Comparison of modeled sampling strategies for estimation of dairy herd lameness prevalence and cow-level variables associated with lameness

Breed differences in oral behaviors in feed-restricted dairy heifers

Holsteins and Jerseys, the 2 most prominent dairy breeds in the United States, differ in many regards. They have not been evaluated for differences in oral behavior performance, despite anecdotal evidence that Jerseys perform more abnormal behaviors than Holsteins. As abnormal behaviors can indicate compromised welfare, we evaluated whether breed differences existed in year-old heifers. Because many oral behaviors could be expressed in abnormal ways, we also sought to describe performance of a wide range of behaviors and whether these varied among individuals. We studied 42 pair-housed heifers (33 Holstein, 9 Jersey) at 12.8 ± 1.1 mo of age (mean ± SD) that were restricted to 50% of their ad libitum total mixed ration (TMR) intake for 2 d as part of a short-term feed challenge. Using continuous video recording from 0800 to 2000 h on the second day of feed restriction, we scored time spent performing tongue rolling, tongue flicking, self-grooming, allogrooming, intersucking, drinking urine, drinking water, and nonnutritive oral manipulation (NNOM) of rice hull bedding, the feed bin, or other pen fixtures. Eating TMR was recorded at 5-min intervals. We found that Jerseys spent more time tongue rolling (3.3% vs. 0.2% proportion of 12-h observations) and performing all types of NNOM than Holsteins (feed bin: 3.8% vs. 2.4%; bedding: 7.7% vs. 5.4%; other: 7.5% vs. 4.2%; total: 19.0% vs. 12.0%), and tended to spend more time tongue flicking (1.4% vs. 1.1%). Jerseys spent less time allogrooming than Holsteins (1.3% vs. 3.4%). There was no evidence of an effect of breed on self-grooming (2.0%), water drinking (1.0%), eating TMR (16.0%), or intersucking (0.06%). Urine drinking was performed by 9 total heifers and was not compared between breeds. All behaviors were highly variable across individuals, particularly tongue rolling and intersucking. Allogrooming was more variable than self-grooming, and each subcategory of NNOM was more variable than total NNOM. Outliers, or extreme performance of oral behaviors relative to the rest of our population, were present in most behaviors. Heifers who were outliers in one behavior were not consistently outliers in all. Overall, there are breed differences in many oral behaviors in a feed-restricted environment. Despite no difference in proportion of time spent eating, Jerseys often performed higher levels of potentially abnormal behaviors than Holsteins, though both breeds performed many oral behaviors, sometimes at extreme levels, that may indicate a concern.

The "Real Welfare" Scheme: Changes in UK Finishing Pig Welfare since the Introduction of Formal Welfare Outcome Assessment

Farm animal welfare is an increasingly important issue, leading to the need for an efficient methodology to deliver accurate benchmarking. The "Real Welfare" project developed a methodology based on regular recording of a limited number of animal-based measures, so-called welfare outcomes, which allows faster and easier on-farm assessment of finishing pig welfare. The objective of this paper is to estimate, with sufficient robustness and confidence, the prevalence of different mandatory and optional welfare outcomes in the mainstream herd of the finishing farms in the UK based on the "Real Welfare" scheme data and to assess the changes in prevalence over time, inspection visits and seasons. The mean overall prevalence of the four mandatory welfare outcomes (pigs requiring hospitalization, lame pigs, pigs with severe body marks, and pigs with severe tail lesions) was very low (≤0.2%) and a significant decreasing trend was observed for the first three of these mandatory welfare outcomes since the inception of the scheme. This result might reflect either a reduction in factors giving rise to welfare problems in the mainstream herd or increasing awareness about management of compromised pigs. Additional data are required to clarify these possibilities, but both represent improved pig welfare.

