36) and MOD (OR = 0.40) were less likely to display impaired abduction or adduction compared with those on LO. An interaction between treatment and period revealed longer lying times for cows on LO (10.6 h/d ± 0.39) compared with both MOD and HI (8.7 ± 0.43 and 8.4 ± 0.41 h/d) during EG only. The greatest effects were across grazing periods, with all indicators except rumen fill and locomotion score demonstrating improvements from EG to LG. This suggests cows were able to cope well with increasing levels of grazing intensity, and that regardless of treatment, a greater number of days on pasture led to improvements in welfare indicators.

Scientific characterization methods for better utilization of cattle dung and urine: a concise review

Cattle are usually raised for food, manure, leather, therapeutic, and draught purposes. Biowastes from cattle, such as dung and urine, harbor a diverse group of crucial compounds, metabolites/chemicals, and microorganisms that may benefit humans for agriculture, nutrition, therapeutics, industrial, and other utility products. Several bioactive compounds have been identified in cattle dung and urine, which possess unique properties and may vary based on agro-climatic zones and feeding practices. Therefore, cattle dung and urine have great significance, and a balanced nutritional diet may be a key to improved quality of these products/by-products. This review primarily focuses on the scientific aspects of biochemical and microbial characterization of cattle biowastes. Various methods including genomics for analyzing cattle dung and gas chromatography-mass spectroscopy for cattle urine have been reviewed. The presented information might open doors for the further characterization of cattle resources for heterogeneous applications in the production of utility items and addressing research gaps. Methods for cattle's dung and urine characterization.

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.

Modeling the economic impacts of mobility scores in dairy cows under Irish spring pasture-based management

Moderate to severe forms of suboptimal mobility on dairy cows are associated with yield losses, whereas mild forms of suboptimal mobility are associated with elevated somatic cell count and an increased risk to be culled. Although the economic consequences of severe forms of suboptimal mobility (also referred as clinical lameness) have been studied extensively, the mild forms are generally ignored. Therefore, the aim of the current study was to determine the economic consequences associated with varying prevalence and forms of suboptimal mobility within spring calving, pasture-based dairy herds. A new submodel predicting mobility scores was developed and integrated within an existing pastured-based herd dynamic model. Using a daily timestep, this model simulates claw disorders, and the consequent mobility score of individual cows. The impact of a cow having varying forms of suboptimal mobility on production and reproduction was simulated. The economic impact was simulated including treatment costs, as well as the production and reproductive impacts of varying levels of suboptimal mobility. Furthermore, different genetic predispositions for mobility issues and their interaction with herd-level management associated with each level of suboptimal mobility were simulated. Overall, 13 scenarios were simulated, representing a typical spring calving, pasture-based dairy herd with 100 cows. The first scenario represents a perfect herd wherein 100% of the cows had mobility score 0 (optimal mobility) throughout the lactation. The remaining 12 scenarios represent a combination of (1) 3 different herd-management levels, and (2) 4 different levels of a genetic predisposition for suboptimal mobility. The analysis showed that a 17% decrease in farm net profit was achieved in the worst outcome (wherein just 5% of the herd had optimal mobility) compared with the perfect herd. This was due to reduced milk yield, increased culling, and increased treatment costs for mobility issues compared the ideal scenario.

Identifying cow - level factors and farm characteristics associated with locomotion scores in dairy cows using cumulative link mixed models

Lameness is a tremendous problem in intensively managed dairy herds all over the world. It has been associated with considerable adverse effects on animal welfare and economic viability. The majority of studies have evaluated factors associated with gait disturbance by categorising cows into lame and non-lame. This procedure yet entails a loss of information and precision. In the present study, we extend the binomial response to five categories acknowledging the ordered categorical nature of locomotion assessments, which conserves a higher level of information. A cumulative link mixed modelling approach was used to identify factors associated with increasing locomotion scores. The analysis revealed that a low body condition, elevated somatic cell count, more severe hock lesions, increasing parity, absence of pasture access, and poor udder cleanliness were relevant variables associated with higher locomotion scores. Furthermore, distinct differences in the locomotion scores assigned were identified in regard to breed, observer, and season. Using locomotion scores rather than a dichotomised response variable uncovers more refined relationships between gait disturbances and associated factors. This will help to understand the intricate nature of gait disturbances in dairy cows more deeply.

