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The emerging risk of resistance to antimicrobials has brought about the need to document animal production in the European Union. The required documentation of treatment data on-farm may withhold viable information, which can be analysed if made accessible in a digital format. The aim of the study was to use a digital system for the documentation of treatments and to investigate relationships between treatments, performance parameters and breeds. Data were collected between August 2020 and September 2022 on a combined pig farm in northern Germany. A digital tool was used to obtain data on treatments, while sows' performance information and breed data were drawn from the sow planner of the farm. Treatment indices were generated for the sows (TIS, treatment index sow) and the sows' litters (treatment index litter, TIL). During the time of data collection, 17 % (n = 113) of the farrowing events (n = 661) took place with farrowing-related treatments (FRTs), and 43.5 % (n = 94) of the sows had to receive FRT at least once. Linear mixed models were used to investigate the dependent variables TIS, TIL and FRT and the performance parameters piglets born alive, stillborn piglets and weaned piglets. The explanatory variables parity, season, year, the interaction of season and year, and the breed of the sow (crossbred Large White × Landrace and purebred Large White), as well as the random effect of the sow nested in the breed of the sow, were included in the models for all dependent variables. Additionally, the breed of the boar (Duroc, Pietrain), TIS, TIL and FRT were investigated in the models of the performance parameters. The following effects were all significant (p). Parity had an effect on TIS, piglets born alive and stillborn piglets. Sows with parity of 1 had the highest least-squares mean (LSM) = 0.42 (standard error (SE) = 0.04) for TIS, which decreased over parities of 2–3, 4–5 and 6–7 (LSM = 0.16, SE = 0.04) and increased for parity of ≥8 (LSM = 0.34, SE = 0.05). While sows with parity of 1 produced the lowest numbers and sows with parities of 4–5 the highest numbers of piglets born alive, the number of stillborn piglets increased with parity number, with the lowest numbers for parity of 1 and the highest numbers for parity of ≥8. Overall, the performance of the farm improved in the second year of data collection with less FRT, more weaned piglets and fewer stillborn piglets. Crossbred sows produced more piglets born alive and weaned piglets but also more stillborn piglets. The use of Pietrain boars led to more piglets being born alive. FRT and high treatment indices of the sow related with an increase in stillborn piglets and high treatment indices of the sow resulted in fewer piglets born alive. In conclusion, digitalized treatment data allow for analyses of the herd's health status, and relations between production performance and treatments can be investigated.

Abstract Background Tail biting is a multifactorial problem. As the health status is one of the factors commonly linked to tail biting, this study focuses on the health of identified biters. 30 (obsessive) biters are compared to 30 control animals by clinical and pathological examination as well as blood and cerebrospinal fluid samples. In that way, altogether 174 variables are compared between the groups. Moreover, connections between the variables are analysed. Results In the clinical examination, 6 biters, but only 2 controls (P = 0.019) were noticeably agitated in the evaluation of general behaviour, while 8 controls were noticeably calmer (2 biters, P = 0.02). Biters had a lower body weight (P = 0.0007) and 13 biters had overlong bristles (4 controls, P = 0.008). In the pathological examination, 5 biters, but none of the controls had a hyperceratosis or inflammation of the pars proventricularis of the stomach (P = 0.018). However, 7 controls and only 3 biters were affected by gut inflammation (P = 0.03). In the blood sample, protein and albumin levels were below normal range for biters (protein: 51.6 g/l, albumin: 25.4 g/l), but not for controls (protein: 53.7 g/l, albumin: 27.4 g/l), (protein: P = 0.05, albumin: P = 0.02). Moreover, 14 biters, but only 8 controls had poikilocytosis (P = 0.05). Although not statistically different between groups, many animals (36/60) were affected by hypoproteinemia and hyponatremia as well as by hypokalemia (53/60) and almost all animals (58/60) had hypomagnesemia. For hypomagnesemia, significant connections with variables linked to tail damage and ear necrosis were detected (rs/V/ρ ≥ 0.4, P ≤ 0.05). Conclusion The results suggest that behavioural tests might be helpful in identifying biters. Moreover, cornification and inflammation of the pars proventricularis is linked to becoming a biter. Furthermore, the results highlight the need for appropriate and adjusted nutrient and mineral supply, especially with regard to magnesium.

Dairy cattle housing is characterised by increasing herd sizes and the need for assisting technical tools to monitor the cows’ health. This study investigated the combination of logistic regression models with multivariate cumulative sum (MCUSUM) control charts in healthmonitoring of dairy cattle. Sensor information of 618 cows with 791 lactations (138 438 cow days), nine behavioural variables were included as parts of the behavioural patterns: physical activity (“neck activity”, “leg activity”, “walking duration”), resting (“lying duration”, “standing duration”, “transitions from lying to standing”) and feeding (“feeding duration”, “rumination duration”, “inactivity duration”) behaviour. For each of these behavioural patterns, a logistic regression model with the health status (sick vs not sick) as a dependent variable was designed after a variable selection (herd level) based on the herd dataset with 618 cows (618 lactations; 115 547 cow days), which included the variables of each behaviour pattern and the stage of lactation nested in the number of lactations as explanatory variables. The explanatory variables were added stepwise to the model, with the final model being selected with respect to the lowest values of Akaike’s and Bayes’ information criteria. Each model was then applied to a dataset with 173 cows (22 891 cow days) at cow level, resulting in individual daily risk probabilities for getting sick. Thus, risk probabilities of each behavioural pattern were estimated and included in the MCUSUM control charts to identify cows at risk of disease. The performance of the MCUSUM control charts was cross-validated to identify the best fitting reference value k and the threshold value h. Alerts given within 5 days prior to diagnosis were counted as detected sicknesses. The performance resulted in a block sensitivity of 70.9–81.4%, specificity of 87.9–94.2% and a false-positive rate of 5.8–12.1%. The performance was confirmed while testing the entire algorithm resulting in a mean area under the receiver operating characteristics curve of 0.89. Calculating precision and the F1-score resulted in a precision of 49.0–60.9% (training: 48.8–63.5%) and an F1-score of 61.1–65.7% in testing (training: 61.0–67.0%). The precision-recall curve (PRC) was derived from precision and recall with an area under the PRC of 0.70 in training and testing. In summary, the present study was able to develop an algorithm showing good classification potential for the online monitoring of sickness behaviour.

