Dairy cattle welfare - the relative effect of legislation, industry standards and labelled niche production in five European countries.

The only common European Union (EU) legislation set up specifically to ensure the welfare of dairy cattle is for calves. As a consequence, there is wide diversity in how dairy cattle welfare is ensured in EU countries. A few countries have legal requirements for dairy cattle welfare, while in others, it is left to industry standards or niche production requirements, typically linked to various premium labels. In this paper, we compared animal welfare provisions in dairy cattle production across five countries with different combinations of legislative and other approaches: Denmark, Germany, the Netherlands, Sweden, and the United Kingdom. Firstly, we aimed to map the diversity of animal welfare initiatives. Secondly, we used the Benchmark method of expert valuations and weightings of the relative importance of individual welfare provisions. We found that Denmark and Sweden have the highest level of dairy cattle welfare provisions as measured by the Benchmark method, partly due to high legislative welfare requirements, followed by the United Kingdom, which has an extensive industry standard with very high uptake. Germany and the Netherlands, on the other hand, have lower levels of documented welfare provisions, and correspondingly a Benchmark score closer to a baseline defined by legal requirements at EU level. We also found differences in what elements of animal welfare were focussed on. Some initiatives emphasised fulfilling the social needs of cattle, while others focused more on space and freedom to move. Also, the countries with the highest Benchmark score had a relatively high level of production of organic and other specialty dairy products. We found the effect of national legislation or ambitious industry standards on dairy cattle welfare to be much larger than previous studies have found in either pigs or poultry. At a time when the EU is considering stepping up its efforts to improve animal welfare in terms of common minimum standards, the results of this study could have important policy implications. The diversity in the level of dairy cattle welfare standards found across countries may speak in favour of having shared minimum standards, both at EU level and globally. However, even among countries with a similar Benchmark score, we found a difference in the kinds of welfare provisions at work, which may make full harmonisation of standards more challenging.

Improvement of the Welfare Quality scoring model for dairy cows to fit experts' opinion.

After several years of implementation, the original Welfare Quality scoring model for dairy cows appears to be highly sensitive to the number and cleanliness of drinkers and not enough to the prevalence of diseases, and as a consequence may not fit the opinion of some animal welfare experts. The present paper aims to improve the Welfare Quality calculations for the criteria 'Absence of prolonged thirst' and 'Absence of disease' in dairy cows, so that the results are more sensitive to input data and better fit experts' opinion. First, we modified the calculation of 'Absence of prolonged thirst' by linearising the calculation for drinkers' availability to avoid threshold effects. Second, we modified the calculation of 'Absence of disease' by applying a Choquet integral on the three lowest spline-based scores for each health disorder to limit compensation between health disorders. Third, we performed a global sensitivity analysis of the original and the alternative scoring models. Fourth, we compared the results obtained with the original and the alternative models with eight experts' opinions on two subsets composed of 44 and 60 farms, respectively, inspected using the Welfare Quality protocol and on which experts gave their opinion on the overall level of animal welfare. Results show that the alternative model significantly reduced the 'threshold effects' related to the number of drinkers and the compensation between health disorders. On the first subset, the alternative model fits the experts' opinion slightly better than the original model (P = 0.061). On the second subset, the models performed equally. In conclusion, the proposed refinements for calculating scores are validated since they significantly reduced 'threshold effects' and the influence of measures related to drinkers. It also reduced the compensation between health disorders by considering only the three lowest scores and thus increasing the influence of measures related to health disorders, and slightly improve at overall score level the accordance with experts' opinion.

Developing a tool to assess the health-related quality of life in calves with respiratory disease: content validation.