Pairwise comparison locomotion scoring for dairy cattle

Conventional locomotion scoring is a subjective, absolute, and discrete assessment of locomotion. Here we assess pairwise comparison scoring to improve upon the limited intra- and interobserver consistency typical of conventional locomotion scoring. Five observers performed conventional 4-level locomotion scoring using 50 video recordings of dairy cattle, and also assessed 90 pairs of videos (composed from the same 50 recordings) using relative pairwise scoring. Intra- and interobserver consistency of pairwise scores [intraobserver: percentage agreement (PA) = 82%, κ = 0.63; interobserver: PA = 79%, κ = 0.57] were greater than of 4-level absolute scores (intraobserver: PA = 72%, κw = 0.74; interobserver: PA = 56%, κw = 0.59). Pairwise scores were scaled with an optimization method to obtain the position of the 50 recordings on a continuous locomotion scale. These continuous locomotion scores (CLS) were compared with the conventional mean absolute visual locomotion scores (VLS). Correlation between CLS and VLS was strong (τ = 0.69), and consistency between binarized CLS and binarized VLS was high (PA = 84%, κ = 0.66 for threshold VLS ≥1). Just noticeable difference (JND) for locomotion scoring was 0.3 on a 4-level scale ranging from 0 to 3. Pairwise scoring and scaling had the scoring consistency of binary absolute scoring with finer continuous granularity than 4-level absolute scoring. The pairwise scoring method, and associated scaling, offer a more consistent and informative alternative to conventional absolute multilevel locomotion scoring.

Modeling cost-effective monitoring schemes for food safety contaminants: Case study for dioxins in the dairy supply chain

Food safety monitoring is essential for hazard identification in food chain, but its application may be limited due to costly analytical methods and (inefficient) sampling procedures. The objective of this study was to design cost-effective monitoring schemes for food safety contaminants along the food production chain, given restricted monitoring budgets. As a case study, we focused on dioxins in the dairy supply chain with feed mills, dairy farms, dairy trucks and storage silos in dairy plants as possible control points. The cost-effectiveness of monitoring schemes was assessed using a model consisting of a simulation module and an optimization module. In the simulation module, the probability to collect at least one contaminated sample was computed for different sampling strategies (simple random sampling, stratified random sampling and systematic sampling) at each control point. The optimization module maximized the effectiveness of a monitoring scheme to identify the contaminated sample by determining the optimal sampling strategies, the optimal number of incremental samples collected, and the pooling rate (number of collected samples mixed into one aggregated sample) at each control point. The modelling approach was applied to two cases with different types of contamination. Results of these cases showed that, to identify the same contaminated sample, monitoring schemes with systematic sampling were more cost-effective at feed mills and dairy farms. The combination of simulation and optimization methods showed to be useful for developing cost-effective food safety monitoring schemes along the food supply chain.

Univariate associations between housing, management, and facility design factors and the prevalence of lameness lesions in fourteen small-scale dairy farms in Northeastern Algeria

Background and Aim:

This cross-sectional study aimed to analyze the associations between different types of housing, management, and facilities on the prevalence of lame, causing lesions in smallholder dairy farms in Algeria.

Materials and Methods:

The on-site investigation took place between December 2012 and May 2015. All cows were locomotion scored on a four-point scale, and foot lesions causing lame were diagnosed and recorded. Factors related to the farm and the cows’ conditions were also assessed. The association between the possible risk factors and lame lesions was assessed using univariate analysis.

Results:

Of the 349 cows evaluated, 13% were lame (lameness score ≥2), with higher lameness values recorded for the hind feet than for the forefeet. Cows without lameness were classified as healthy. The two most frequent lesion diagnoses observed in lame cows were interdigital dermatitis/heel horn erosion (ID/HE; 39%) and interdigital phlegmon (IP; 35%), followed by traumatic lesions (T; 11%), digital dermatitis (DD; 8.7%), and laminitis-related diseases (L; 6.5%). The risk of being lame was increased in large herds with cows of the Holstein breed, and those in the third parity and above. Tie housing, concrete floor, concentrate feeding, zero-grazing, and the use of foot trimming occasionally were associated with increased risk for the presence of lame lesions. The region and footbathing frequency had no association with the prevalence of lame lesions (p≥0.05).

Conclusion:

These results have important implications; they indicate that several aspects of housing, management, and facility design are common protective factors for the prevalence of lame lesions. These factors should be maintained correctly to not only reduce the number of lame cows in these herds but also decrease the direct and indirect costs associated with cases of lameness.

