Comparison of Cattle Housing Systems Based on the Criterion of Damage to Barn Equipment and Construction Errors

Simple Summary

As a result of many years of use, dairy cattle barns are subject to gradual wear and degradation. Damage to technical equipment can be identified in many areas in the barn. These areas are used by dairy cattle, so it is important to recognize the problem of damage and the associated health risks for animals. The problem of damage to internal equipment (e.g., damage to the floor, partitions between lying stalls, feed ladders, drinking bowls) applies to both tie-stall and freestall barns, which are the most common in dairy farms. Such premises became an inspiration to compare barns with a tie-stall system, a freestall system and their individual areas (lying, feeding, milking and social) in terms of the amount of damage but also construction errors. Most damage per one barn was found in the feeding area of objects with a tie-stall housing system. More cow health problems (e.g., laminitis, hoof problems) were identified in the barns with the freestall housing system. Equipment failures and construction errors may disrupt efficient and animal-safe dairy production in the barn. The results of the research study may be an incentive for farmers to check the barns in terms of their technical wear.

Abstract

Dairy cattle housing systems are the subject of numerous studies, in which a strong emphasis is placed on the comparison of animal welfare, animal behavior, production indicators and labor inputs. Dairy cattle housing systems are linked to specific livestock buildings, which is a prerequisite for undertaking studies comparing barns and their technical equipment. The aim of the study was to compare barns with two types of housing systems, i.e., tie-stall and freestall, including the identification of technical wear in various areas used by animals. This objective was linked to the assessment of animal health problems in livestock facilities. The research covered 38 dairy farms, 19 of which kept cows in the tie-stall system and 19 in the freestall system. The barns in these farms were examined for technical damage and construction errors, assessed in four areas: lying, feeding, milking and social. The research results confirmed significant differences in the degree of damage to technical equipment in individual areas of barns and between barns with tie-stall and freestall housing systems. The conclusions indicate the need to link the degradation of barns and their technical equipment, as well as design errors with the evaluation of dairy cattle welfare in future studies.

Time-Consuming, but Necessary: A Wide Range of Measures Should Be Included in Welfare Assessments for Dairy Herds

Animal welfare assessments that measure welfare outcomes, including behavior and health, can be highly valid. However, the time and skill required are major barriers to their use. We explored whether feasibility of welfare outcome assessment for dairy herds may be improved by rationalizing the number of measures included. We compared two approaches: analyzing whether strong pairwise associations between measures existed, enabling the subsequent exclusion of associated measures; and identifying possible summary measures—“iceberg indicators”—of dairy herd welfare that could predict herd welfare status. A cross-sectional study of dairy herd welfare was undertaken by a single assessor on 51 English farms, in which 96 welfare outcome measures were assessed. All measures showed at least one pairwise association; percentage of lame cows showed the most (33 correlations). However, most correlations were weak–moderate, suggesting limited scope for excluding measures from protocols based on pairwise relationships. A composite measure of the largest portion of herd welfare status was then identified via Principal Component Analysis (Principal Component 1, accounting for 16.9% of variance), and linear regression revealed that 22 measures correlated with this. Of these 22, agreement statistics indicated that percentage of lame cows and qualitative descriptors of “calmness” and “happiness” best predicted Principal Component 1. However, even these correctly classified only ~50% of farms according to which quartile of the Principal Component 1 they occupied. Further research is recommended, but results suggest that welfare assessments incorporating many diverse measures remain necessary to provide sufficient detail about dairy herd welfare.

Farm-level factors associated with lameness prevalence, productivity, and milk quality in farms with automated milking systems

Impaired locomotion (lameness) may negatively affect the ability and desire of cows to milk voluntarily, which is a key factor in success of automated milking systems (AMS). The objective of this study was to identify factors associated with herd-level lameness prevalence and associations of lameness and other farm-level factors with milking activity, milk yield, and milk quality in herds with AMS. From April to September 2019, 75 herds with AMS in Ontario, Canada, were visited, and data on barn design and farm management practices were collected. Data from AMS were collected, along with milk recording data, for the 6-mo period before farm visits. Farms averaged 98 ± 71 lactating cows, 2.3 ± 1.5 robot units/farm, 43.6 ± 9.4 cows/robot, 36.4 ± 4.9 kg/d of milk, a milking frequency of 3.01 ± 0.33 milkings/d, and a herd average geometric mean SCC of 179.3 ± 74.6 (× 1,000) cells/mL. Thirty percent of cows/farm (minimum of 30 cows/farm) were scored for body condition (1 = underconditioned to 5 = over conditioned) and locomotion (1 = sound to 5 = lame; clinically lame ≥3 out of 5 = 28.3 ± 11.7%, and severely lame ≥4 out of 5 = 3.0 ± 3.2%). Clinical lameness (locomotion score ≥3) was less prevalent on farms with sand bedding, with increased feed bunk space per cow, and on farms with non-Holstein breeds versus Holsteins, and tended to be less prevalent with lesser proportion of underconditioned cows (with body condition score ≤2.5). Severe lameness occurrence (farms with any cows with locomotion score ≥4) was associated with a greater proportion of underconditioned cows and in farms with stalls with greater curb heights. Herd average milk yield/cow per day increased with lesser prevalence of clinical lameness (each 10-percentage-point decrease in clinical lameness prevalence was associated with 2.0 kg/cow per day greater milk yield) and greater milking visit frequency per day, and tended to be greater with increased feed push-up frequency. Lesser herd average somatic cell count was associated with lesser clinical lameness prevalence, herd average days in milk, and proportion of overconditioned cows, and somatic cell count tended to be lesser for farms with sand bedding versus those with organic bedding substrates. The results highlight the importance of minimizing lameness prevalence, using of sand bedding, ensuring adequate feed access and feed bunk space, and maintaining proper cow body condition to optimize herd-level productivity and milk quality in AMS herds.