Bovine respiratory disease (BRD) is a major welfare and productivity issue for calves. Despite the extensive negative impacts on calf welfare and performance, BRD remains challenging to detect and treat effectively. However, the clinical signs of disease are only one aspect of the disease that is experienced by the individual. The assessment of emotional experience in animals is not straightforward, but it is increasingly recognised that the quality of behaviour and demeanour of an individual is a reflection of their internal emotional state. The aim of the present study was to complete the content validation stage of the development process for a health-related quality of life (HRQOL) tool. This was based around indicators from an existing conceptual framework containing twenty-three indicators in two domains (clinical signs and behavioural expression). The content validation stage involves engaging with key stakeholders. For this study, this took the form of a survey and discussions with focus groups, which are standard methods in this field. A survey and stakeholder focus groups were conducted to assess the usefulness of each indicator and its relevance for inclusion within a HRQOL tool. In the survey, participants were asked to rate the usefulness of each of the indicators using a 4-point scale which were then dichotomised into 'useful' and 'less useful'. Based on the 'useful' result, each indicator within the domains was ranked. A similar approach was taken with the responses from the focus groups. Focus group participants were asked to select indicators that they felt were of use and the result of this was used to rank each of the indicators. The ranks of the indicators from both the survey and the focus groups along with the transcripts from the focus groups were used to determine the indicators from each domain to include within the HRQOL tool. Indicators within the clinical signs domain that were included were nasal discharge, cough, respiratory effort, ocular appearance (discharge and vibrancy), body and head posture and ear carriage. For the domain of behavioural expression, the indicators included were movement to feed, responsiveness, spatial proximity, volume of feed intake, motivation at feed and vigour. The next stage will be to validate the construction of the HRQOL tool through its use in practice. The inclusion of indicators that allow the experiential aspects of disease to be recorded in health assessments will likely increase the ability of farmers and others to detect respiratory disease in calves.

Early prediction of respiratory disease in preweaning dairy calves using feeding and activity behaviors.

Bovine respiratory disease (BRD) represents one of the major disease challenges affecting preweaning dairy-bred calves. Previous studies have shown that differences in feeding and activity behaviors exist between healthy and diseased calves affected by BRD. The aim of this study was to develop and assess the accuracy of models designed to predict BRD from feeding and activity behaviors. Feeding and activity behaviors were recorded for 100 male preweaning calves between ~8 to 42 d of age. Calves were group housed with ad libitum access to milk via automatic milk feeders, water, starter diet, and straw. Activity was monitored via a leg-mounted accelerometer. Health status of individual calves was monitored daily using an adapted version of the Wisconsin Scoring System to identify BRD. Three models were created to predict disease: (1) deviation from normal lying time based on moving averages (MA); (2) random forest (RF), a machine learning technique based on feeding and activity variables; and (3) a combination of RF and MA output. For the MA model, lying time was predicted based on behavior over previous days (3- and 7-d MA) and the expected value for the current day (based on calf age; measured using accelerometers). Data were not split into training and test data sets. Occasions when the actual lying time increased >9% of predicted lying time were classified as a deviation from normal and a disease alert was provided. Both feeding and activity behaviors were included within the RF model. Data were split into training (70%) and test (30%) data sets based on disease events. Events were classified as 2 d before, the day(s) of the disease event, and 2 d after the event. Accuracy of models was assessed using sensitivity, specificity, balanced accuracy, and Matthews correlation coefficient (MCC). If a positive disease prediction agreed with an actual disease event within a 3-d rolling window, it was classified as a true positive. Stand-alone models (RF; MA) showed high specificity (0.95; 0.97), moderate sensitivity (0.35; 0.43), balanced accuracy (0.65; 0.64), and MCC (0.25; 0.29). Combining outputs increased accuracy (specificity = 0.95, sensitivity = 0.54, balanced accuracy = 0.75, MCC = 0.36). The work presented is the first to demonstrate the use of modeling data derived from precision livestock farming techniques that monitor feeding and activity behaviors for early detection of BRD in preweaning calves, offering a significant advance in health management of youngstock.

Feeding behaviour and activity as early indicators of disease in pre-weaned dairy calves.

