Understanding Cows' Emotions on Farm: Are Eye White and Ear Posture Reliable Indicators?

Events with Different Emotional Valence Affect the Eye's Lacrimal Caruncle Temperature Changes in Sheep

Infrared thermography (IRT) has been recently applied to measure lacrimal caruncle temperature non-invasively since this region is related to the sympathetic response, and it seems a promising technique that is able to infer negative emotions in sheep (e.g., fear). However, the scientific literature so far is limited in understanding whether a caruncle's temperature changes also in response to positive emotional states in sheep. Through classical conditioning, we aimed to assess how a positive or a negative event affects the physiological (lacrimal caruncle temperature measured with IRT and cortisol levels) and behavioral responses of sheep (ear position). Fourteen ewes from the same flock were randomly assigned to two treatment groups: positive (n = 7) and negative (n = 7). Each group was then trained through classical conditioning to associate a neutral auditory (ring bell) stimulus to an oncoming event: for the positive group, the presence of a food reward (maize grains), while for the negative one, the opening of an umbrella. After three weeks of training, before (at rest) and after (post-treatment), lacrimal caruncle temperature was non-invasively measured via IRT, and saliva samples were gently collected to measure cortisol levels. During treatment, sheep behavior was videorecorded and then analyzed using a focal animal sampling technique. At rest, the eye's lacrimal caruncle temperature was similar in both groups, while post-treatment, a significant increase was shown only in the negative group (t-test; p = 0.017). In the anticipation phase, sheep in the positive group kept their ears forward longer compared to those in the negative one (Mann-Whitney; p < 0.014), 8.3 ± 2.1 s and 5.2 ± 4.2 s, respectively. The behavioral response observed reflects a learnt association between a neutral stimulus and events with different emotional valence. Cortisol concentration slightly increased in both groups post-treatment. Our results confirm that IRT is a non-invasive technique that can be useful when applied to assess how positive and negative events may affect the physiological response in sheep.

Automated monitoring and detection of disease using a generic facial feature scoring system - A case study on FMD infected cows

Digital images are becoming more readily available and possibilities for image processing are developing rapidly. This opens the possibility to use digital images to monitor and detect diseases in animals. In this paper we present 1) a generic facial feature scoring system based on seven facial features, 2) manual scores of images of Holstein Frisian heifers during foot-and-mouth disease vaccine efficacy trials and 3) automatic disease scores of the same animals. The automatic scoring system was based on the manual version and trained on annotated images from the manual scoring system. For both systems we found an increase in disease scores three days post infection, followed by a recovery. This temporal pattern matched with observations made by animal caretakers. Importantly, the automatic system was able to discern animals that were protected by the vaccine, and did not develop blisters at the feet, and animals that were not protected. Finally, automatic scores could be used to detect healthy and sick animals with a sensitivity and specificity of 0.94 on the second and third days following infection in an experimental setting. This generic facial feature disease scoring system could be further developed and extended to lactating Holstein Frisian dairy cows, other breeds and other infectious diseases. The system could be applied during animal experiments or, after further development, in a farm setting.

Positive Welfare Indicators in Dairy Animals

Nowadays, there is growing interest in positive animal welfare not only from the view of scientists but also from that of society. The consumer demands more sustainable livestock production, and animal welfare is an essential part of sustainability, so there is interest in incorporating positive welfare indicators into welfare assessment schemes and legislation. The aim of this review is to cite all the positive welfare indicators that have been proposed for dairy animals in theory or practice. In total, twenty-four indicators were retrieved. The most promising are exploration, access to pasture, comfort and resting, feeding, and behavioral synchronicity. Qualitative behavioral assessment (QBA), social affiliative behaviors, play, maternal care, ear postures, vocalizations, visible eye white, nasal temperature, anticipation, cognitive bias, laterality, and oxytocin have been also studied in dairy ruminants. QBA is the indicator that is most often used for the on-farm welfare assessment. Among all dairy animals, studies have been performed mostly on cattle, followed by sheep and goats, and finally buffaloes. The research on camel welfare is limited. Therefore, there is a need for further research and official assessment protocols for buffaloes and especially camels.