Animal welfare outcomes and associated risk indicators on Austrian dairy farms: A cross-sectional study

In 2017, an Austrian dairy company implemented a third-party animal-based assessment of health and welfare to stimulate welfare improvements on farms. Using this cross-sectional data set, we aimed at identifying prevailing welfare problems and associations thereof with main farm and management characteristics. Welfare outcome measures regarding body condition, cleanliness, diarrhea, integument alterations, claw condition, lameness, rising behavior, and avoidance distance toward humans were assessed by 13 trained observers. Data from health recordings and farm characteristics, such as housing system, feeding regimen, and pasture access, were collected via a questionnaire. Analyses included outcome measures from 23,749 individual cows on 1,221 farms [median (M) herd size = 19, interquartile range (IQR) = 16]. Herd-level prevalence of the outcome measures showed a high between-farm variability with highest median values for dirty lower hind leg (M = 46%, IQR = 47), signs of diarrhea (M = 28%, IQR = 39), and hairless patches on the tarsal joint (M = 21%, IQR = 36). Median prevalence of severe welfare problems, such as very lean cows, lesions, lameness, or mastitis treatments, were low compared with previously reported findings (very lean: 0%, IQR = 0; lesion tarsus: 0%, IQR = 4; moderately lame loose-housed: 7%, IQR = 16; mastitis treatments: 10%, IQR = 16). On half of the farms, at least 83% (IQR = 25) of the assessed cows could be touched in a standardized approach test, indicating a good human-animal relationship. Using generalized linear models, we found frequent associations with welfare outcome measures for the amount of milk delivered per cow (e.g., lower risk of very lean cows or dirty hind legs but higher risk of mastitis treatments or antibiotic dry-off with increasing milk delivery), housing system (e.g., loose-housed animals were at lower risk of lesions on the tarsal joint than animals kept in tiestalls, but at higher risk of being classified as very fat), and assessment period (winter vs. summer period). Beneficial associations were consistently found for an increasing number of days with access to pasture (e.g., body condition, integument alterations, lameness) as well as organic compared with conventional farming (e.g., integument alterations, claw health, lameness). Although the latter associations may be especially important for advisory services, in policy making, or when engaging with the public, other farm or management characteristics require careful attention, as they may have both beneficial as well as adverse impacts on welfare, calling for good management skills to avoid undesired effects.

Short communication: Evaluation of the sample size of individual indicators in gestating sows concerning the Welfare Quality® protocol applied to sows and piglets

Sample sizes of welfare assessment protocols must warrant to reflect prevalences on-farm properly - regardless of farm size. Still, solely a fixed sample size was specified for the Welfare Quality® protocol for sows and piglets. The present study investigated whether animals may be assessed from only one body side as applied in the protocol and whether the pre-set sample size of 30 animals mirrors the prevalences of the animal-based indicators on-farm in the gestation unit considering different farm sizes. All indicators were assessed for both sides of an animal's body by one observer on 13 farms in Germany, which were visited five times within 10 months. The farm visits were treated as independent since different animals were housed in the gestation units. The number of sows in the gestation units varied between 18 and 549 animals. The comparison of sides was carried out calculating exact agreement between animals' sides and a Wilcoxon signed-rank test (W). The results signified that it is sufficient to assess the animal from one side (exact agreement: 88.3% to 99.5%, except for bursitis (70.0%); W: P-values 0.14 to 0.92). However, if side preferences existed in the indicator bursitis a potential bias must be considered. In the following, the sample size was evaluated by comparing samples' prevalences against true prevalence, that is, the prevalence of all observed animals in the gestation unit in each farm visit. Therefore, subsets of data were generated by applying simple random sampling without replacement. The samples randomly included the animals' right or left sides. Linear regression was rated as appropriate provided: coefficient of determination R2 ≥ 0.90, slope = 1 and intercept = 0 signifying exact agreement. The results revealed that the sample size required by the protocol and the application of calculation formulas are solely appropriate to mirror the prevalences of frequent indicators in the gestation unit, for example, bursitis (mean prevalence 34.4%). Using a proportion of animals, for example, a sample of 30% of all observed animals in a farm visit, pointed out that proportions must increase with indicators' underlying prevalence narrowing 0.00%. Local infections (mean prevalence 13.3%) needed samples including 60% of all observed animals in each farm visit, whereas vulva lesions (mean prevalence 7.28%) only reached accuracy with the inclusion of 70% of the animals. Indicators with a mean prevalence of <1% were not analysed but can most likely only be ascertained by the assessment of all animals.