Simulating the mechanics behind sub-optimal mobility and the associated economic losses in dairy production

Hoof disorders and sub-optimal mobility (SOM) are economically important health issues in dairy farming. Although the dynamics of hoof disorders have an important effect on cow mobility, they have not been considered in previous simulation models that estimate the economic loss of SOM. Furthermore, these models do not consider the varying severities of SOM. The objective of this study was to develop a novel bio-economic simulation model to simulate the dynamics of 8 hoof disorders: digital dermatitis (DD), interdigital hyperplasia (HYP), interdigital dermatitis/heel-horn erosion (IDHE), interdigital phlegmon (IP), overgrown hoof (OH), sole haemorrhage (SH), sole ulcer (SU) and white-line disease (WLD), their role in SOM, and estimate the economic loss of SOM in a herd of 125 dairy cows. A Reed-Frost model was used for DD and a Greenwood model for the other 7 hoof disorders. Economic analysis was conducted per mobility score according to a 5-point mobility scoring method (1 = perfect mobility; 5 = severely impaired mobility) by comparing a scenario with SOM and one without SOM. Parameters used in the model were based on literature and expert opinion and deemed credible during model validation rounds. Results showed that the mean cumulative incidence for maximum mobility scores 2-5 SOM episodes were respectively 34, 16, 7 and <1 episodes per 100 cows per pasture period and 39, 19, 8, <1 episodes per 100 cows per housing period. The mean total annual economic loss due to SOM resulting from the hoof disorders under study was €15,342: €122 per cow per year. The economic analysis uncovered direct economic losses that could be directly linked to SOM episodes and indirect economic losses that could not be directly linked to SOM episodes but arose due to the presence of SOM. The mean total annual direct economic loss for maximum mobility score 2-5 SOM episodes was €1129, €3098, €4354 and €480, respectively. The mean total annual indirect economic loss varied considerably between the 5th and 95th percentiles: €-6174 and €19,499, and had a mean of €6281. This loss was composed of additional indirect culling due to SOM (∼65%) and changes in the overall herd milk production (∼35%) because of additional younger replacement heifers entering the herd due to increased culling rates. The bio-economic model presented novel results with respect to indirect economic losses arising due to SOM. The results can be used to stimulate farmer awareness and promote better SOM management.

Assessing dairy cow welfare during the grazing and housing periods on spring-calving, pasture-based dairy farms

The different periods characterizing spring-calving, pasture-based dairy systems common in Ireland have seldom been the focus of large-scale dairy cow welfare research. Thus, the aim of this study was to devise and conduct an animal-based welfare assessment during both the grazing and housing periods on spring-calving, pasture-based dairy farms, to identify areas for improvement and establish benchmarks for indicators of good welfare. Assessment of seven animal-based welfare indicators was conducted during two visits (one each at grazing and housing) to 82 commercial dairy farms in southern Ireland. Herd-level descriptive statistics were performed for all welfare indicators at each visit, and differences between visits were analyzed using paired t-tests and Wilcoxon signed-rank tests. A mean of 9% and 10% clinically lame cows (mobility scores 2 and 3) were observed at housing and grazing, respectively. Recommended body condition scores (BCS) were not met for a mean of 13% of cows at grazing and 23% at housing, with more over-conditioned cows present at housing than grazing (P < 0.001). Ocular discharge was uncommon in both periods. Prevalence of moderate and severe nasal discharge combined was lower during housing (5%) than grazing (7%). In both periods, similar mean levels of tail injury were observed: 2% to 3% of cows with tail lacerations, 9% with broken tails, and 8% (measured at housing only) with docked tails. Integument alterations involved primarily hair loss and were most prevalent on the hindquarters (26%) during grazing and on the head–neck–back (66%) and the hindquarter (32%) regions during housing. Cows displayed an avoidance distance of >1 m (indicative of a fearful response) from an approaching human in an average of 82% of grazing cows and 42% to 75% of housed cows, dependent on test location. Opportunities to improve welfare in this system were identified in the areas of tail injury prevention, nasal health, and the management of indoor housing and feeding. The performance of the top 20% of farms for each welfare indicator was used to establish benchmarks of: 0% to 5% clinical lameness, 0% to 12% of cows outside recommended BCS, 0% to 27% ocular discharge, 2% to 16% nasal discharge, 0% tail lacerations and docked tails, 0% to 3% tail breaks, 0% to 14% integument alterations, and 4% to 74% for avoidance distance of >1 m. These represent attainable targets for spring-calving pasture-based farms to promote good dairy cow welfare.

Invited review: A 2020 perspective on pasture-based dairy systems and products

Grazing pasture is the basis for dairy production systems in regions with temperate climates, such as in Ireland, New Zealand, parts of Australia, the United States, and Europe. Milk and dairy products from cows on pasture-based farms predominantly consuming fresh grazed grass (typically classified as "grass-fed" milk) have been previously shown to possess a different nutrient profile, with potential nutritional benefits, compared with conventional milk derived from total mixed ration. Moreover, pasture-based production systems are considered more environmentally and animal welfare friendly by consumers. As such, there is significant potential for market capitalization on grass-fed dairy products. As competition in this space increases, the regulations of what constitutes as grass-fed vary between different regions of the world. With this in mind, there is a need for clear and independently accredited grass-fed standards, defining the grass-fed criteria for labeling of products as such, subsequently increasing the clarity and confidence for the consumer. This review outlines the numerous effects of pasture production systems on dairy product composition, nutritional profile, and sustainability, and highlights potential future methods for authentication.