Across the industry, there is large variation in health status of dairy calves and as a result, disease incidence and antibiotic use is high. This has significant implications for animal welfare, productivity and profitability of dairy and dairy-beef production systems. Technology-based early detection systems could alleviate these issues; however, methods of early detection of disease in dairy calves have not been widely explored. This study aimed to determine whether changes in activity and feeding behaviour can be used as early warning indicators of respiratory disease in calves. In total, 100 pre-weaned male Holstein calves (age: ~8-42 days) were used. Calves were group-housed and provided with starter diet, straw bedding and ad libitum water. Calves were fed milk replacer ad libitum through an automatic calf feeder, and each calf was fitted with a leg-mounted activity monitor. Daily activity and feeding behaviour variables were calculated for each calf. Each calf was assessed daily using a modified version of the Wisconsin Scoring System to assess respiratory disease status. Calves were classed as 'Diseased', 'Intermediate' or 'Healthy' based on their cumulative health score. The peak day of the most extreme illness event was identified for each calf. Data from Diseased and Healthy calves were paired for analysis based on age and BW. Data were compared for the day of peak illness, and for the 3 days previous and post. Compared to healthy calves, diseased calves lay for longer and tended to have longer lying bouts (daily lying: 17.6 ±â€¯0.3 vs 16.7 ±â€¯0.2 h, P < 0.01; bout length: 74.8 ±â€¯10.6 vs 56.0 ±â€¯3.7 min, P = 0.09 for diseased and healthy calves, respectively). Diseased calves fed for a shorter time and had fewer feeder visits (with intake) each day compared to healthy calves (feeding time (min): 19.3 ±â€¯1.4 vs 22.8 ±â€¯1.5; P < 0.05; visits: 2.1 ±â€¯0.2 vs 3.2 ±â€¯0.4; P < 0.05). Importantly, differences between diseased and healthy calves were evident in both activity and feeding behaviour on the days prior to the peak day of disease. Lying bout length was greater in diseased calves for the 2 days prior to the peak day (P < 0.05), lying time was longer on day -1 (P < 0.05) and feeder visits with milk intake were less frequent on day -3 (P < 0.05). Thus, measurement of feeding and activity using precision technology within early detection systems could facilitate early intervention and optimized treatment.

Dairy cow trade-off preference for 2 different lying qualities: Lying surface and lying space.

Lying down is an important behavior for cows, contributing to their health and welfare. With dairy cows being housed for increasingly longer periods, if not year-round, it is important to ensure that dairy cow lying comfort is not compromised when they are housed. The aim of this study was to assess cow preference for 2 different qualities of lying area that appear to be important to cows-surface type and an open lying space-to better understand how to optimize lying comfort for cows when housed. Twenty-four Holstein dairy cows were used during the study, which took place in Scotland from July to November 2018. The study consisted of 6 experimental periods, each lasting a total of 21 d. Cows were tested 4 at a time and individually housed in their own test pen. Each pen had 3 lying surfaces: sand, mattress, and straw (2.4 m × 2.4 m each) with a freestall in the middle of each, which could be removed. Cows were given access to one surface at a time (training period) with a freestall for 2 d, and then given a choice of all 3 surfaces for 2 d. When given the choice with freestalls in position, cows spent, on average, the largest amount of their lying time on straw (46.6 ± 7.8%) followed by mattress (44.3 ± 12.4%). Freestalls were then removed and the training and choice phase was repeated on the following day, with cows, on average, spending the most time lying on straw (64.4 ± 7.2%). Finally, a freestall was refitted onto each cow's most preferred surface and the cows were given a choice between lying on their most preferred surface with a freestall (P1 + freestall) or on their second or third preferred surface without a freestall (P2 + open and P3 + open, respectively) for 3 d. During this final trade-off stage, of the 19 cows for which data were available, 14 cows chose to give up the opportunity to lie down on their most preferred surface to have more space on P2 + open and P3 + open, 3 cows chose to lie down on P1 + freestall, and 2 cows made no clear choice. Overall, cows spent the largest amount of their total lying time on their second most preferred surface as an open lying space (65.7 ± 6.9%) compared with their preferred surface with a freestall (20.5 ± 5.9%) and their third preferred surface as an open lying space (13.8 ± 3.7%). The results indicate that when lying down, these dairy cows value an open lying space more than the lying surface.

