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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 - 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 coefficient (RS), intraclass correlation coefficient (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”.

Consistency over time is a basic requirement for welfare assessment schemes since consistency must not depend, for example, on the day it is carried out. This study analysed the consistency of the indicators of the Animal Welfare Indicators (AWIN) protocol for horses (Equus caballus) over time. Given the multi-dimensionality of animal welfare, the AWIN protocol includes a variety of indicators evaluating, eg the health status or the behaviour of the animals. Fourteen establishments keeping horses in Germany were visited four times each (day 0, day 3, day 42, day 90). For the evaluation of reliability and agreement between the different visits, ie across time, the reference visit on day 0 was compared to the other visits via calculation of Spearman's rank correlation (RS), intra-class correlation (ICC), smallest detectable change (SDC) and limits of agreement (LoA). The indicator, Qualitative Behaviour Assessment (QBA) was analysed by Principal Component Analysis (PCA). Most of the indicators demonstrated sufficient consistency over time. Indicators that were inconsistent included parts of the Horse Grimace Scale, outcomes of behavioural tests, the presence of swollen joints as well as the indicators hoof neglect, alopecia on the legs and water cleanliness. The QBA was consistent for the period of 42 days, but not for 90 days. Overall, those indicators with insufficient consistency over time require to be revised or replaced in future welfare assessment schemes.

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 assess the interobserver reliability of the measures forming the Welfare Quality® animal welfare assessment protocol for sows and piglets. The study was carried out at nine farms in Northern Germany. Two trained observers evaluated identical animals simultaneously but independently in 40 joint farm visits. Interobserver reliability was calculated at individual animal level using Cohen's kappa, weighted kappa and the prevalence-adjusted, bias-adjusted kappa (PABAK) and at farm level using Spearman's rank correlation coefficient (RS), the intraclass correlation coefficient (ICC), smallest detectable change (SDC) and limits of agreement (LoA). While a direct comparison of the adjectives of the qualitative behaviour assessment showed poor interobserver reliability, a Principal Component Analysis detected good interobserver reliability. The assessment of social and exploratory behaviours showed acceptable interobserver reliability, while the assessment of stereotypies displayed good interobserver reliability. The human-animal relationship test showed only poor interobserver reliability at individual animal and farm levels. In most cases, measures of health and physical state assessed in sows and piglets exhibited acceptable or good interobserver reliability. In conclusion, after some measures are revised, particularly those examining the human-animal relationship, the Welfare Quality® protocol for sows and piglets will represent a reliable approach in terms of interobserver reliability to assess the welfare of sows and piglets.

Multi-criteria decision analysis deals with decision problems in which multiple criteria need to be considered. The criteria might be measured on different scales so that comparability is difficult. One approach to help the user to organize the problem and to reflect on his or her assessment on the decision is Measuring Attractiveness by a Categorical Based Evaluation TecHnique (MACBETH). Here the user needs to provide qualitative judgment about differences of attractiveness regarding pairs of options. MACBETH was implemented in the M-MACBETH software using the additive aggregation model. The present article introduces the software tool “AniFair” which combines the MACBETH approach with the Choquet integral as an aggregation function, because the Choquet integral enables the modeling of interaction between criteria. With the Choquet integral, the user can define constraints on the relative importance of criteria (Shapley value) and the interaction between criteria. In contrast to M-MACBETH, with every instance of “AniFair” the user is made available at least two aggregation level. “AniFair” provides Graphical User Interfaces for the entering of information. The software tool is introduced via an example from the Welfare Quality Assessment protocol for pigs. With this, “AniFair” is applied to real data that were collected from thirteen farms in Northern Germany by an animal welfare expert. The “AniFair” results enabled a division of the farms into five groups of comparable performance concerning the welfare principle “Good feeding”. Hereby, the results differed in how much the interaction between criteria contributed to the Choquet integral values. The shares varied from 5% to 55%. With this, the vulnerability of aggregation results towards relative importance of and interaction between criteria was stressed, as changes in the ranking due to the definition of constraints could be shown. All results were exported to human readable txt or csv files for further analyses, and advice could be given to the farmers on how to improve their welfare situation.