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.

Housing, management characteristics, and factors associated with lameness, hock lesion, and hygiene of lactating dairy cattle on Upper Midwest United States dairy farms using automatic milking systems

The objectives of this cross-sectional study were to describe housing and management practices on farms using automatic milking systems (AMS) in 2 states of the upper Midwest and to evaluate the association of various housing and management factors with 3 measures of animal welfare: prevalence of lameness, severe hock lesions, and dirty cows. Fifty-four farms were visited once to collect facility measurements and observations, interview the dairy producer, and score cows for locomotion, hock lesions, and hygiene. Median number of AMS units/farm was 2 (interquartile range = 1; range = 1 to 8). Factors concerning labor were the most commonly cited reason by dairy producers for making the transition to the AMS; additional commonly cited factors were an improvement in lifestyle and human health. Number of cows fetched per AMS, or manually brought to the AMS if not milked voluntarily, was 4.7 ± 2.3 cows/AMS per day (8% of cows) for free traffic flow farms and 3.3 ± 1.8 cows/AMS per day (5% of cows) for guided traffic flow farms. Cow resting surface was significantly associated with prevalence of lameness and severe lameness. Farms with sand-bedded freestalls (17.2%) and bedded packs (17.4%) had significantly lower lameness prevalence (score ≥3 on a 1 to 5 scale, with 1 = normal locomotion) than farms with mattress freestalls (30.5%), waterbeds (25.0%), and mattresses with access to pasture (22.6%). Farms with mattresses and access to pasture had similar lameness prevalence to farms with waterbeds, but were lower than farms with mattresses only. A somewhat similar result was found for severe lameness prevalence (score ≥4 on a 1 to 5 scale, with 1 = normal locomotion); farms with sand-bedded freestalls (2.8%), bedded packs (0.0%), and mattress freestalls with access to pasture (1.5%) had significantly lower prevalence than farms with mattresses (7.1%) or waterbeds (10.8%). Severe hock lesion prevalence (score = 3 on a 1 to 3 scale, with 1 = normal, 3 = swelling) in herds with sand-bedded freestalls, waterbeds, and bedded packs were similar and significantly lower than the prevalence in mattress-based freestalls. Cows housed in sand-bedded freestalls had significantly lower prevalence of dirty cows (score = 3 or 3.5 on a 1 to 5 scale, with 1 = clean) than those housed on mattresses and waterbeds, and had significantly lower prevalence of severely dirty cows (score = 4, 4.5 or 5 on a 1 to 5 scale, with 1 = clean) than all other housing systems except waterbeds, which was similar. Manure removal system (manual, automatic, or slatted floor) was significantly associated with prevalence of severely dirty cows; farms with manual scraping had lower prevalence of severely dirty cows than farms where alley scraping was practiced automatically or slatted floors were used. Dairy producers using AMS appeared to be successful with a variety of facility designs and management practices. Cow resting surface in AMS herds was associated with some animal health and welfare measurements.

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.

Applying animal-based welfare assessments on New Zealand dairy farms: feasibility and a comparison with United Kingdom data

AIMS

To assess the feasibility of applying animal-based welfare assessments developed for use in Europe on New Zealand dairy farms; in particular, to identify measures which could be evaluated during a single visit at milking time alongside whole herd locomotion scoring.

METHODS

A protocol for animal welfare assessment, developed in the United Kingdom (UK), was evaluated. Measures that were suitable for use on pasture-based dairy farms in New Zealand were then assessed for practicability on 59 farms across New Zealand, during and immediately after milking, alongside whole herd locomotion scoring. Where data were collected the results were compared to those from a UK study of 53 dairy farms.

RESULTS

Thirteen observations of the physical condition of cows were considered suitable for measurement, excluding observations related to hock lesions as they are rarely observed on pasture-based farms. Five of these measures were not assessed as there was not time to do so during milking alongside whole herd locomotion scoring. Thus, the prevalence of dirty flanks, hind limbs and udders, dull coat, thick hairy coat, significant hair loss, very fat cows (body condition score (BCS) ≥7 on 1-10 scale) and very thin cows (BCS≤3), were recorded. Three measures of behaviour were considered suitable for measurement on-farm, but only locomotion score was practicable and was measured. Farmer-estimates for the incidence of mastitis, lameness, sudden death, milk fever and other diseases were also obtained.Overall, dirty flanks, dirty udders and estimated milk fever incidence were more prevalent in this study than in the UK. The prevalence of thin and fat cows, lame cows and estimated mastitis incidence were much lower in the present study than on UK farms.

CONCLUSIONS AND CLINICAL RELEVANCE

Animal-based assessments can be used on dairy farms in New Zealand, but need to be modified from those developed for housed cows.Welfare on these farms was generally good compared to those in the UK, but these results need to be confirmed on more farms using a wider range of assessments than proved practicable in this study.