The behavior of dairy cattle in the transition period: Effects of blood calcium status.

The aim of this study was to use an automated behavior-monitoring system to objectively assess the association between lying and activity behavior in the precalving, calving, and postcalving periods between multiparous and primiparous cows with (1) normocalcemia, (2) subclinical hypocalcemia, or (3) clinical hypocalcemia at calving. Behavioral data and blood serum samples were collected from 51 multiparous and 21 primiparous Holstein dairy cattle. Blood samples from the coccygeal vein were taken within 24 h of calving, and serum was analyzed to measure total calcium concentration. Cows were classified into one of 3 categories: normocalcemia (serum calcium concentration ≥ 2.0 mmol/L), subclinical hypocalcemia (serum calcium concentration < 2.0 mmol/L, absence of clinical signs), and clinical hypocalcemia (clinical signs and successful treatment). An activity sensor was fitted to the right hind leg of cows 3 wk before their expected calving date. Data for lying time, standing time, number of steps, and the total number of standing and lying bouts (postural transitions) were automatically collected and summed into 15-min blocks. Behavioral variables were summarized into 2-h and 24-h periods before analyses. Mixed effect models were used to analyze cow behavior in the entire 14 d before calving (d -14 to -1), on the day of calving, and the entire 21 d postcalving (d 1 to 21). In the precalving period, multiparous cows with normocalcemia had fewer postural transitions (18.5 ± 6.9 no./d) compared with cows with subclinical hypocalcemia (23.5 ± 8.0 no./d) and clinical hypocalcemia (23.5 ± 8.6 no./d). However, there was no association between blood calcium status on lying time (min/d) or step count (no./d) for multiparous cows. For primiparous cows, the step count of cows with subclinical hypocalcemia remained constant across the period, and the step count of cows with normocalcemia decreased from 842.8 steps/d on d -14 to 427.5 steps/d on d -1. Postpartum cows with clinical hypocalcemia were less active (fewer steps) and spent 88 min/d (1.5 h) and 125 min/d (2.1 h) more time lying down compared with cows with subclinical hypocalcemia and normocalcemia, respectively. This shows that clinical hypocalcemia is associated with significant long-lasting behavioral effects on cows during the critical postpartum period.

Comparison of thermal imaging and rectal temperature in the diagnosis of pyrexia in pre-weaned calves using on farm conditions.

Measuring core body temperature is used as part of the diagnostic process in assessing the health of animals. Typically in calves, this is carried out using a rectal thermometer which can be time consuming, stressful to the calf and is invasive by nature. A non-invasive technique that is gaining recognition is thermal imaging. This study investigated the use of thermal imaging as a technique to assess core body temperature in pre-weaned artificially reared calves. A total of 125 male and female calves had rectal temperatures measured daily from day 7 until day 40 of life, and at the same time had a thermal image taken of the area around the medial canthus of the eye. A weak correlation (r = 0.28) was found between calf rectal temperature and thermal image temperature. A multivariable predictive model for core body temperature increased the correlation (r = 0.32) when including the environmental parameters of air temperature (p < .001) and wind speed (p < .001) as well as reconstituted milk replacer consumption (p < .01). The effectiveness of a predictive model including these parameters for the detection of calves with a core body temperature ≥ 39.5 °C was examined and found to have a sensitivity of 0% and a specificity of 100%. The results of this study demonstrate the need to take thermal environmental parameters into consideration when using thermal imaging to assess body temperature. However, the results suggest that accurate measures of core body temperature using thermal imaging cannot be achieved under commercial farm conditions. Further research is needed to determine what other factors could be measured to increase predictive ability.