Effect of mother bonded rearing on growth, health and physiological state of Murrah buffalo calves

We investigated the effect of different types of mother-young contacts (fenceline, restricted and no contact) on the health, growth performance, behaviour and physiological state of Murrah buffalo calves. A total of 24 calves were allocated to three groups of 8: NCM (no calf-mother contact), RCM (restricted calf-mother contact) and FCM (fenceline calf-mother contact). At three months of age, the FCM calves had a higher average body weight (58.6 ± 1.5 kg) than the RCM (52.8 ± 1.3 kg) and NCM (53.6 ± 1.3 kg) calves (P < 0.05). The average daily gain (ADG) at three months of age was greater in FCM (0.6 ± 0.1 kg/d) than RCM (0.5 ± 0.1 kg/d) and NCM (0.5 ± 0.1 kg/d) calves (P < 0.05). The mean immunoglobulin G (IgG) concentrations were significantly greater on d 7, 28, 42 and d 56 of sampling (P < 0.05 for all comparisons) in FCM than RCM and NCM calves. The mean cortisol levels were highest in the NCM calves followed by RCM and the lowest values were observed in FCM calves on d 0, d 7, d 28, d 42 and d 56, respectively (P < 0.05, for all recorded days). The diarrhoea score and eggs per gram of faeces (EPG) were significantly greater in the NCM group compared to the RCM and FCM groups. The time spent in cross sucking, licking inanimate objects and self-licking was greatest (P < 0.05) in NCM calves, followed by RCM calves, and was almost non-existent in the FCM group on all the recorded weeks. Time spent in backward ear position was greater (P < 0.05) in FCM than RCM and NCM calves. The average time spent in forward ear position was greatest (P < 0.05) in the RCM calves followed by NCM with the lowest time observed in FCM calves. The mean duration of time spent by calves in the asymmetrical and axial ear position differed significantly (P < 0.05) among NCM, RCM and FCM calves, P < 0.05. The full and fenceline buffalo calf-mother contact system showed higher growth rates, lower levels of stress responses, oral stereotypies and eggs per gram of faeces. In addition, ear postures may be used as a dependable, and reliable measure of positive, low arousal emotional states.

The Welfare of Dairy Cows in Pasture, Free Stall, and Compost Barn Management Systems in a Brazilian Subtropical Region

The effect of milk production systems on the welfare of dairy cows has been studied worldwide, but studies that compare pasture-based, compost barn, and free stall systems, according to animal welfare, are more scarce. In this work, the welfare of 51 dairy herds, including 17 from each management system, was investigated through the application of the Welfare Quality® protocol. Descriptive statistics and the Kruskal-Wallis non-parametric method were used to analyze variables. In the present work, the welfare of the evaluated herds was significantly better in the pasture-based system than in the confinement systems. However, the pasture-based system presented weaknesses in providing water resources. The compost barn had fewer animal welfare critical points than the free stall system, as well as it was better than the free stall in measures related to comfort and health. The free stall did not present better scores than the other systems. It is concluded that the welfare of dairy cows is affected by the rearing system, with better scores, in most measures, in the pasture-based system, followed by the compost barn and, finally, the free stall.

Correlation of Animal-based parameters with environment-based parameters in an on-farm welfare assessment of growing pigs

Nine pig farms were evaluated for the welfare quality in Korea using animal- and environment-based parameters (particularly air quality parameters) during the winter of 2013. The Welfare Quality^® (WQ^®) protocol consists of 12 criteria within four principles. The WQ^® protocol classifies farms into four categories ranging from ‘excellent’ to ‘not classified’. Each of these criteria has specific measures for calculating scores. Calculations for the welfare scores were conducted online using the calculation model in the WQ^® protocol. Environment-based parameters like microclimate (i.e., temperature, relative humidity, air speed, and particulate matter), bacteria (total airborne bacteria, airborne total coliform, and airborne total Escherichia coli), concentration of gases (carbon dioxide, ammonia, and hydrogen sulfide) were measured to investigate the relationship between animal- and environment-based parameters. Correlations between the results of animal- and environment-based parameters were estimated using spearman correlation coefficient. The overall assessments found that five out of nine farms were ‘acceptable’, and four farms were ‘enhanced’; no farm was ‘not classified’. The average score for the four principles across the nine farms, in decreasing order, were ‘good feeding’ (63.13 points) > ‘good housing’ (59.26 points) > ‘good health’ (33.47 points) > ‘appropriate behaviors’ (25.48 points). In the result of the environment aspect, the relative humidity of farms 2 (93.4%), 3 (100%), and 9 (98%) was much higher than the recommended maximum relative humidity of 80%, and four out of the nine farms had ammonia concentrations greater than 40 ppm. Ammonia had negative correlations with ‘positive social behaviors’ and positive emotional states: content, enjoying, sociable, playful, lively, happy and it had positive correlations with negative emotional states: aimless, distressed. The concentration of carbon dioxide had negative correlations with positive emotional states; calm, sociable, playful, happy and it had a positive correlation with negative emotional state; aimless. Our results indicate that the control of the environment for growing pigs can help improve their welfare, particularly via good air quality (carbon dioxide, ammonia, hydrogen sulfide).