Sampling strategies for assessing lameness, injuries, and body condition score on dairy farms

Our objective was to evaluate how sampling strategies (i.e., how many cows to sample and which animals to include) used in 4 dairy cattle welfare assessment programs affect the classification of dairy farms relative to thresholds of acceptability for animal-based measures. We predicted that classification performance would improve when more cows were sampled and when selecting from all lactating cows versus when some pens were excluded. On 38 freestall farms, we assessed all 12,375 cows for lameness, injuries on the tarsal (hock) and carpal joints, and body condition score and calculated the farm-level prevalence for each measure. Based on approaches used in the industry, we evaluated 6 sampling strategies generated using formulas with precision (d) of 15, 10, or 5% applied to either a single high-producing pen or all lactating cows; an additional sample was included with d = 10% applied to the entire herd, selecting lactating cows in proportion to their representation in the herd. For each sampling strategy, cow records were selected randomly (in 10,000 replicates) to calculate prevalence. The strategy of assessing all cows in the high-producing pen was also compared. Farms were classified as meeting (below) or failing to meet (above) thresholds of ≤15% moderate lameness; ≤20% moderate carpal or hock injuries; <10, <5, and ≤1% severe lameness; or injuries on the carpus or hock; and <5, <3, <1, or 0% thin cows. For each measure and threshold, we calculated pooled percent agreement, kappa, sensitivity, specificity, and positive and negative predictive value for each sampling strategy using true prevalence as the gold standard for herd classification. Across measures and thresholds, classification performance increased with the number of cows sampled [i.e., when narrower precision values (d = 5 vs. 10 vs. 15%) were used in the sample size calculation]. Because narrower precision values can dramatically increase sample size, assessment programs may need to consider both feasibility and the degree of misclassification they will accept. Applying the formula directly to lactating cows performed better than applying it to the entire herd and then selecting lactating cows in proportion to their representation in the herd. Farm classifications were similar whether cows in the hospital pen were included or excluded from the sample. Selecting all cows from the high-producing pen resulted in classifications similar to when including all lactating cows, suggesting that assessing cows from the high-producing pen may serve as an acceptable proxy for all lactating cows on the farm.

Reliability of sampling strategies for measuring dairy cattle welfare on commercial farms

Our objective was to evaluate how the proportion of high-producing lactating cows sampled on each farm and the selection method affect prevalence estimates for animal-based measures. We assessed the entire high-producing pen (days in milk <100; range = 81-241 cows) on 10 California farms using measures from the Welfare Quality Protocol for Cattle. Cows were restrained in head locks and visually evaluated for body condition, dirtiness, skin alterations (hair loss, lesions, or swelling), discharge (ocular, nasal, vulvar), diarrhea, and impaired respiration. Lameness was scored upon release. Prevalence was calculated as a percentage of assessed cows. The most common conditions were dirty hindquarters (33.5 ± 10.7%, mean ± standard deviation) and lesions or swelling on the carpal joint (34.4 ± 7.0%) and hock (26.4 ± 16.7%). Diarrhea (8.0 ± 5.8%), lameness (moderate = 7.3 ± 4.7%, severe = 2.2 ± 2.2%), and neck (5.8 ± 12.6%), flank (4.5 ± 5.0%), or hindquarter alterations (5.5 ± 3.9%) were less common. Very fat cows, vulvar discharge, and impaired respiration were rare (≤1%) and were excluded from further analysis. Four sampling strategies were used to generate 20 estimates for each animal-based measure. The strategies were (1) selecting every 10th, 5th, 4th, 3rd, 2nd, 2 of 3, or 3 of 4 cows at the feed bunk (7 estimates/measure); (2) randomly selecting 7 matching proportions of the pen; (3) randomly selecting cows using 3 sample size calculations from the Welfare Quality Protocol; and (4) selecting the first, middle, or final third of cows exiting the milking parlor. Estimates were compared with true values using regression analysis and were considered accurate if they met 3 criteria: the coefficient of determination was ≥0.9 and the slope and intercept did not differ significantly from 1 and 0, respectively. All estimates met the slope and intercept criteria, whereas the coefficient of determination increased when more cows were sampled. All estimates were accurate for neck alterations, ocular discharge (22.2 ± 27.4%), and carpal joint hair loss (14.1 ± 17.4%). Selecting a third of the milking order or using the Welfare Quality sample size calculations failed to accurately estimate all measures simultaneously. However, all estimates were accurate when selecting at least 2 of every 3 cows locked at the feed bunk. Using restraint position at the feed bunk did not differ systematically from computer-selecting the same proportion of cows randomly, and the former may be a simpler approach for welfare assessments.