Behavioural tests might have the potential to evaluate certain aspects of welfare such as emotional state or the human-animal relationship. However, reliability assessments of these tests are rare. Therefore, in this study, different behavioural tests for growing pigs were assessed regarding their on-farm reliability. Eleven growing pig farms were visited three times each by two experienced observers. The farm visits took place with a time interval of one week in between the first and the second farm visits and a time interval of four weeks in between the first and the third farm visits, i.e. the second and the third farm visits were three weeks apart. During the second farm visit, exactly the same animals were tested while at the third farm visit, other animals were tested. The observers carried out a Novel object test (NOT), a Voluntary human approach test (VHAT), a Forced human approach test (FHAT) and a Human-Animal Relationship Test (HART) at group level in the home pen of the pigs. The results of the different farm visits and observers, respectively, were compared by a combination of statistical parameters: Spearman’s rank correlation coefficient (RS), intraclass correlation coefficient (ICC), limits of agreement (LoA) and smallest detectable change (SDC). The interobserver reliability was in general acceptable for all tests (e.g. NOT: RS: 0.50, ICC: 0.56, SDC: 2.47, LoA: −2.49–2.28) to good (e.g. FHAT: RS: 0.98, ICC: 0.98, SDC: 0.23, LoA: −0.22–0.25). The test-retest reliability, on the contrary, was rather insufficient: only in the comparison of the first to the second farm visits did RS and ICC reach values of ≥0.40 for the FHAT and HART (for some categories). However, the deviation between the two observers detected by SDC and LoA were above 10%. No reliability was detected for the other two comparisons as well as for all comparisons of the NOT and VHAT, (e.g. VHAT, first to second farm visit: RS: 0.15, ICC: 0.04, SDC: 30.2, LoA: −24.5–38.6). Thus, it can be concluded that interobserver reliability was sufficient, while in the form of these behavioural tests used consistency over time at the moment remains insufficient. Hence, with regard to welfare assessment schemes, this aspect must be taken into account and future work should concentrate on recategorisation, enhancement of knowledge concerning the validity of these tests in different settings as well as possible alternatives. Nevertheless, the good interobserver reliability points out a potential usefulness of these tests for other purposes i.e. whether the animals need to be tested only once throughout their lives.

Objective tools for the assessment of animal welfare are needed. The present study analyzed the interobserver reliability of the Animal Welfare Indicators (AWIN) welfare assessment protocol for horses to further enhance knowledge concerning reliability. Therefore, two trained observers conducted 18 assessments on farm at the same time and on the same animals. The results were compared at individual level by calculation of Cohen's kappa (κ), weighted kappa (κw), and prevalence-adjusted, bias-adjusted kappa (PABAK). Spearman rank correlation coefficient (RS), intraclass correlation coefficient (ICC), limits of agreement (LoA), and smallest detectable change (SDC) were used at farm level. The Qualitative Behaviour Assessment was further analyzed by means of principal component analysis. At the individual level, most of the indicators demonstrated acceptable (κ, κw, PABAK ≥ 0.4) to good (κ, κw, PABAK ≥ 0.6) interobserver reliability. Also, at farm level, most of the indicators demonstrated acceptable (RS ≥ 0.4; ICC ≥ 0.4; SDC: ≤ 0.1; LoA e [0.1; 0.1]) to good (RS: ≥ 0.7; ICC: ≥ 0.7; SDC: ≤ 0.05; LoA: e [0.05; 0.05]) interobserver reliability. Exceptions were the indicators moderate presence of tension above eye area (score 1) and orbital tightening (score 1) on the Horse Grimace Scale, as well as the presence of swollen joints. Furthermore, the present results indicate that the details for the different scores should be improved for some indicators such as the Body Condition Score. In general, this study points out a good interobserver reliability of the AWIN welfare assessment protocol for horses.

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.

Simple Summary Many studies are working with GPS sensors to track farm animals in order to gather information related to the animals’ health, the use of space and resources provided to the animals or their social contacts. When a herd of animals is tracked uninterruptedly, a huge amount of data is generated. Furthermore, problems like the limited battery life of wireless sensors have to be dealt with. This article presents the software “HerdGPS-Preprocessor” for the preparation of GPS data collected from an animal herd. The GPS data is provided cleaned and organized, such that the output files enable direct statistical analysis. Additionally, contact lists are output to enable network analyses. This study also delivers an example analysis with the “HerdGPS-Preprocessor”, in which GPS data of forty horses kept in a loose-housing barn were used to visualise and analyse contact networks. From the calculation of network parameters (density, diameter) and metrics associated to the clique structure of the horses, resting and activity phases could be distinguished. Furthermore, by network analysis it was shown that pasture opening and the visiting times of horse owners affect the contact structure. Thus, “HerdGPS-Preprocessor” is a valuable tool in studies collecting GPS data from herd animals. Abstract Sensors delivering information on the position of farm animals have been widely used in precision livestock farming. Global Positioning System (GPS) sensors are already known from applications in military, private and commercial environments, and their application in animal science is increasing. However, as trade-offs between sensor cost, battery life and sensor weight have to be made, GPS based studies scheduling long data collection periods and including a high number of animals, have to deal with problems like high hardware costs and data disruption during recharging of sensors. Furthermore, human–animal interaction due to sensor changing at the end of battery life interferes with the animal behaviour under analysis. The present study thus proposes a setting to deal with these challenges and offers the software tool “HerdGPS-Preprocessor”, because collecting position data from multiple animals nonstop for several weeks produces a high amount of raw data which needs to be sorted, preprocessed and provided in a suitable format per animal and day. The software tool “HerdGPS-Preprocessor” additionally outputs contact lists to enable a straight analysis of animal contacts. The software tool was exemplarily deployed for one month of daily and continuous GPS data of 40 horses in a loose-housing boarding facility in northern Germany. Contact lists were used to generate separate networks for every hour, which are then analysed with regard to the network parameter density, diameter and clique structure. Differences depending on the day and the day time could be observed. More dense networks with more and larger cliques were determined in the hours prior to the opening of additional pasture.