The behavior of dairy cattle in late gestation: Effects of parity and dystocia.

The aim of this study was to objectively assess, using an automated behavioral monitoring system, any behavioral differences between primiparous and multiparous cows before calving, and to quantify any behavioral differences between assisted (dystocic) and unassisted (eutocic) calvings. Data were collected from 32 multiparous and 12 primiparous Holstein dairy cattle to describe normal calving behavior and parity differences. To quantify behavior related to calving difficulty, the data from 14 animals that had dystocia at calving were matched to cows that had an eutocic calving based on parity, locomotion score, calf breed, calf sex, month, and year of calving. An IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) was fitted to the right hind leg of cows 4 wk before their expected calving date. Data for lying time, standing time, number of steps, motion index (total motion), and the total number of standing and lying bouts (postural transitions) were automatically collected and summed into 15-min blocks. Behavioral variables were summarized into 2-h periods and 24-h periods before analyses. Mixed-effect models were used to analyze cow behavior in the last 4 d before calving (d -4 to -1), and on the day of calving. In the 4 d before calving, compared with multiparous cows, primiparous cows lay down an average 2.8 h/d less, had 9.1 more postural transitions/d (37.7 ± 1.2 vs. 27.6 ± 0.7), walked 172 more steps/d, and had a higher motion index (2,673.2 vs. 1,981.5 units/d). There was an effect of 2-h period on all behavioral variables on the day of calving. No indicator of calving difficulty was found on the day of calving, nor the days leading up to calving. These findings suggest that parity should be considered when predicting the day of calving, and changes in cow behavior on the day of calving could be used to identify calving cows, and to predict the time of calving.

Relationship between metabolic status and behavior in dairy cows in week 4 of lactation.

Blood metabolite and hormone concentrations are indicative of metabolic status, but blood sampling and analysis is invasive and time-consuming. Monitoring behavior can be done automatically, and behaviors may also be used as indicators of metabolic status. The aim of this study was to analyze the relationships between metabolic status and feeding behavior, lying behavior, motion index and steps of dairy cows in week 4 postpartum. Behavioral data from 81 Holstein-Friesian cows were collected using computerized feeders and accelerometers, and blood samples were collected for analysis of free-fatty acid (FFA), ß-hydroxybutyrate (BHB), glucose, insulin, IGF-1 and growth hormone (GH) concentrations. First, cluster analysis was performed to categorize cows as having poor, average, good or very good metabolic status based on their plasma FFA, BHB, glucose, insulin, IGF-1 and GH concentration. Subsequently, the performance and behavior of cows in clusters with poor, average and good metabolic status were compared using GLM. Cows with a poor or average metabolic status tended to have greater fat-and-protein-corrected milk yield than cows with good metabolic status. Furthermore, cows with a poor metabolic status had a lower energy balance and dry matter intake (DMI) than cows with an average or good metabolic status and had a lower number of meals than cows with good metabolic status. Daily number of visits to the feeder and lying time tended to be positively related with metabolic status. Feeding rate (kg/min), daily meal time (min/day), number of lying bouts per day, steps and motion index were not related with metabolic status. In conclusion, better metabolic status in dairy cows in early lactation was associated with a greater DMI, increased feeding activity and a tendency to more time spent lying, compared with poor metabolic status. These results suggest that compromised metabolic status is reflected in altered cow's behavior in week 4 of lactation.

The use of infrared thermography for detecting digital dermatitis in dairy cattle: What is the best measure of temperature and foot location to use?