ANIMAL BEHAVIOR AND WELL-BEING SYMPOSIUM: Optimizing outcome measures of welfare in dairy cattle assessment

In most countries producing milk, industry- or other stakeholder-driven initiatives are in place to improve welfare and overall dairy farming sustainability. Those initiatives typically include a system of verification of reaching targets and progress over time. Reliable indicators are a fundamental requirement to provide public assurance and allow improvement on farms. Assessing dairy cattle welfare through outcome measures of welfare is done today through visual evaluations, including those of lameness, injuries, hygiene, and body condition. Numerical scoring charts for visual evaluation have been validated, and training programs have been developed to achieve high repeatability of assessors. Sampling strategies have been validated to determine how many animals and how many days are required to obtain reliable estimates of prevalence. However, visual evaluations require long periods of data collection, and multiple visits on farm, along with repeated checks of assessors to ensure repeatability over time, are, in turn, very costly to implement. An attractive alternative is relying on automated measures as activity monitors are becoming common on commercial farms; among those, lying time retains the most attention. The use of herd lying time in both free-stall and tie-stall situations has been validated. Current research is looking at relationships between lying time and other outcome measures of welfare, as well as lying time and risk factors for welfare in the environment (e.g., poor stall configuration or hoof trimming routine). We are not quite yet ready to rely solely on lying time to assess welfare; however, activity monitoring could certainly contribute to early detection of health and welfare issues (e.g., frequency of visits to the robotic milking system). Another interesting avenue is the development of early outcome measures of welfare and, possibly, remote indicators, for example, performance data collected routinely in Dairy Herd Improvement agencies' databases. The rationale is that a herd with good health and high longevity should be at lower risk of poor welfare. Research is needed to identify predictors and their conditions of use, allowing us to discriminate good vs. poor welfare status, at both the individual and herd levels. Finally, milk samples are already collected routinely to check quality and safety. It would be convenient to be able to predict cow welfare status directly with the milk using biomarkers, but again, we are not there yet.

Sequential sampling: a novel method in farm animal welfare assessment

Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first 'basic' scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second 'cautious' scheme, an adaptation is made to ensure that correctly classifying a farm as 'bad' is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall association between lameness prevalence and the proportion of lame cows that were severely lame on a farm was found. However, as this association was found to not be consistent across all farms, the sampling scheme did not prove to be as useful as expected. The preferred scheme was therefore the 'cautious' scheme for which a sampling protocol has also been developed.

Association of abnormal hind-limb postures and back arch with gait abnormality in dairy cattle

Detection of lameness in individual cows is important for the prompt treatment of this painful and production-limiting disease. Current methods for lameness detection involve watching cows walk for several strides. If clinical signs predictive of lameness could be observed more conveniently, as cows are undergoing regularly scheduled examinations while standing, detection levels could increase. The objective of this study was to assess the association between postures observed while cows are standing in stanchions and clinical lameness evaluated by locomotion scoring, and to evaluate the observation of these postures as a test for lameness. The study included 1,243 cows from 4 farms. Cows were observed while standing in stanchions for regularly scheduled management procedures and the presence of arched back and cow-hocked, wide-stance, and favored-limb postures were recorded. The same cows were locomotion-scored as they exited the milking parlor. The proportion of cows observed with arched back and cow-hocked and favored-limb postures increased with increasing severity of lameness (higher locomotion score) but did not increase for the wide-stance posture. For the presence of these postures as a test for lameness (locomotion score ≥3), sensitivity and specificity were 0.63 and 0.64 for back arch, 0.54 and 0.57 for cow hocks, and 0.05 and 0.98 for favored limb. Back-arched, cow-hocked, and favored limb postures were associated with lameness but were not highly sensitive or specific as diagnostic tests. However, observation of back arch may be useful to identify cows needing further examination.