The present study’s aim was to test a German guideline for farm’s self-monitoring in sows and piglets for its feasibility as well as its interobserver and test–retest reliability. The study was performed between September 2016 and April 2018 on 13 farrowing farms in Northern Germany. Contrary to the guideline, the testing was not carried out by the farmers themselves but by 2 observers with experience in pigs representing common farmers. For the interobserver reliability study, the observers performed 20 joint farm visits independently assessing the same animals. For the test–retest reliability study, each farm was visited 5 times by 1 observer (day 0, day 3, week 7, month 5, month 10). Farm visit 1 (day 0) was used as reference and compared with the remaining farm visits. The reliability was evaluated using Spearman’s rank correlation coefficient (RS), intraclass correlation coefficient (ICC), and limits of agreement (LoA). As results, the guideline’s feasibility was limited. The indicators’ reliability also presented divergent results: All indicators in piglets revealed acceptable to good interobserver reliability (RS 0.64 to 0.77 ICC 0.33 to 0.48 LoA between the intervals −0.02 to 0.13 and −0.02 to 0.00). Contrarily, interobserver reliability was low for indicators in sows (e.g., claw alterations: RS −0.41 ICC 0.00 LoA −0.97 to 0.68). Overall acceptable test–retest reliability could be assigned to all indicators although no exact agreement existed but only the pursuit of trends is indicated. On the basis of the present results, the guideline in its present form cannot be recommended for farms’ self-monitoring. Given the restricted applicability, it should be reconsidered whether it might not be more appropriate to use scientifically tested and generally accepted animal welfare assessment systems such as the Welfare Quality animal welfare assessment protocols, although their application is also time-consuming.

The present study aimed at testing the feasibility and on-farm test–retest reliability of the Welfare Quality Assessment protocol for pigs applied to sows and piglets. The study was conducted on 13 farms in Northern Germany, which were visited 5 times by the same observer, and included 2 experimental setups: first, the complete Welfare Quality Assessment protocol for sows and piglets was applied to the farms. Second, additional assessments in the gestation unit considered all sows. The complete protocol assessments were used to evaluate the feasibility of the protocol. Furthermore, the data were analyzed with regard to on-farm test–retest reliability. The present publication focuses on the Welfare Quality principles good feeding, good housing, and good health, which are based on individual indicators (IN). The second experimental setup was utilized to verify the test–retest reliability of IN in the gestation unit with an increased number of animals under assessment. The test–retest reliability was calculated using Spearman’s rank correlation coefficient (RS), intraclass correlation coefficient (ICC), smallest detectable change (SDC), and limits of agreement (LoA). Farm visit 1 (F1; day 0) was set as a reference and compared with farm visits 2 to 5 (F2 to 5; day 3, week 7, month 5, month 10). The IN of the above-named Welfare Quality principles achieved mostly acceptable test–retest reliability (e.g., wounds on the body F1 to F4: RS 0.34 to 0.57, ICC 0.40 to 0.41, SDC 0.02 to 0.12, LoA [−0.03; 0.02] to [−0.09; 0.14]) in terms of the on-farm test–retest reliability. Poor test–retest reliability was detected for body condition score concerning the principle good feeding, for bursitis and panting in sows and for huddling and panting in piglets within the principle good housing, and finally for vulva lesions, metritis, and local infections in sows and for scouring and lameness in piglets in the principle good health. Variations among the farm visits, which resulted in poor test–retest reliability, may be explained by seasonal effects (panting), moving animals (bursitis, lameness, huddling), rare occurrences of diseases (metritis, local infections, scouring), and differently conditioned sow groups (body condition score). The second experimental setup confirmed the results for IN in the gestation unit. Thus, the reported test–retest reliability determines the Welfare Quality Assessment protocol for sows and piglets to be a reliable approach to assess welfare in sows and piglets.

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 (ntotal = 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.