Lameness in dairy cattle is a persistent problem, indicating pain caused by underlying disease states and is associated with reduced milk yields. Digital dermatitis is a common cause of lameness. Thermal imaging is a technique that may facilitate early detection of this disease and has the potential for use in automated detection systems. Previous studies with thermal imaging have imaged either the heels or the coronary band of the foot and typically only used the maximum temperature (Max) value as the outcome measure. This study investigated the utility of other statistical descriptors: 90th percentile (90PCT), 95th percentile (95PCT), standard deviation (SD) and coefficient of variation (CoV) and compared the utility of imaging the heel or coronary band. Images were collected from lame and healthy cows using a high-resolution thermal camera. Analyses were done at the cow and foot level. There were significant differences between lame and healthy feet detectable at the heels (95th percentile: P<0.05; SD: P<0.05) and coronary band (SD: P<0.05). Within lame cows, 95PCT values were higher at the heel (P<0.05) and Max values were higher at the coronary band (P<0.05) in the lame foot compared to the healthy foot. ROC analysis showed an AUC value of 0.72 for Max temperature and 0.68 for 95PCT at the heels. It was concluded that maximum temperature is the most accurate measure, but other statistical descriptors of temperature can be used to detect lameness. These may be useful in certain contexts, such as where there is contamination. Differentiation of lame from healthy feet was most apparent when imaging the heels.

Accuracy of genotype imputation in Labrador Retrievers.

The dog is a valuable model species for the genetic analysis of complex traits, and the use of genotype imputation in dogs will be an important tool for future studies. It is of particular interest to analyse the effect of factors like single nucleotide polymorphism (SNP) density of genotyping arrays and relatedness between dogs on imputation accuracy due to the acknowledged genetic and pedigree structure of dog breeds. In this study, we simulated different genotyping strategies based on data from 1179 Labrador Retriever dogs. The study involved 5826 SNPs on chromosome 1 representing the high density (HighD) array; the low-density (LowD) array was simulated by masking different proportions of SNPs on the HighD array. The correlations between true and imputed genotypes for a realistic masking level of 87.5% ranged from 0.92 to 0.97, depending on the scenario used. A correlation of 0.92 was found for a likely scenario (10% of dogs genotyped using HighD, 87.5% of HighD SNPs masked in the LowD array), which indicates that genotype imputation in Labrador Retrievers can be a valuable tool to reduce experimental costs while increasing sample size. Furthermore, we show that genotype imputation can be performed successfully even without pedigree information and with low relatedness between dogs in the reference and validation sets. Based on these results, the impact of genotype imputation was evaluated in a genome-wide association analysis and genomic prediction in Labrador Retrievers.

Temperament and dominance relate to feeding behaviour and activity in beef cattle: implications for performance and methane emissions.

In beef cattle, feeding behaviour and activity are associated with feed efficiency and methane (CH4) emissions. This study aimed to understand the underlying traits responsible for the contribution of cattle behaviour to individual differences in feed efficiency, performance and CH4 emissions. A total of 84 steers (530±114 kg BW) of two different breeds (crossbreed Charolais and Luing) were used. The experiment was a 2×2×3 factorial design with breed, basal diets (concentrate v. mixed) and dietary treatments (no additive, calcium nitrate or rapeseed cake) as the main factors. The individual dry matter intake (DMI; kg) was recorded daily and the BW was measured weekly over a 56-day period. Ultrasound fat depth was measured on day 56. Based on the previous data, the indexes average daily gain, food conversion and residual feed intake (RFI) were calculated. The frequency of meals, the duration per visit and the time spent feeding per day were taken as feeding behaviour measures. Daily activity was measured using the number of steps, the number of standing bouts and the time standing per day. Agonistic interactions (including the number of contacts, aggressive interactions, and displacements per day) between steers at the feeders were assessed as indicators of dominance. Temperament was assessed using the crush score test (which measures restlessness when restrained) and the flight speed on release from restraint. Statistical analysis was performed using multivariate regression models. Steers that spent more time eating showed better feed efficiency (P=0.039), which can be due to greater secretion of saliva. Feeding time was longer with the mixed diet (P<0.001), Luings (P=0.009) and dominant steers (P=0.032). Higher activity (more steps) in the pen was associated with poorer RFI, possibly because of higher energy expenditure for muscle activity. Frequent meals contributed to a reduction in CH4 emissions per kg DMI. The meal frequency was higher with a mixed diet (P<0.001) and increased in more temperamental (P=0.003) and dominant (P=0.017) steers. In addition, feed intake was lower (P=0.032) in more temperamental steers. This study reveals that efficiency increases with a longer feeding time and CH4 emissions decrease with more frequent meals. As dominant steers eat more frequently and for longer, a reduction in competition at the feeder would improve both feed efficiency and CH4 emissions. Feed efficiency can also be improved through a reduction in activity. Selection for calmer cattle would reduce activity and increase feed intake, which may improve feed efficiency and promote growth, respectively.