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

In general, one animal is considered dominant over another animal if it has won more fights than its opponent. Whether this difference in won and lost fights is significant is neglected in most studies. Thus, the present study evaluates the impact of two different calculation methods for dyadic interactions with a significant asymmetric outcome on the results of social network analysis regarding agonistic interactions of pigs in three different mixing events (weaned piglets, fattening pigs and gilts). Directly after mixing, all animals were video recorded for 17 (fattening pigs, gilts) and 28 h (weaned piglets), documenting agonistic interactions. Two calculation methods for significant dyads, that is, dyadic interactions with a clear dominant subordinate relationship in which one animal has won significantly more fights than its encounter, were proposed: pen individual limits were calculated by a sign test considering the differences of won and lost fights of all dyadic interactions in each pen; dyad individual limits were determined by a one-sided sign test for each individual dyad. For all data sets (ALL, including all dyadic interactions; PEN or DYAD, including only significant dyads according to pen or dyad individual limits), networks were built based on the information of initiator and receiver with the pigs as nodes and the edges between them illustrating attacks. General network parameters describing the whole network structure and centrality parameters describing the position of each animal in the network were calculated. Both pen and dyad individual limits revealed only a small percentage of significant dyads for weaned piglets (12.4% or 8.8%), fattening pigs (4.2% or 0.6%) and gilts (3.6% or 0.4%). The comparison between the data sets revealed only high Spearman’s rank correlation coefficients (rS) for the density, that is, percentage of possible edges that were actually present in the network, whereas the centrality parameters showed only moderate rS values (0.37 to 0.75). Thus, the rank order of the animals changed due to the exclusion of insignificant dyads, which shows that the results obtained from social network analysis are clearly influenced if insignificant dyads are excluded from the analyses. Due to the fact that the pen individual limits consider the overall level of agonistic interactions within each pen, this calculation method should be preferred over the dyad individual limits. Otherwise, too many animals in the group became isolated nodes with zero centrality for which no statement about their position within the network can be made.

The recent development of dairy production is characterised by increasing herd sizes and therefore increasingly complicated visual observation of cow behaviour, which is traditionally the basis for diagnoses of production diseases. The limitation of the direct visual behavioural observation due to the increasing number of individual cows implies a growing need for an automated detection of changes within behavioural patterns to identify cows that show sickness behaviour. Sensor systems can be used to measure behavioural patterns such as activity, resting, feeding and rumination. Behavioural patterns change with the occurrence of sickness but also interact with external factors. Changes such as prolonged lying duration or shortened feeding duration caused by metabolic disorders or infections, respectively, then serve as a detection tool for sick individuals. The aim of the present review is to outline the impact of production diseases on the daily behavioural patterns of dairy cows by referring to sickness behaviour.

The aim of this paper was to validate an alternative multi-criteria evaluation system to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. This alternative methodology aimed to be more transparent for stakeholders and more flexible than the methodology proposed by WQ. The WQ assessment protocol for growing pigs was implemented to collect data in different farms in Schleswig-Holstein, Germany. In total, 44 observations were carried out. The aggregation system proposed in the WQ protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first two steps of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion and principle. The utility functions and the aggregation function were constructed in two separated steps. The MACBETH (Measuring Attractiveness by a Categorical-Based Evaluation Technique) method was used for utility function determination and the Choquet integral (CI) was used as an aggregation operator. The WQ decision-makers’ preferences were fitted in order to construct the utility functions and to determine the CI parameters. The validation of the MAUT model was divided into two steps, first, the results of the model were compared with the results of the WQ project at criteria and principle level, and second, a sensitivity analysis of our model was carried out to demonstrate the relative importance of welfare measures in the different steps of the multi-criteria aggregation process. Using the MAUT, similar results were obtained to those obtained when applying the WQ protocol aggregation methods, both at criteria and principle level. Thus, this model could be implemented to produce an overall assessment of animal welfare in the context of the WQ protocol for growing pigs. Furthermore, this methodology could also be used as a framework in order to produce an overall assessment of welfare for other livestock species. Two main findings are obtained from the sensitivity analysis, first, a limited number of measures had a strong influence on improving or worsening the level of welfare at criteria level and second, the MAUT model was not very sensitive to an improvement in or a worsening of single welfare measures at principle level. The use of weighted sums and the conversion of disease measures into ordinal scores should be reconsidered.

The aim of this paper was to present an alternative multi-criteria evaluation model to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. The WQ assessment protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first step of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion. The utility functions and the aggregation function were constructed in two separated steps. The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) method was used for utility function determination and the Choquet Integral (CI) was used as an aggregation operator. The WQ decision-makers’ preferences were fitted in order to construct the utility functions and to determine the CI parameters. The methods were tested with generated data sets for farms of growing pigs. Using the MAUT, similar results were obtained to the ones obtained applying the WQ protocol aggregation methods. It can be concluded that due to the use of an interactive approach such as MACBETH, this alternative methodology is more transparent and more flexible than the methodology proposed by WQ, which allows the possibility to modify the model according, for instance, to new scientific knowledge.

The objective of this study was to develop an automated monitoring system to detect lameness in group-housed sows early and reliably on the basis of acceleration data sampled from ear tags. To this end, acceleration data from ear tags were acquired from an experimental system deployed at the Futterkamp Agriculture Research Farm from May 2012 until November 2013. The developed method performs a wavelet transform for each individual sow’s time series of total acceleration. Feature series are then computed by locally estimating the energy, variation and variance in a small moving window. These feature series are then further decomposed into uniform level sets. From these series of level sets, the highest and lowest levels are monitored for lameness detection. To that end, they are split into a past record to serve as reference data representing a sow’s expected behaviour. The deviations between the reference and the remaining detection part of current data, termed feature activated, were then utilised to possibly indicate a lameness condition. The method was applied to a sample of 14 sows, seven of which were diagnosed as lame by a veterinarian on the last day of the sampling period of 14 days each. A prediction part of 3 days was set. Feature activated were clearly separable for the lame and healthy group with means of 8.8 and 0.8, respectively. The day-wise means were 1.93, 9.47 and 15.16 for the lame group and 0.02, 1.13 and 1.44 for the healthy group. A threshold could be set to completely avoid false positives while successfully classifying six lame sows on at least one of the 2 last days. The accuracy values for this threshold were 0.57, 0.71 and 0.78 when restricting to data from the particular day. A threshold that maximised the accuracy achieved values of 0.57, 0.79 and 0.93. Thus, the method presented seems powerful enough to suggest that an individual classification from ear tag-sampled acceleration data into lame and healthy is feasible without previous knowledge of the health status, but has to be validated by using a larger data set.