Optimization of production factors plays a central role in efficient milk production operations. Causal relationships between production parameters (health, fertility, feeding, performance and farm size) on the one hand and efficiency parameters on the other have been identified in several studies. In recent years, structural equation modelling (SEM) has not only gained importance in agriculture but also in milk production, providing the opportunity to investigate multilateral relationships. Additionally, SEM enables an estimation of parameters which are not themselves measurable, the so-called latent variables. The current study was based on the data of 943 branch settlements (including the years 2012 and 2013) of dairy farms keeping German Holstein cows in Schleswig-Holstein (Northern Germany) which provided a combination of the structural parameters, economic parameters and biological performance of the farms. An SEM using this combined data was applied to investigate the complexity of influences on efficiency parameters in milk production. Efficiency was sub-divided into and evaluated by two effect variables (economic efficiency and biological efficiency). Economic efficiency was defined as a conventional efficiency assessment criterion from full-cost accounting, whereas biological efficiency was used to evaluate the quality of herd management. Performance was identified as the key parameter for independent evaluation of efficiency by assessing biological (γ41 = 0.644) or economic efficiency (γ42 = 0.266). The SEM explained more than three times higher proportion of the variance in biological efficiency than in economic efficiency. The investigation proved the eligibility of partial least squares SEM for the evaluation of efficiency in milk production.

Tail biting in pigs is a serious welfare problem with multifactorial causes. Several risk factors are described in the literature ranging from environmental factors including stocking densities, deficiencies in feed quality or accessibility, to internal factors such as poor health status, genetics or sex. Also, the human–animal relationship can have an effect on behaviour and performance of the animals. Thus, the aim of the current study was to evaluate whether intensified human–animal interaction in the rearing period can reduce the occurrence of tail biting in weaned piglets. For this, two treatment groups were established. The trial group differed only in intensified human–animal interaction (e.g. calm speech, petting, food provision) from the control group, which was carried out three times a week by one person for 15 min in each pen. Once a week the animals’ tails were scored regarding tail lesions and losses and a human approach test was performed. The intensified human–animal interaction influenced the animals’ behaviour towards the human as well as towards their pen mates. The trial group showed significantly better results compared with the control group, i.e. fewer tail lesions and more animals with intact tails. Also, the results of the human approach test in the trial group showed a lower latency to approach compared with the control group. Thus, integration of an intensified human–animal interaction into the daily practice of pig farms could be one possibility for enhancing the human–animal relationship and reducing occurrence of tail biting.

The aim of this study was to determine the most suitable and practical definition of spatial and temporal proximities between grouped-housed horses by comparing GPS position data. In total, 43 horses held in a “HIT Active Stable®” were equipped with GPS loggers. Different definitions of spatial (≤ 1, 2, 3, 4, 5 m) and temporal proximity (≤ 10, 30, 60, 90, 120 s interruptions between recording points) were investigated for morning pasture periods of 30 days analyzing proximity lengths, number of proximities as well as the network parameters density and fragmentation. With increasing spatial proximity definition, the duration of proximities rose from 9 % (4 compared to 5 m) to 76 % (1 compared to 2 m). The number of proximities also increased accordingly. Ascending temporal proximity definitions provided a lower number of proximities by 13–21 % (10 s to 30 s) depending on the spatial definition and the proximities became longer. Further, with higher spatial proximity definition, the network density ascended and fragmentation decreased, which shows that more horses had proximities and group formation occurred. We identified a proximity definition of 3 m for at least 60 s as the most useful solution because of a decreasing change in proximity length and number due to biological and technical restrictions. Further, it is suspected that this approach helps to better characterize the group formation of horses kept in groups.

Positive emotions constitute a very important part of animal welfare. They are, however, also the most challenging elements to be objectively measured. Due to its feasibility, the qualitative behavior assessment (QBA) is included in the Welfare Quality Assessment protocol for growing pigs as the animal-based measurement tool for positive emotions. Reliability testing on the QBA in the form as included in the protocols is, however, rare. Therefore, the present study aimed at the evaluation of the inter- and intraobserver as well as test-retest reliability of the QBA in growing pigs. This was done by trained observers based on 19 joint on-farm assessments, the repeated assessments of 24 farms during 2 growing periods, and 107 video sequences. The results were compared between the observers and the repeated farm visits. Therefore, millimeter values were directly compared by calculation of Spearman's rank correlation coefficients (RS), and furthermore, the results were subjected to a principal component analysis (PCA). The results identified 2 main principal components (PC; PC1 and PC2) together explaining from 42 to 75% of the variation in the recorded variables of the different PCA. The factor loadings that the adjectives reached on PC1 and PC2 were compared by calculation of RS between observers and farm visits, respectively. Reliability was interpreted as acceptable if at least a moderate correlation was detected; that is, RS was greater than or equal to 0.4. Regarding the on-farm assessments, and, therefore, under practical conditions, no sufficient interobserver reliability (RS = -0.16 for PC1 and RS = 0.13 for PC2) was found. In terms of the test-retest reliability, only 1 comparison of 2 farm visits showed a positive correlation for PC1 (RS = 0.79) as well as for PC2 (RS = 0.64). The other 5 comparisons presented negative to weak positive correlations. However, based on video sequences, good interobserver (RS = 0.67 for PC1 and RS = 0.60 for PC2) and intraobserver (RS = 0.94 for PC1 and RS = 0.44 for PC2) reliability was achieved. Therefore, the present study revealed good reliability for the QBA in the form as it is currently included in the Welfare Quality Assessment protocol for growing pigs based on video sequences but insufficient reliability for the application on the farm.