Trained-user opinion about Welfare Quality measures and integrated scoring of dairy cattle welfare.

The Welfare Quality (WQ) protocol for on-farm dairy cattle welfare assessment describes 27 measures and a stepwise method for integrating values for these measures into 11 criteria scores, grouped further into 4 principle scores and finally into an overall welfare categorization with 4 levels. We conducted an online survey to examine whether trained users' opinions of the WQ protocol for dairy cattle correspond with the integrated scores (criteria, principles, and overall categorization) calculated according to the WQ protocol. First, the trained users' scores (n = 8-15) for reliability and validity and their ranking of the importance of all measures for herd welfare were compared with the degree of actual effect of these measures on the WQ integrated scores. Logistic regression was applied to identify the measures that affected the WQ overall welfare categorization into the "not classified" or "enhanced" categories for a database of 491 European herds. The smallest multivariate model maintaining the highest percentage of both sensitivity and specificity for the "enhanced" category contained 6 measures, whereas the model for "not classified" contained 4 measures. Some of the measures that were ranked as least important by trained users (e.g., measures relating to drinkers) had the highest influence on the WQ overall welfare categorization. Conversely, measures rated as most important by the trained users (e.g., lameness and mortality) had a lower effect on the WQ overall category. In addition, trained users were asked to allocate criterion and overall welfare scores to 7 focal herds selected from the database (n = 491 herds). Data on all WQ measures for these focal herds relative to all other herds in the database were provided. The degree to which expert scores corresponded to each other, the systematic difference, and the correspondence between median trained-user opinion and the WQ criterion scores were then tested. The level of correspondence between expert scoring and WQ scoring for 6 of the 12 criteria and for the overall welfare score was low. The WQ scores of the protocol for dairy cattle thus lacked correspondence with trained users on the importance of several welfare measures.

Current available strategies to mitigate greenhouse gas emissions in livestock systems: an animal welfare perspective.

Livestock production is a major contributor to greenhouse gas (GHG) emissions, so will play a significant role in the mitigation effort. Recent literature highlights different strategies to mitigate GHG emissions in the livestock sector. Animal welfare is a criterion of sustainability and any strategy designed to reduce the carbon footprint of livestock production should consider animal welfare amongst other sustainability metrics. We discuss and tabulate the likely relationships and trade-offs between the GHG mitigation potential of mitigation strategies and their welfare consequences, focusing on ruminant species and on cattle in particular. The major livestock GHG mitigation strategies were classified according to their mitigation approach as reducing total emissions (inhibiting methane production in the rumen), or reducing emissions intensity (Ei; reducing CH4 per output unit without directly targeting methanogenesis). Strategies classified as antimethanogenic included chemical inhibitors, electron acceptors (i.e. nitrates), ionophores (i.e. Monensin) and dietary lipids. Increasing diet digestibility, intensive housing, improving health and welfare, increasing reproductive efficiency and breeding for higher productivity were categorized as strategies that reduce Ei. Strategies that increase productivity are very promising ways to reduce the livestock carbon footprint, though in intensive systems this is likely to be achieved at the cost of welfare. Other strategies can effectively reduce GHG emissions whilst simultaneously improving animal welfare (e.g. feed supplementation or improving health). These win-win strategies should be strongly supported as they address both environmental and ethical sustainability. In order to identify the most cost-effective measures for improving environmental sustainability of livestock production, the consequences of current and future strategies for animal welfare must be scrutinized and contrasted against their effectiveness in mitigating climate change.