Animal welfare has become an important subject of public and political debate, leading to the necessity of an objective evaluation system for on-farm use. As welfare is a multi-dimensional concept, it makes sense to use a multi-criteria aggregation system to obtain an overall welfare score. Such an aggregation system is provided by the Welfare Quality® Network. The present paper focusses on the assessment of the multi-criteria evaluation model included in the Welfare Quality® protocol for growing pigs in order to aggregate the animal-based indicators first to criteria, then to principles and finally to an overall welfare score. Specifically, the importance of the indicators on the overall assessment of growing pig farms is analysed in a given population which consisted of a total of 198 protocol assessments carried out on a sample of 24 farms in Germany. By means of partial least squares modelling, the influence of measures in the calculation procedure is estimated by calculation and interpretation of Variable Importance for Projection (VIP) scores. Variable Importance for Projection scores revealed some meaningful, unexpected influences as the multi-criteria evaluation model of Welfare Quality® aimed at avoiding interferences and double-counting. Some of these influences led to the assumption that some measures might have potential as iceberg indicators, whereas others showed lesser importance. Thus, feasibility can be gained by the deletion and special weighting of indicators according to their importance. Altogether, the study is an essential contribution to the further development of the Welfare Quality® protocols as well as the application of multi-criteria decision systems in the field of animal welfare science in general.

Lameness is an important issue in group-housed sows. Automatic detection systems are a beneficial diagnostic tool to support management. The aim of the present study was to evaluate data of a positioning system including acceleration measurements to detect lameness in group-housed sows. Data were acquired at the Futterkamp research farm from May 2012 until April 2013. In the gestation unit, 212 group-housed sows were equipped with an ear sensor to sample position and acceleration per sow and second. Three activity indices were calculated per sow and day: path length walked by a sow during the day (Path), number of squares (25×25 cm) visited during the day (Square) and variance of the acceleration measurement during the day (Acc). In addition, data on lameness treatments of the sows and a weekly lameness score were used as reference systems. To determine the influence of a lameness event, all indices were analysed in a linear random regression model. Test day, parity class and day before treatment had a significant influence on all activity indices (P

Feed production is the main contributor to a subset of environmental impacts of pork production. In this context, this study is concerned with the substitution of soy products in pig diets in order to reduce these impacts. The aim of this study was to assess three alternative diets in gestating and lactating sows as well as growing and finishing pigs in order to reduce the amount of soy products used as ingredients. In the three alternative scenarios soy proteins were compensated for by either using a combination of different feedstuffs (e.g. rapeseed meal, fava beans, and synthetic amino acids) (LOW), maximising the use of legumes (mainly fava beans) (LEG) and increasing the amount of synthetic amino acids (AA). These alternative scenarios were compared with standard diets (ST) and formulated in order to reduce the crude-protein content of the diet while maintaining the same performance of the pigs. Each of the resulting 16 diets was then assessed with respect to global warming, eutrophication, acidification, and land use, both when accounting and not accounting for emissions due to land use change. The analysis per kilogram of feed showed that the ST diets performed best with regard to global warming, eutrophication, and acidification. When emissions from land use and land use change were added, ST and AA diets appeared to have the least impact. In contrast, the assessment of scenarios per kilogram of pork highlighted that the AA scenario contributed the least in all impact categories. In conclusion, it is possible to partly replace soybean products by using synthetic amino acids in order to minimise the environmental impacts of the pork supply chain.

This paper discusses the arising need for an objective, but feasible, reliable and valid method for assessing animal welfare on farms. Animal welfare has become especially important since the industrialisation of animal housing after the Second World War and as public awareness and concern has increased. Simultaneously, alienation of the public from agriculture has taken place, as the population has moved increasingly from rural areas to towns. This has led to a very emotional discussion concerning the welfare of farmed animals, and thus a need for not only a clear definition but also a way of objectively measuring it has arisen. It is probably best defined as a total of the different conceptions health, natural behaviour and positive affective state. In the last few years, different methods for an objective assessment have been developed; however, all of them still face great challenges in their practical implementation and acceptance. The most promising method is probably the Welfare Quality® (WQ) approach, especially as it concentrates on animal-based parameters. The development of the WQ protocols emphasised not only the different conceptions of animal welfare but also especially the feasibility, reliability and validity of the parameters to be included. One of the main challenges of these protocols remains, however, the final aggregation of the results to a welfare score. Furthermore, a thorough cost–benefit analysis has not been carried out so far. Even more importantly, only a few studies have addressed the general reliability and validity of the complete protocols, and those studies that have addressed these issues have also revealed challenges concerning the interobserver and test–retest reliability of some of the included parameters. As an example, this is discussed in detail for the "Welfare Quality® animal welfare assessment protocol for growing pigs". In conclusion, the WQ approach can be seen as promising, but it has also revealed that there are still a considerable number of challenges that need to be addressed in further studies on the WQ protocols in order to achieve constant improvement. These challenges should be borne in mind in the application of these protocols, which should not be simply referred to as a gold standard.