Several studies have used behavioural tests to characterise sows regarding their maternal performance. These studies have always chosen a selection of behavioural tests and the combination of tests varied between the studies. In the present study, 47 sows were tested in week 2 and 4 of lactation in five successive maternal tests, which were conducted in their home pens and in a test arena. The sows’ reaction to piglet stress signals, separation from and reunion with their piglets were tested. The behavioural parameters observed in these maternal tests were examined by means of a factor analysis to identify redundancies in behavioural parameters. Five factors were extracted, explaining together 89.2 % of the total variance, of which Factor 1 explains 33.5 %, Factor 2 18.4 %, Factor 3 14.5 %, Factor 4 12.6 % and Factor 5 10.2 %. The interpretation of the factor loadings revealed four underlying maternal factors: communication, care, contact and local attachment. Communication, thus vocalisation, was extracted by the factor analysis as the most important maternal factor and is used in sows to call their piglets in threatening situations as in the separation test and the piglet scream test. Furthermore, communication plays a role for the maternal contact and care factors. Sows used vocalisation to contact their piglets using nose-to-nose contacts, which were observed in the reunion test and also in the piglet scream test. With regard to the care factor, sows use vocalisation to call their piglets for nursing and to synchronise nursing with other sows. The willingness to stay with their piglets, thus local attachment to their piglets, was shown by sows in the separation and reunion test in the test arena and the piglet scream test. Furthermore, the factor analysis proves that single maternal tests can also combine more than one maternal factor and that the experimental environment in which the tests are placed influences the significance of the tests. The present results demonstrate the complexity and diversity of maternal behaviour.

This study analyses tail and ear postures of growing pigs in two different housing systems throughout the growing period. On one farm, 168 undocked pigs (84: barren housing, 84: enriched housing) were observed individually at three time periods: beginning, middle and end of the growing period. By scan sampling, the tail (curled-up, raised, hanging, tucked under, wagging) and ear posture (forwards, sidewards, backwards, mixed) was noted. Scans were performed hourly during the activity periods by direct observation. Moreover, the body posture (standing, feeding, lying (eyes open), lying (eyes closed) and tail lesions were noted. Data were analysed using the GLIMMIX procedure in SAS. Results revealed significant differences between the enriched and barren group especially for curled-up tails, tucked under tails and ears directed forwards. More curled-up tails and ears directed forwards occurred in the enriched and more tucked under tails in the barren habitat. The time period of observation also had significant influences. Tail lesions had significant effects on most tail postures. Most ear postures were influenced by the body posture of the pigs. Overall, this study contributes to the understanding of body language, specifically tail and ear postures in pigs.

The aim of the present study was to investigate whether the primarily positive affective state of fattening pigs influences various behavioral and physiological parameters such as the pigs’ playing behavior, way of behaving in behavioral tests, body language signals, or diameter, and astroglia cell numbers of hippocampi, salivary immunoglobulin A (IgA) content, or salivary protein composition. Additionally, the suitability of the variables mentioned was examined to assess the pigs’ positive affective state in practice, which still constitutes a latent variable not itself measurable. For this, a dataset including behavioral and physiological data of 60 fattening pigs from 3 different farms with different housing systems was analyzed by the partial least squares structural equation modeling (PLS-SEM) method. A hierarchical component model (HCM) was used including the pigs’ positive affective state as a higher-order component (HOC) and the behavioral and physiological parameters as lower-order components (LOC). Playing behavior, body language signals, and behavioral tests were revealed, in this order, to be most influenced by the pigs’ positive affective state since these resulted in the corresponding path coefficients (PC) of PC = 0.83, PC = 0.79, and PC = 0.62, respectively. Additionally moderate and weak R2-values occurred for the endogenous latent variables playing behavior (R2 = 69.8%), body language signals (R2 = 62.7%), and behavioral tests (R2 = 39.5%). Furthermore, the indicator of the “locomotor play” showed the highest indicator reliability (IR) (IR = 0.85) to estimate the latent variable of pigs’ positive affective state. The results of the present study supplement the comprehension and assessment of the pigs’ positive affective state in general.

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.

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.