On-farm detection of claw lesions in dairy cows based on acoustic analyses and machine learning

Claw lesions are a serious problem on dairy farms, affecting both the health and welfare of the cow. Automated detection of lameness with a practical, on-farm application would support the early detection and treatment of lame cows, potentially reducing the number and severity of claw lesions. Therefore, in this study, a method was proposed for the detection of claw lesions based on the acoustic analysis of a cow's gait. A panel was constructed to measure the impact sound of animals walking over it. The recorded impact sound was edited, and 640 sound files from 64 cows were analyzed. The classification of animal-lameness status was performed using a machine-learning process with a random forest algorithm. The gold standard was a 2-point scale of hoof-trimming results (healthy vs. affected), and 38 properties of the recorded sound files were used as influencing factors. A prediction model for classifying the cow lameness was built using a random forest algorithm. This was validated by comparing the reference output from hoof-trimming with the model output concerning the impact sound. Altering the likelihood settings and changing the cutoff value to predict lame animals improved the prediction model. At a cutoff at 0.4, a decreased false-negative rate was generated, and the false-positive rate only increased slightly. This model obtained a sensitivity of 0.81 and a specificity of 0.97. With this procedure, Cohen's Kappa value of 0.80 showed good agreement between model classification and diagnoses from hoof-trimming. In summary, the prediction model enabled the detection of cows with claw lesions. This study shows that lameness can be detected by machine learning from the impact sound of hoofs in dairy cows.

Impact of Nutrients on the Hoof Health in Cattle

Lameness is currently one of the most important and economically demanding diseases in cattle. It is manifested in a change in locomotion that is associated with lesions, especially the pelvic limbs. The disease of the hoof is painful, affecting the welfare of dairy cows. Important factors that influence the health of the limbs include nutrition, animal hygiene, stable technology, and genetic and breeding predispositions. Nutrition is one of the basic preventive factors affecting the quality and growth of the hoof horn, and the associated prevalence of hoof disease. The strength and structure of the hoof horn are affected by the composition of the feed ration (amino acids, minerals, vitamins, and toxic substances contaminating the feed ration, or arising in the feed ration as metabolites of fungi).

Cow and herd-level risk factors associated with mobility scores in pasture-based dairy cows

Lameness in dairy cows is an area of concern from an economic, environmental and animal welfare point of view. While the potential risk factors associated with suboptimal mobility in non-pasture-based systems are evident throughout the literature, the same information is less abundant for pasture-based systems specifically those coupled with seasonal calving, like those in Ireland. Therefore, the objective of this study was to determine the potential risk factors associated with specific mobility scores (0 = good, 1 = imperfect, 2 = impaired, and 3 = severely impaired mobility) for pasture-based dairy cows. Various cow and herd-level potential risk factors from Irish pasture-based systems were collected and analyzed for their association with suboptimal mobility, whereby a mobility score of 0 refers to cows with optimal mobility and a mobility score ≥ 1 refers to a cow with some form of suboptimal mobility. Combined cow and herd-level statistical models were used to determine the increased or decreased risk for mobility score 1, 2, and 3 (any form of suboptimal mobility) compared to the risk for mobility score 0 (optimal mobility), as the outcome variable and the various potential risk factors at both the cow and herd-level were included as predictor type variables. Cow-level variables included body condition score, milk yield, genetic predicted transmitting ability for 'lameness', somatic cell score, calving month and cow breed. Herd-level variables included various environmental and management practices on farm. These analyses have identified several cow-level potential risk factors (including low body condition score, high milk yield, elevated somatic cell count, stage of lactation, calving month, and certain breed types), as well as various herd-level potential risk factors (including the amount of time taken to complete the milking process, claw trimmer training, farm layout factors and foot bathing practices) which are associated with suboptimal mobility. The results of this study should be considered by farm advisors when advising and implementing a cow/herd health program for dairy cows in pasture-based systems.

Grazing Cow Behavior's Association with Mild and Moderate Lameness

Accelerometer-based mobility scoring has focused on cow behaviors such as lying and walking. Accuracy levels as high as 91% have been previously reported. However, there has been limited replication of results. Here, measures previously identified as indicative of mobility, such as lying bouts and walking time, were examined. On a research farm and a commercial farm, 63 grazing cows' behavior was monitored in four trials (16, 16, 16, and 15 cows) using leg-worn accelerometers. Seventeen good mobility (score 0), 23 imperfect mobility (score 1), and 22 mildly impaired mobility (score 2) cows were monitored. Only modest associations with activity, standing, and lying events were found. Thus, behavior monitoring appears to be insufficient to discern mildly and moderately impaired mobility of grazing cows.