Whenever an outbreak of classical swine fever has occurred in the European Union (EU), the basic control measures have usually been supplemented by preventive culling. This strategy has led to a great number of culled pigs and is discussed by general public and politics from both ethical and economic points of view. Emergency vaccination has been deemed to be an alternative control measure for some time now. PCR testing also provides a possible future strategy, since this method would allow a rapid and reliable testing of pigs in the vicinity of an outbreak farm. In this study, a spatial and temporal Monte-Carlo simulation model was used to compare alternative control strategies based upon these two measures (»Emergency Vaccination«, »Test To Slaughter«, »Test To Control« and »Vaccination in conjunction with Rapid Testing«) with the current control strategy. Two regions for investigation with different farm densities were used in the model. In a region with a low farm density, the basic EU control measures seemed to be sufficient to control an epidemic. In a region with a high farm density, additional measures would be necessary. »Emergency Vaccination« in a 3 km application zone and »Traditional Control« reached the same level of infected farms. Both »Test To Slaughter« and »Test To Control« combined with preventive culling led to a lower number of infected farms compared to the sole preventive culling strategy. The alternative control measures can reduce the number of culled farms significantly compared to »Traditional Control«.

The present study was designed to analyze the growth performance, behavioral patterns and intensity of injuries of weaned pigs (26 days) during a rearing period of 6 weeks. The farrowing system (group housing (GH) v. single housing (SH)) and the post-weaning regrouping weight class (light, medium, heavy) were considered as the main factors. A number of 120 GH-pigs and 120 SH-pigs were kept in three batches (20 pens, 12 pigs each). The GH- and SH-pigs were divided by weight into three groups: light (5 to ⩽7 kg), medium (>7 to ⩽9 kg) and heavy (>9 to ⩽12 kg), with two pigs of six different litters in each pen. The pigs were weighed individually at weaning (week 1) and during rearing (weeks 2, 3 and 7). The feed conversion ratio (FCR) was calculated between weeks 1 and 7. The duration and number of fights (NF) per pen and hour were determined by continuous sampling (40 h after weaning). Lesions of the integument were scored into four classes (none, minor, medium, severe) and recorded at weaning and 48 h afterwards. The farrowing system had no effect on the weights in week 1 (GH: 7.8 kg v. SH: 7.7 kg; week as linear, quadratic regression nested within housing systems) or in week 7 (GH: 29.4 kg v. SH: 28.6 kg). The body weights were influenced significantly by the weaning weight class (light: 11.7 kg (s.e.m.: 0.30), medium: 14.8 kg (s.e.m.: 0.22), heavy: 17.3 kg (s.e.m.: 0.26)). The FCR of the GH-pigs was 1.64 (s.e.m.: 0.03) and 1.58 (s.e.m.: 0.03) for SH-pigs. A reduced agonistic behavior of the GH-pigs was observed with 2.1 fights per pen and hour (s.e.m.: 0.07) v. the SH-pigs with 4.6 fights per pen and hour (s.e.m.: 0.05). The fight duration of the GH-pigs with 10.3 s per pen and hour (s.e.m.: 1.07) was significantly lower in comparison to the SH-pigs with 18.8 s per pen and hour (s.e.m.: 1.06). The SH-pigs had more new skin lesions at the shoulders than the GH-pigs 48 h after weaning (P < 0.05). In conclusion, early mixing of unacquainted litters during lactation had no influence on their growth performance during rearing but reduced agonistic behavior and lesion score difference during the first 2 days after weaning. No significant interaction between the farrowing system and weaning weight class was detected with regard to growth performance and NF.

In spite of the improvement in management and the breeding goal of increasing the number of piglets born alive, piglet mortality is still a substantial problem in pig breeding. The objective of the first part of the study was to estimate genetic parameters for different causes of piglet losses and to investigate the relationship to litter-size traits. Data were collected on a nucleus herd from January till December 2004. Records from 943 German Landrace sows with 1538 pure-bred litters and 13 971 individually weighted piglets were included. Four different causes of piglet losses (LOSS) were evaluated. Additional analysed traits were underweight and runting. Furthermore, the fertility traits number of piglets born alive, born in total and stillborn piglets as well as the individual birth and weaning weights were analysed. The different LOSS were treated as a binary trait and subsequently the heritabilities were estimated using a threshold model. The most important LOSS was crushing under the sow (12.4%). The survival rate and crushing had a heritability of h2 = 0.03. The fertility traits piglets born alive, born in total and stillborn piglets were analysed with a linear model and heritabilities rank from h2 = 0.05 (stillborn) to h2 = 0.10 (born alive). The estimated heritabilities for birth- and weaning weight were both h2 = 0.10. The genetic correlations between number of piglets born alive and each LOSS trait were analysed bivariately. Of all piglets born alive 84.3% survive the lactation period. Survival decreased with increasing litter size (rg = −0.54 up to −0.78) and the probability of being crushed under the sow increased.

The aim of the present study was to investigate the daily measured traits milk yield, water intake and dry matter intake with fixed and random regression models added with different error covariance structures. It was analysed whether these models deliver better model fitting in contrast to conventional fixed and random regression models. Furthermore, possible autocorrelation between repeated measures was investigated. The effect of model choice on statistical inference was also tested. Data recording was performed on the Futterkamp dairy research farm of the Chamber of Agriculture of Schleswig-Holstein. A dataset of about 21 000 observations from 178 Holstein cows was used. Average milk yield, water intake and dry matter intake were 34.9, 82.4 and 19.8 kg, respectively. Statistical analysis was performed using different linear mixed models. Lactation number, test day and the parameters to model the function of lactation day were included as fixed effects. Different structures were tested for the residuals; they were compared for their ability to fit the model using the likelihood ratio test, and Akaike’s and Bayesian’s information criteria. Different autocorrelation patterns were found. Adjacent repeated measures of daily milk yield were highest correlated (p1 = 0.32) in contrast to measures further apart, while for water intake and dry matter intake, the measurements with a lag of two units had the highest correlations with p2 = 0.11 and 0.12. The covariance structure of TOEPLITZ was most suitable to indicate the dependencies of the repeated measures for all traits. Generally, the most complex model, random regression with the additional covariance structure TOEPLITZ(4), provided the lowest information criteria. Furthermore, the model choice influenced the significance values of one fixed effect and therefore the general inference of the data analysis. Thus, the random regression + TOEPLITZ(4) model is recommended for use for the analysis of equally spaced datasets of milk yield, water intake and dry matter intake.