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 study was to assess the feasibility and test-retest reliability of the Welfare Quality® Animal Welfare Assessment Protocol for Growing Pigs. Twenty-three German pig farms were visited repeatedly by the same trained observers; each farm being visited six times during two fattening periods. The entire protocol assessment was carried out during each farm visit, ie a Qualitative Behaviour Assessment (QBA), behavioural observations (BO), a Human Animal Relationship test (HAR) and different individual parameters (IPs), eg bursitis and tail-biting. Test-retest reliability was evaluated by a Wilcoxon signed rank test (W) and by calculation of the Smallest Detectable Change (SDC) and Limits of Agreement (LoA). The QBA presented non-satisfactory agreement between farm visits. However, good agreement, in general, was found for the BO. For the HAR, no reliability could be detected. Most IPs were of acceptable agreement, with the exception of bursitis and manure on the body. Bursitis showed great differences, which can be explained by difficulties in the assessment when the animals moved around or their legs were dirty. The disagreement in the parameter manure on the body can be explained by seasonal effects. Disagreement was further found concerning the parameters coughing, sneezing, pleuritis, pneumonia and milkspots. Feasibility was good; both observers could be well-trained to fulfil the protocol. Furthermore, the time needed for an assessment did not exceed 6 h. The parts of the protocol that proved to be insufficiently reliable need to be addressed in the future in order to enhance and improve the objective measurement of animal welfare.

Group housing is claimed to possibly provide horses with a species-appropriate movement possibility, and hence, better welfare. Thus, this study analyzed the daily walked distances of 51 horses held in one group in a "HIT Active Stable" (Hinrichs Innovation + Technik) in Northern Germany by using global positioning system (GPS) technology during a 7 ½-month time span. The daily walking distances of the whole group, as well as newcomers, were investigated. The horses traveled an average of 8.43 km/day. Linear mixed models were applied. The observation day had a significant effect on the daily walking distances (P.01) due to season and the available area per horse. The age as covariate also had a significant effect (P.01). The breed had no significant effect (P = .96). No significant differences were found in sex (P = .69), which can be explained by the fact that only mares and geldings were investigated, which do not show increasing locomotion caused by sexual behavior as stallions do. On six of the first nine days, new horses moved significantly more compared to the remaining 24 of the 30 observation days directly after individuals' inclusion. This is probably due to more exploration and rank-fighting behavior. Similar walking distances were seen among the horses on the single observation days because all horses had to travel the same distance to reach resources. Further, it is suspected that not all horses can sufficiently live out their urges to move, especially in winter, when pasture is inaccessible.

Recently, consumers concerns towards an environmental friendly food production are growing. The dairy sector contributes to the production of important greenhouse gases such as methane. The life cycle assessment (LCA) method enables to quantify the emissions and the use of resources throughout the entire life cycle of a product. The aim of the current study was to investigate the influence of performance parameters on the level of important environmental impacts (global warming potential (GWP), freshwater eutrophication (FE), terrestrial acidification (TA) and agricultural land occupation (ALO)) associated with milk production. Therein, the environmental impacts were analyzed using LCA considering two separate datasets (total, continuous) from Northern German farms throughout the years 2004-2013. Therefore, the performance parameters determining the level of environmental impacts were identified using the partial least square method. Thereby, a differentiated analysis among regions with various soil characteristics (Heath, Hill, Marsh) was conducted additionally. Further, linear mixed models were applied to each of the environmental impact categories. Energy-corrected milk yield (ECM), ECM from roughage, feed efficiency and the use of concentrates were identified as the most important determinants of environmental impacts. In general, an increase in productivity, especially an increase in ECM per cow and an increase in the amount of ECM produced per area of agricultural land accompanied with an improvement in environmental efficiency. The type of feed used had the major impact on the level of environmental impacts, whereby both concentrates and roughage had disadvantages. These results were in line with previous studies. Although, this study provides additional information relating the most important determinants of different environmental impacts, including a differentiated consideration of the relationship between performance parameters and environmental efficiency among regions. Further analyses on specific soil characteristics and their impact on environmental efficiency are recommended. In line with the concept of eco-efficiency, useful mitigation strategies in practice need to be applied depending on individual framework conditions.

This study identifies iceberg indicators for welfare assessment in sows and piglets to enhance feasibility and sustainability of available protocols. Indicators of the Welfare Quality&reg, protocol and of a German protocol were collected over 65 farm visits to 13 farms in Germany between September 2016 and April 2018. Data were analysed using partial least square structural equation modelling (PLS-SEM). A hierarchical component model was built (animal welfare = higher-order, Welfare Quality&reg, principles = lower-order components). In sows, welfare was revealed to be most influenced by the principles good housing, good health and appropriate behaviour (path coefficients = 0.77, 0.86, 0.91). High coefficients of determination R&sup2, indicated a large amount of explained variance (good housing R&sup2, = 0.59, good health R&sup2, = 0.75, appropriate behaviour R&sup2, = 0.83). Stereotypies was the indicator most valuable to assess sow welfare. Additionally, the final model included the indicators panting, shoulder sores, metritis, mortality and an indicator assessing stereotypies in resting animals (indicator reliabilities 0.54&ndash, 0.88). However, the model did not include the indicators lameness and body condition, which may be due to the farm sample. Welfare of piglets was most explained by the indicators carpal joint lesions, mortality, sneezing and undersized animals (indicator reliabilities 0.48&ndash, 0.86).