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.

Creating a model to detect dairy cattle farms with poor welfare using a national database.

The objective of this study was to determine whether dairy farms with poor cow welfare could be identified using a national database for bovine identification and registration that monitors cattle deaths and movements. The welfare of dairy cattle was assessed using the Welfare Quality(®) protocol (WQ) on 24 Portuguese dairy farms and on 1930 animals. Five farms were classified as having poor welfare and the other 19 were classified as having good welfare. Fourteen million records from the national cattle database were analysed to identify potential welfare indicators for dairy farms. Fifteen potential national welfare indicators were calculated based on that database, and the link between the results on the WQ evaluation and the national cattle database was made using the identification code of each farm. Within the potential national welfare indicators, only two were significantly different between farms with good welfare and poor welfare, 'proportion of on-farm deaths' (p<0.01) and 'female/male birth ratio' (p<0.05). To determine whether the database welfare indicators could be used to distinguish farms with good welfare from farms with poor welfare, we created a model using the classifier J48 of Waikato Environment for Knowledge Analysis. The model was a decision tree based on two variables, 'proportion of on-farm deaths' and 'calving-to-calving interval', and it was able to correctly identify 70% and 79% of the farms classified as having poor and good welfare, respectively. The national cattle database analysis could be useful in helping official veterinary services in detecting farms that have poor welfare and also in determining which welfare indicators are poor on each particular farm.

Current trends in British dairy management regimens.

This paper presents a summary of results from a 2012 survey that investigated feeding and housing management regimens currently adopted by dairy farmers in Britain. Responses from 863 farms provide a snapshot of dairy industry structure and a description of the range of management systems currently in operation. Outcomes highlight a diversity of management practices, showing that 31% of farms maintained a traditional grazing system with no forage feeding indoors during the summer, whereas 38% of farmers indicated that all their milking cows received some feeding indoors during the summer. A system of housing dairy cows for 24 h/d while they are lactating was implemented by 8% of farms, whereas 1% of farms did not house their cows at any time of the year. Statistical analyses were carried out on 3 distinct groups identified from survey responses: (1) farmers who did not undertake any indoor feeding during the summer; (2) farmers who fed all their milking cows indoors during the summer; and (3) farmers who continuously housed their cows for 24h/d while lactating. Results showed a significant relationship between management type and herd size, and between management type and breed type; on average, herd sizes were larger within systems that feed indoors. No significant relationship was found between management type and farm location when classified by estimated grassland productivity. The results indicate that traditional all-summer grazing is no longer the predominant system adopted by dairy farmers and that other systems such as all-year-round indoor feeding and continuous housing are becoming more prevalent in Britain.

Comparison of breast milk vitamin A concentration measured in fresh milk by a rapid field assay (the iCheck FLUORO) with standard measurement of stored milk by HPLC.

Availability of rapid, point-of-contact analytical methods would facilitate the use of breast milk vitamin A concentration (BMVA) to assess vitamin A (VA) status. We compared BMVA concentrations measured by high-performance liquid chromatography (HPLC) (the standard technique) with those by iCheck FLUORO, a new portable fluorometer that can rapidly quantify BMVA. Casual breast milk samples (n=154) were collected during a representative survey in Yaoundé and Douala, Cameroon. Milk fat and BMVA concentrations (by iCheck) were measured in fresh milk in the field. After storage at <-20 °C, BMVA concentrations were also measured by HPLC. BMVA values from the two methods were highly correlated (R(2)=0.72 for BMVA/l; R(2)=0.62 for BMVA/g fat, both P<0.0001). HPLC values were greater than iCheck values on average, and the difference increased with increasing BMVA. The iCheck FLUORO could be useful for monitoring fortification programs, but before-after surveys to assess change in BMVA concentrations should use one method consistently.