The aim of the study was to analyse the genetic background of different traits to characterise the maternal behaviour of sows and to evaluate the relationship to different causes of piglet losses – increasing piglet survival due to higher maternal abilities of the sow. A total of 1538 purebred litters from 943 German Landrace sows in the year 2004 were available for data analysis. Around 13 971 individually earmarked piglets were included in the analyses. Maternal abilities were characterised through the sow’s reaction to the separation from her litter during the first 24 h after farrowing, and on day 21 of lactation, the reaction towards the playback of a piglet’s distress call and the reaction towards an unknown noise (music). In 1220 of these litters, the sows were also scored for aggressiveness in the group when regrouped before entering the farrowing crates. To describe fertility, the number of piglets born alive, stillborn piglets, number of piglets born in total and the individual birth weight were utilised. Different causes of piglet losses were evaluated as binary traits of the dam with survival rate, different definitions for crushing by the sow, being underweight and runts. The heritability for being aggressive in the group was h2 = 0.32 and for the behaviour traits during lactation, the heritabilities ranged from h2 = 0.06 to 0.14. The genetic correlations showed that more-reactive sows had fewer piglet losses.

Background: Mastitis-metritis-agalactia (MMA) syndrome occurs in the first days post-partum and causes piglet losses mainly due to malnutrition. One possibility for prophylaxis of MMA is via homeopathy. In this veterinary study, the effectiveness of a prophylactic administration of homeopathic remedies for the prevention of the occurrence of MMA in swine was evaluated., Methods: In a randomised and blinded study, 60 sows were examined. Sows were randomly distributed in two groups: the experimental group (CL/LL) received a prophylactic administration of the complex homeopathic remedies Caulophyllum Logoplex and Lachesis Logoplex , and the placebo group was administered a sodium chloride (NaCl) solution in the same injection scheme as the experimental group. Clinical signs of MMA, behavioural changes, as well as production parameters, were recorded beginning with the day of farrowing until 5 days post-partum., Results: The treatment group showed no significant effect on the occurrence of MMA in sows (CL/LL: 56.67% MMA positive sows; NaCl: 53.53% MMA positive sows). Treatment group had also no significant effect on health parameters (vaginal discharge, raised rectal temperature, shortage of milk) or behavioural parameters (impaired feeding behaviour and impaired general condition). For the production parameter average weight gain, statistically significant effects in the treatment group were detected., Conclusions: Prophylaxis with the homeopathic remedies Caulophyllum Logoplex and Lachesis Logoplex showed neither an improvement in MMA prevention nor an improvement in health parameters or behavioural traits in the present herd of sows., Competing Interests: None declared., (Faculty of Homeopathy. This article is published by Thieme.)

Background: This study aimed to validate slaughterhouse indicators collected during meat inspection as an alternative to on-farm animal welfare indicators. For this purpose, the assessments of twelve on-farm and seven slaughterhouse indicators of 628 pigs from three different farms were combined into three indices, differentiated between on-farm and slaughterhouse: (1) limb health, (2) other organ health, and (3) respiratory health. At first, an assessment at animal-level using agreement parameters was carried out to ascertain whether the same welfare or health issues were identified on-farm and at slaughterhouse, taking the production period (farrowing, rearing and fattening period) and the last weeks before slaughtering into account. Second, the connection of slaughterhouse findings on the individual on-farm health indices was examined using logistic regressions, to determine whether certain welfare issues can be better monitored using slaughterhouse indicators., Results: Acceptable agreement was determined using the Prevalence-Adjusted Bias-Adjusted Kappa (PABAK) for the farrowing and fattening period, but not for the rearing period. A more detailed analysis of the weeks before slaughter shows that there is still a poor agreement 8 weeks before slaughter and an acceptable agreement 4 weeks before slaughter. This indicated the slaughterhouse indicators pneumonia, pleuritis and pericarditis as possible estimators of fever and deviant behavior on-farm and the slaughterhouse indicators bursitis and joint inflammations as possible estimators of lameness. In the second part of the analysis, the connection of slaughterhouse findings on the individual on-farm health indices was investigated; a significant influence of the farm on the limb and respiratory indices and no significant influence of the slaughterhouse findings could be determined, provided that all weekly assessments during the lifetime of the pigs have been taken into account. However, an influence of the slaughterhouse findings on the respiratory index and on the other organ index could be determined if only the weekly assessments four and eight weeks before slaughter, respectively, were taken into account., Conclusions: In general, the possible suitable indicators detected by the PABAK, could replace some health-related indicators but a complete substitution of on-farm welfare assessment is not possible. In addition, the traceability over time must be investigated further., (© 2024. The Author(s).)

Background: Tail biting is a multifactorial problem. As the health status is one of the factors commonly linked to tail biting, this study focuses on the health of identified biters. 30 (obsessive) biters are compared to 30 control animals by clinical and pathological examination as well as blood and cerebrospinal fluid samples. In that way, altogether 174 variables are compared between the groups. Moreover, connections between the variables are analysed., Results: In the clinical examination, 6 biters, but only 2 controls (P = 0.019) were noticeably agitated in the evaluation of general behaviour, while 8 controls were noticeably calmer (2 biters, P = 0.02). Biters had a lower body weight (P = 0.0007) and 13 biters had overlong bristles (4 controls, P = 0.008). In the pathological examination, 5 biters, but none of the controls had a hyperceratosis or inflammation of the pars proventricularis of the stomach (P = 0.018). However, 7 controls and only 3 biters were affected by gut inflammation (P = 0.03). In the blood sample, protein and albumin levels were below normal range for biters (protein: 51.6 g/l, albumin: 25.4 g/l), but not for controls (protein: 53.7 g/l, albumin: 27.4 g/l), (protein: P = 0.05, albumin: P = 0.02). Moreover, 14 biters, but only 8 controls had poikilocytosis (P = 0.05). Although not statistically different between groups, many animals (36/60) were affected by hypoproteinemia and hyponatremia as well as by hypokalemia (53/60) and almost all animals (58/60) had hypomagnesemia. For hypomagnesemia, significant connections with variables linked to tail damage and ear necrosis were detected (r s /V/ρ ≥ 0.4, P ≤ 0.05)., Conclusion: The results suggest that behavioural tests might be helpful in identifying biters. Moreover, cornification and inflammation of the pars proventricularis is linked to becoming a biter. Furthermore, the results highlight the need for appropriate and adjusted nutrient and mineral supply, especially with regard to magnesium., (© 2023. The Author(s).)