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.

In commercial pig production, the mixing of unacquainted pigs is a standard procedure which leads to agonistic interactions with a wide range of individual pig behaviour. A reduction in these agonistic interactions positively affects animal health, welfare aspects and production parameters. With the help of social network analysis, insight into animal societies can be gained and structures of agonistic behaviour can be detected. The aim of the present study was to analyse how the general network properties (density, clustering coefficient, weakly and strongly connected components and centralisation) develop over three different rehousing and mixing events (weaned pigs, growing pigs and gilts). Therefore, the agonistic behaviour of the animals in the flatdeck pens, the growing and the breeding stables were recorded directly after mixing (in total 17 h of video observation for each pen). In total, 65 groups in the rearing area (flatdeck pens), 24 groups in the growing stable and 12 groups in the breeding stable were recorded. In contrast to the second and the third rehousing and mixing events, the results for the density and the clustering coefficient showed that in the agonistic interaction networks of the first mixing event the animals were very densely connected and therefore formed highly connected clusters, indicating that nearly all animals in a pen fought against each other during the observation period. The results for the weakly and strongly connected components suggest that agonistic interactions have a group-wide structure which is not immediately obvious in a dyadic analysis. Furthermore, the in-degree centralisation showed significantly smaller values than the out-degree centralisation at all three observed age levels, which suggests that the distribution of individuals initiating agonistic interactions was more skewed than the distribution of individuals receiving agonistic interactions. By quantifying the important aspects of group structure in different production stages, information based on social network analysis could help identify and understand the formation of behavioural patterns, e.g. agonistic interactions, tail biting and access to resources.

Previous studies showed that depending on different factors, such as age, level of familiarity or group size, the number of agonistic interactions in pigs directly after mixing can demonstrate a large variation: from groups which reveal a clear decline in agonistic interactions one day after mixing to groups with highly temporal fluctuations even four days after mixing. Information of these agonistic interactions is often used to calculate dominance indices and is the basis to construct social networks. However, in order to get information about won and lost fights or about the initiator and the receiver of an agonistic interaction, these parameters rely on direct and continuous video observation. Video analysis is, however, very time-consuming, but provides the most accurate results as it measures directly the agonistic behaviour. Thus, the aim of the present study was to investigate the temporal development of agonistic interactions directly after mixing for weaned piglets, growing pigs and gilts. Furthermore, we evaluated the impact of the above described temporal variations on dominance indices as well as on social network parameters. This information is important to determine the most appropriate time span to obtain stable results for dominance indices as well as parameters derived from social network analysis. The results for growing pigs and gilts revealed a significant decrease from 0.6 to 0.2 agonistic interactions/animal/hour one day after mixing (6 h of video observation) (p

The present study aimed at introducing a reliable and more feasible indicator to evaluate stereotypies in sows in comparison with the ‘Welfare Quality® animal welfare assessment protocol for sows and piglets’. Therefore, the indicators for the assessment of stereotypies of the Welfare Quality® protocol for sows and piglets as the gold standard (sham chewing, tongue rolling, teeth grinding, bar, drinker, trough biting and floor licking) were tested in relation to the potential indicator ‘frothy saliva’ in an on-farm study on farrowing farms. The analysis included the correlation between indicators, their interobserver agreement and test-retest reliability. Therefore, Spearman’s rank correlation coefficient (RS), intraclass correlation coefficient (ICC), smallest detectable change (SDC) and limits of agreement (LoA) were used. As results, the potential indicator ‘frothy saliva’ showed an acceptable correlation with the most observed indicator sham chewing (RS 0.42), which was in turn correlated to the indicator tongue rolling (RS 0.35). ‘Frothy saliva’ showed similar interobserver agreement as the indicators for the assessment of stereotypies, e.g. ‘frothy saliva’ (RS 0.90 ICC 0.93 SDC 0.16 LoA [−0.18;0.14]) and sham chewing (RS 0.96 ICC 0.94 SDC 0.11 LoA [−0.08;0.13]). Concerning its test-retest reliability, the results showed that the potential indicator ‘frothy saliva’ can be used to differentiate between farms (RS 0.61-0.87 ICC 0.74-0.91 SDC 0.20-0.35 LoA [−0.16;0.24]–[−0.46;0.25]), which matched the results of the indicators for the assessment of stereotypies, e.g. sham chewing (RS 0.81-0.93 ICC 0.80–0.91 SDC 0.16-0.23 LoA [−0.22;0.10]–[−0.24;0.21]). Sensitivity, specificity and regarding result parameters confirmed the usefulness of the potential indicator ‘frothy saliva’ on-farm (sensitivity 0.86, specificity 0.62, positive likelihood ratio 2.26, negative likelihood ratio 0.23). However, organic enrichment material can be a confounding factor. So does the currently still unknown relationship between ‘frothy saliva’ and non-stereotypic foraging or eating activities of sows. Besides that, the potential indicator ‘frothy saliva’ proved to be as reliable as the indicators for the assessment of stereotypies and demonstrated higher feasibility. Hence, the use of the potential indicator ‘frothy saliva’ is recommended to assess stereotypies in sows. Thereby, it could contribute to an improvement of the Welfare Quality® protocol for sows and piglets.