The "Welfare Quality protocols" (WQP) were developed in 2009 as objective welfare assessment tools. The WQP are based on four welfare principles: 1) "good feeding", 2) "good housing", 3) "good health", and 4) "appropriate behavior". The included WQP-indicators were developed for growing pigs and are recommended for rearing piglets, although, to the authors' knowledge, they have not been tested in this age class. Therefore, the present study tested selected indicators from different welfare assessment protocols with regard to test-retest reliability (TRR), consistency over time, in an on-farm study on rearing pigs. This allows to investigate whether the WQP-indicators developed for growing pigs can be recommended for rearing piglets and whether the additional indicators should be included in the WQP. In total 28 selected pen- or individual-level indicators were used by one observer to assess the animal welfare of rearing piglets on three pig farms. Per batch 40 to 125 piglets were randomly selected and individually marked to record the weekly assessments. This procedure was repeated in three consecutive batches per farm and resulted in a total of 759 rearing piglets being assessed. Spearman's rank correlation co-efficient (RS), intraclass correlation co-efficient (ICC), and limits of agreement (LoA) were calculated to evaluate their TRR, especially if the TRR was influenced by the group of assessed animals (batch comparisons) or the age of the assessed piglets (age class comparisons). From the 28 indicators, 12 had a very low prevalence of <1% making an assumption about their TRR meaningless. From the pen level indicators, "sneezing" achieved acceptable TRR for both comparisons and "behavioral observations" (BO) achieved in general good values (e.g., "positive social behavior": (RS: 0.34 to 0.89; ICC: 0.00 to 0.90; LoA ϵ [-2.93; 7.41] to ϵ [-18.9; 11.5]) for both comparisons (batch, age class). The WQP-indicators of sufficient TRR, such as "tail lesions", "lameness", "wounds on the body", "human-animal-relationship test" and "BO", cannot cover the four welfare principles adequately. In particular, problems remained with the welfare principles of "good feeding", "good housing", and partly "good health". However, these grievances could be overcome by including further indicators from other sources outside the WQP which have acceptable to good results for TRR in this study, such as "back posture", "ear lesions", "normal behavior", and "tail posture"., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

This study examined relevant variables for predicting the prevalence of pigs with a tail lesion in rearing (REA) and fattening (FAT). Tail lesions were recorded at two scoring days a week in six pens in both REA (10 batches, 840 scoring days) and FAT (5 batches, 624 scoring days). To select the variables that best explain the variation within the prevalence of pigs with a tail lesion, partial least squares regression models were used with the variable importance in projection (VIP) and regression coefficients (β) as selection criteria. In REA, five factors were extracted explaining 60.6% of the dependent variable's variance, whereas in FAT five extracted factors explained 62.4% of the dependent variable's variance. According to VIP and β, seven variables were selected in REA and six in FAT with the tail posture being the most important variable. In addition, skin lesions, treatment index in the suckling phase, water consumption (mean), activity time (mean; CV) and exhaust air rate (CV) were selected in REA. In FAT, additional musculoskeletal system issues, activity time (mean; CV) and exhaust air rate (mean; CV) were selected according to VIP and β. The selected variables indicate which variables should be collected in the stable to e.g., predict tail biting.

Since there is a practical need, this study focused on the behavior of 51 horses kept in one large group in order to make management suggestions regarding the animal:watering point ratio and the design of lying halls. Drinking events and interactions between pairs of horses were analyzed for 18 days as well as the occupancy time of the watering point. The time period had significant effects on drinking events with visible interactions (P < .05). The highest least square means (LSM) and standard errors (SE) of drinking events with and without visible interaction were observed between 12 noon-2 p.m. (13.6 ± 2.2 and 8.6 ± 1.6 drinking events, respectively) which was also the time period of main occupancy of the watering point (41.9 ± 2.7 min/2 h). About 57% of drinking events were classed as with visible interaction, of which over 90% were mild (i.e. laying back of ears, tightening of face). Horses' behavior (resting while standing/others) and lying positions (sternal/lateral) in different lying halls were analyzed over 36 days by generalized mixed models. The sternal position was preferred (12.4% ± 1.4%-39.2% ± 3.0%) compared to the lateral one (1.4% ± 0.4%-8.3% ± 1.6%). Older horses spent significantly less time in the sternal position (13.8% ± 1.6%) and rested more standing (45.4% ± 3.3%) compared to younger horses (26.4% ± 4.5% and 29.1% ± 4.9%, respectively) (P < .05). Overall, this study provides first insights into drinking and lying behavior of horses kept in a large group., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Dairy cattle housing is characterised by increasing herd sizes and the need for assisting technical tools to monitor the cows' health. This study investigated the combination of logistic regression models with multivariate cumulative sum (MCUSUM) control charts in healthmonitoring of dairy cattle. Sensor information of 618 cows with 791 lactations (138 438 cow days), nine behavioural variables were included as parts of the behavioural patterns: physical activity ("neck activity", "leg activity", "walking duration"), resting ("lying duration", "standing duration", "transitions from lying to standing") and feeding ("feeding duration", "rumination duration", "inactivity duration") behaviour. For each of these behavioural patterns, a logistic regression model with the health status (sick vs not sick) as a dependent variable was designed after a variable selection (herd level) based on the herd dataset with 618 cows (618 lactations; 115 547 cow days), which included the variables of each behaviour pattern and the stage of lactation nested in the number of lactations as explanatory variables. The explanatory variables were added stepwise to the model, with the final model being selected with respect to the lowest values of Akaike's and Bayes' information criteria. Each model was then applied to a dataset with 173 cows (22 891 cow days) at cow level, resulting in individual daily risk probabilities for getting sick. Thus, risk probabilities of each behavioural pattern were estimated and included in the MCUSUM control charts to identify cows at risk of disease. The performance of the MCUSUM control charts was cross-validated to identify the best fitting reference value k and the threshold value h. Alerts given within 5 days prior to diagnosis were counted as detected sicknesses. The performance resulted in a block sensitivity of 70.9-81.4%, specificity of 87.9-94.2% and a false-positive rate of 5.8-12.1%. The performance was confirmed while testing the entire algorithm resulting in a mean area under the receiver operating characteristics curve of 0.89. Calculating precision and the F 1 -score resulted in a precision of 49.0-60.9% (training: 48.8-63.5%) and an F 1 -score of 61.1-65.7% in testing (training: 61.0-67.0%). The precision-recall curve (PRC) was derived from precision and recall with an area under the PRC of 0.70 in training and testing. In summary, the present study was able to develop an algorithm showing good classification potential for the online monitoring of sickness behaviour., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Equine headshaking syndrome (EHS) is characterised as non-physical and involuntary movement of the horse's head and neck. Although EHS is clinically simple to diagnose, its aetiopathogenesis often remains unclear. The aim of this study was to gain an overview of signalment and therapy possibilities used in France and Switzerland. To do this, an online survey was developed and distributed via newsletters. A total of 933 complete, answered surveys from France ( n = 804) and Switzerland ( n = 129) were evaluated. The median age in France was 12.4 years (CH = 14.3). Mostly geldings were affected (58.5% FRA , 57.4% CH ). There was an association with Warmbloods in Switzerland (55.8% CH ), but in France, in addition to Warmbloods (34.4% FRA ), Thoroughbreds (27.2% FRA ) were also affected. Moreover, horses affected by EHS often show stereotypical behaviour (15.7% FRA , 14.7% CH ). A total of 38.4% FRA and 67.4% CH of horse owners utilised therapy measures, with nose covers being most commonly used (19.9% FRA , 30.2% CH ). Horse owners resorted to alternative treatments that had not previously been studied in context with EHS (15% FRA , 20.9% CH ). Conservative treatments, such as medication, were used by 5.4% CH and 1.9% FRA . This study provides an overview of the status of horses affected by EHS in France and Switzerland and thus offers a fundamental step to understanding the consequences of welfare issues associated with EHS.

The present study examined whether tail and ear postures in fattening pigs (n = 228) housed in different environments could be suitable for assessing their affective state. In doing so, it investigated the appearance of curled-up, hanging, raised, tucked-under or wagging tails, respectively, ears directed forward, backward, mixed, and laterally. The environments included a barren and two enriched habitats that offered straw-bedded pens and soil-based rooting areas for the pigs. The tail and ear postures were analyzed using the scan sampling method. At the end of fattening, the pigs in the barren environment showed significantly fewer curled-up tails than those in the enriched environment. The barren-housed pigs showed also more raised, respectively, wagging tails than the enriched-housed pigs. Particularly at the end of fattening, there were no differences concerning the ears directed forward between the two environments and significantly fewer ears directed laterally were observed in the barren than in the enriched environment. Primarily, the curled-up tails could be suitable for indicating the affective state of the fattening pigs whereas the other tail, respectively, ear postures seemed to be less suitable to represent their affective state.

The aim of this study was to analyze the utilization of different stable areas of a total of 52 group-housed horses as well as their preferred stable parts and the use of resources. The study was situated in a "HIT Active Stable ® " in Northern Germany for a period of 227 observation days. After dividing the whole farm area in a grid of 3 × 3 m, the dataset was examined with and without the pasture area. Furthermore, linear mixed models were applied. On average, horses used 53.2 ± 19 different squares per hour. The observation day ( p < 0.001) and the covariate age ( p < 0.001) had significant effects on the different squares visited per hour. No significant effects were found for sex ( p = 0.30) and breed ( p = 0.65) as only geldings and no stallions were part of the group and the distribution of the breeds was unfavorable. The random effect animal showed that the horse-individual estimates from -19.2 to 17.6 different squares visited per hour were quite large. Furthermore, it could be shown that the horses used resources such as feed stalls with a frequency of up to 0.14% more than other paddock areas without resources. Open lying halls with tarp skin were also preferred over the metal hall. The shelters were only partly popular. Use could be visualized with the help of heat maps. This study gives a good overview of the use of individual areas and resources and possible improvements.