The present study aimed at isolating factors of potential influence on the Novel-Object Test (NOT), the Forced Human-Approach Test (FHAT), the Voluntary Human-Approach Test (VHAT) and the Human-Animal Relationship Test (HART) to draw conclusions about factors that should be considered when using these tests for the evaluation of the welfare level at different farms. Therefore, the NOT, FHAT, VHAT and HART were performed three times on ten different fattening farms. The pigs were tested at pen level, so that all pigs of one pen were examined simultaneously and scored individually during the same test. The pigs at the beginning of fattening (1) were significantly more interested in the novel object than the pigs in the middle of fattening (2) and final fattening (3) (1: 79.3 ± 0.03 % vs. 2: 66.4 ± 0.04 %, 3: 67.7 ± 0.04 % of pigs, p

The present paper focuses on evaluating the interobserver reliability of the 'Welfare Quality(®) Animal Welfare Assessment Protocol for Growing Pigs'. The protocol for growing pigs mainly consists of a Qualitative Behaviour Assessment (QBA), direct behaviour observations (BO) carried out by instantaneous scan sampling and checks for different individual parameters (IP), e.g. presence of tail biting, wounds and bursitis. Three trained observers collected the data by performing 29 combined assessments, which were done at the same time and on the same animals; but they were carried out completely independent of each other. The findings were compared by the calculation of Spearman Rank Correlation Coefficients (RS), Intraclass Correlation Coefficients (ICC), Smallest Detectable Changes (SDC) and Limits of Agreements (LoA). There was no agreement found concerning the adjectives belonging to the QBA (e.g. active: RS: 0.50, ICC: 0.30, SDC: 0.38, LoA: -0.05 to 0.45; fearful: RS: 0.06, ICC: 0.0, SDC: 0.26, LoA: -0.20 to 0.30). In contrast, the BO showed good agreement (e.g. social behaviour: RS: 0.45, ICC: 0.50, SDC: 0.09, LoA: -0.09 to 0.03 use of enrichment material: RS: 0.75, ICC: 0.68, SDC: 0.06, LoA: -0.03 to 0.03). Overall, observers agreed well in the IP, e.g. tail biting (RS: 0.52, ICC: 0.88; SDC: 0.05, LoA: -0.01 to 0.02) and wounds (RS: 0.43, ICC: 0.59, SDC: 0.10, LoA: -0.09 to 0.10). The parameter bursitis showed great differences (RS: 0.10, ICC: 0.0, SDC: 0.35, LoA: -0.37 to 0.40), which can be explained by difficulties in the assessment when the animals moved around quickly or their legs were soiled. In conclusion, the interobserver reliability was good in the BO and most IP, but not for the parameter bursitis and the QBA.

Knowledge of the network structure of agonistic interactions helps to understand the formation and the development of aggressive behavior. Therefore, video observation data of 149 pigs over three different age levels were investigated for 2 days each directly after mixing (65 groups in the rearing area, 24 groups in the growing stable and 12 groups in the breeding stable). The aim of the study was to use network analysis to investigate the development of individual network positions of specific animals and to determine whether centrality parameters in previous mixing situations have an impact on the future behavior of the animals. The results of the weighted degree centrality indicated that weaned pigs had a higher fighting intensity directly after mixing compared to growing pigs and gilts. Also, the number of different opponents (degree centrality) was higher compared to the older age groups. The betweenness centrality showed relatively small values and no significant differences between the different age levels, whereas the closeness centrality showed high values at all observed age levels. Experiences gained in previous agonistic interactions had an impact on the centrality parameters in subsequent mixing situations. It was shown that the position of individual animals in agonistic interaction networks can be characterized using social network analysis and that changes over different age levels can be detected. Therefore, social network analysis provides insights into the formation and evolution of behavioral patterns which could be of particular interest for the identification of key factors with regard to abnormal behavior (e.g. tail biting).