The present observational study investigated the application of multivariate cumulative sum (MCUSUM) control charts by including variables selected by principal component analysis and partial least squares (PLS) regression to identify sickness behavior in dairy cattle. Therefore, sensor information (24 variables) was collected from 480 milking cows on a German dairy farm between September 2018 and December 2019. These variables were gathered in potentially different scenarios on farm. In total, data from 749 animals were available for evaluation. Variables were chosen based on the information of 499 cows (62 healthy; 437 sick) with 93,598 observations. The available diagnoses were collected together to form 1,025 sickness events. Hence, the different numbers of selected variables were included into the MCUSUM control charts. The performance of the MCUSUM control charts was evaluated by a 10-fold cross validation; hence, 90% of the original data set (749 cows) represented the training data, and the remaining 10% was used to test the training results. On average, the 10 training data sets included 124,871 observations with 1,392 sickness events, and the 10 testing data sets included, on average, 13,704 observations with 153 sickness events. The MCUSUM generated from the variables selected by principal component analysis showed comparable results in training and testing in all scenarios; therefore, 70.0 to 97.4% of the sickness events were detected. The false-positive rates ranged from 8.5 to 29.6%, and thus they created at least 2.6 false-positive alerts per day in testing. The variables selected by the PLS regression approach showed comparable sickness detection rates (70.0-99.9%) as well as false-positive rates (8.2-62.8%) in most scenarios. The best performing scenario produced 2.5 false-positive alerts in testing. Summarizing, both approaches showed potential for practical implementation; however, the PLS variable selection approach showed fewer false positives. Therefore, the PLS regression approach could generate a more reliable sickness detection algorithm, if combined with MCUSUM control charts, and considered for practical implementation., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The inclusion of edge weights can add valuable insights in the spreading processes within trade networks and may identify factors influencing the final epidemic size. The aim of the study was to evaluate the effect of different network versions on the outcome of an epidemiological model. The weighted network versions included the number of trade contacts (A), the sum of delivered livestock (B) and the mean number of delivered livestock per trade contact (C). Furthermore, other factors, e.g. transmission probability and farm type of primary outbreak, were tested for their impact on the final epidemic size. From 2013-2014, data from a pig trade network in Northern Germany was recorded containing 678 farms connected by 1,018 directed edges. An epidemiological model was implemented considering a higher probability of disease spread for edges with a higher weight for each of the combinations between network version and transmission probability. Only transmission routes following the network structure were considered for disease transmission. The outcome of the epidemiological model (number of infected farms) was tested with a generalized linear mixed model including the fixed effects network version (unweighted, A, B, C), transmission probability and farm type of primary outbreak (breeding farm, farrowing farm, finishing farm, farrow-to-finishing farm, unknown) as well as all twofold interactions. The results revealed that all fixed effects as well as all twofold interactions were significant (p ≤ 0.05), i.e. in the following only the impact of the interactions on the number of infected farms can be interpreted. Network versions B and C showed in all combinations the highest number of infected farms independent of the underlying transmission probability. The unweighted network and network version A showed a significant increase of infected farms with increasing transmission probability. All interactions including the farm type of primary outbreak revealed a significant higher number of infected farms for farm types located at the beginning of the production chain, e.g. breeding farms. These farm types reached also more other farms in 1-4 steps compared to farm types located near to the end of the production chain. The inclusion of edge weights has a significant effect on the outcome of epidemiological models and dependent on the chosen edge weight the results need to be interpreted accordingly., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Comprehensive identification of on-farm animal-health issues still requires extensive efforts so that in practice such monitoring is applied only sparsely. An appealing approach to improve on-farm animal health and welfare monitoring is the application of organ lesion scoring data from the abattoir as such is instantly available for every commercial farm in Europe. Unfortunately, it is also well-known that organ lesion scoring is often unreliable because results are altered by several non-health-related factors, diluting the validity of lesion scoring prevalence as a proxy for on-farm animal health. However, it is theoretically possible to improve prevalence reliability a-posteriori by application of time-series smoothing. The aim of this paper was therefore to analyse whether it is practically possible to increase apparent prevalence estimation reliability retrospectively using a running average, and, if so, which window length and smallest sample size should be preferred in such an approach. Because no gold standard for direct evaluation of lesion reliability is available for field-data, apparent prevalence reliability had to be approximated using prevalence agreement over time. Results indicate that by raising the number of lesion scores per prevalence estimate, apparent prevalence agreement over time can in general be considerably increased. Based on findings presented, a reasonable threshold for prevalence estimation is given by at least n = 50 lesions per farm/abattoir/time-series segment. Results further suggest that it is necessary to consider differences in prevalence sample size for future monitoring purposes, because prevalences that are estimated on a continuum of different sample sizes put together in one evaluation may induce substantial error in prevalence estimates., (Copyright © 2021 Elsevier B.V. All rights reserved.)

With increasing herd sizes came an enhanced requirement for automated systems to support the farmers in the monitoring of the health and welfare status of their livestock. Cattle are a highly sociable species, and the herd structure has important impact on the animal welfare. As the behaviour of the animals and their social interactions can be influenced by the presence of a human observer, a camera based system that automatically detects the animals would be beneficial to analyse dairy cattle herd activity. In the present study, eight surveillance cameras were mounted above the barn area of a group of thirty-six lactating Holstein Friesian dairy cows at the Chamber of Agriculture in Futterkamp in Northern Germany. With Mask R-CNN, a state-of-the-art model of convolutional neural networks was trained to determine pixel level segmentation masks for the cows in the video material. The model was pre-trained on the Microsoft common objects in the context data set, and transfer learning was carried out on annotated image material from the recordings as training data set. In addition, the relationship between the size of the used training data set and the performance on the model after transfer learning was analysed. The trained model achieved averaged precision (Intersection over union, IOU = 0.5) 91% and 85% for the detection of bounding boxes and segmentation masks of the cows, respectively, thereby laying a solid technical basis for an automated analysis of herd activity and the use of resources in loose-housing.

Equine headshaking syndrome is a problematic behavior that has been described in literature for more than 100 years. The signs of headshaking syndrome appear frequently and violently so that riding the horse can be dangerous. The aim of this research was to gain an overview of the underlying causes of equine headshaking syndrome to identify effective treatment options, reduce the distress of horses and, in a second step, potentially improve therapeutic possibilities for horse owners and veterinarians. Most studies on prevalence originate from Anglo-American countries, so this research was to provide an overview of German horses; therefore, an online survey was designed by experts in the field (researchers and veterinarians) and answered by German horse owners. Questionnaires were pretested by a small group of horse owners (n = 5) and redesigned accordingly. The final questionnaire consisted of 27 questions, which were divided into seven open questions with an associated text field and 20 multiple-choice questions (Supplementary Material 1). For some of the multiple-choice questions, multiple answers were permitted. In total, 163 completed questionnaires were obtained from owners of headshaking horses (n total  = 163). Gender distribution of the horses resulted in 64.4% geldings, 33.7% mares, and 1.8% stallions. Most horses were German warmbloods (55.4%). The average age was 12.7 years (with a wide range of 5 to 34 years). The vertical movement of the head was the most frequently mentioned symptom in 75.5% of the evaluated horses. In 18.4% of the cases, the horse owners identified stress as the main trigger for headshaking. Furthermore, 18.4% claimed that their horses suffered from additional stereotypical behavior. The percentages do not refer to the same horses here. 11.0% of the participants in this study tried scientifically evaluated therapies such as surgical therapy (1.2%) or medical treatment (9.8%). In addition, 54.0% of the owners utilized a nose cover to reduce the symptoms of the headshaking syndrome. A high percentage of 84.0% used alternative therapies such as physiotherapy (31.9%), change of equipment (22.7%), or change of riding style (29.4%). Overall, this study provides a useful overview of causes and effective therapies., (Copyright © 2020 Elsevier Inc. All rights reserved.)