Towards a Positive Welfare Protocol for Cattle: A Critical Review of Indicators and Suggestion of How We Might Proceed

Current animal welfare protocols focus on demonstrating the absence (or at least low levels) of indicators of poor welfare, potentially creating a mismatch between what is expected by society (an assurance of good animal welfare) and what is actually being delivered (an assurance of the absence of welfare problems). This paper explores how far we have come, and what work still needs to be done, if we are to develop a protocol for use on commercial dairy farms where the aim is to demonstrate the presence of positive welfare. Following conceptual considerations around a perceived “ideal” protocol, we propose that a future protocol should be constructed (i) of animal-based measures, (ii) of indicators of affective state, and (iii) be structured according to indicators of short-term emotion, medium-term moods and long-term cumulative assessment of negative and positive experiences of an animal's life until now (in contrast to the current focus on indicators that represent different domains/criteria of welfare). These three conditions imposed the overall structure within which we selected our indicators. The paper includes a critical review of the literature on potential indicators of positive affective states in cattle. Based on evidence about the validity and reliability of the different indicators, we select ear position, play, allogrooming, brush use and QBA as candidate indicators that we suggest could form a prototype positive welfare protocol. We emphasise that this prototype protocol has not been tested in practice and so it is perhaps not the protocol itself that is the main outcome of this paper, but the process of trying to develop it. In a final section of this paper, we reflect on some of the lessons learnt from this exercise and speculate on future perspectives. For example, while we consider we have moved towards a prototype positive welfare protocol for short-term affective states, future research energy should be directed towards valid indicators for the medium and long-term.

Quality of Death in Fighting Bulls during Bullfights: Neurobiology and Physiological Responses

During bullfights, bulls undergo physiometabolic responses such as glycolysis, anaerobic reactions, cellular oedema, splenic contraction, and hypovolemic shock. The objective of this review article is to present the current knowledge on the factors that cause stress in fighting bulls during bullfights, including their dying process, by discussing the neurobiology and their physiological responses. The literature shows that biochemical imbalances occur during bullfights, including hypercalcaemia, hypermagnesaemia, hyperphosphataemia, hyperlactataemia, and hyperglycaemia, associated with increased endogenous cortisol and catecholamine levels. Creatine kinase, citrate synthase, and lactate dehydrogenase levels also increase, coupled with decreases in pH, blood bicarbonate levels, excess base, partial oxygen pressure, and oxygen saturation. The intense exercise also causes a marked decrease of glycogen in type I and II muscle fibres that can produce myoglobinuria and muscular necrosis. Other observations suggest the presence of osteochondrosis. The existing information allows us to conclude that during bullfights, bulls face energy and metabolic demands due to the high intensity and duration of the exercise performed, together with muscular injuries, physiological changes, and high enzyme concentrations. In addition, the final stage of the bullfight causes a slow dying process for an animal that is sentient and conscious of its surroundings.

The Use of Artificial Intelligence in Assessing Affective States in Livestock

In order to promote the welfare of farm animals, there is a need to be able to recognize, register and monitor their affective states. Numerous studies show that just like humans, non-human animals are able to feel pain, fear and joy amongst other emotions, too. While behaviorally testing individual animals to identify positive or negative states is a time and labor consuming task to complete, artificial intelligence and machine learning open up a whole new field of science to automatize emotion recognition in production animals. By using sensors and monitoring indirect measures of changes in affective states, self-learning computational mechanisms will allow an effective categorization of emotions and consequently can help farmers to respond accordingly. Not only will this possibility be an efficient method to improve animal welfare, but early detection of stress and fear can also improve productivity and reduce the need for veterinary assistance on the farm. Whereas affective computing in human research has received increasing attention, the knowledge gained on human emotions is yet to be applied to non-human animals. Therefore, a multidisciplinary approach should be taken to combine fields such as affective computing, bioengineering and applied ethology in order to address the current theoretical and practical obstacles that are yet to be overcome.

Happy Cow or Thinking Pig? WUR Wolf—Facial Coding Platform for Measuring Emotions in Farm Animals

Emotions play an indicative and informative role in the investigation of farm animal behaviors. Systems that respond and can measure emotions provide a natural user interface in enabling the digitalization of animal welfare platforms. The faces of farm animals can be one of the richest channels for expressing emotions. WUR Wolf (Wageningen University & Research: Wolf Mascot), a real-time facial recognition platform that can automatically code the emotions of farm animals, is presented in this study. The developed Python-based algorithms detect and track the facial features of cows and pigs, analyze the appearance, ear postures, and eye white regions, and correlate these with the mental/emotional states of the farm animals. The system is trained on a dataset of facial features of images of farm animals collected in over six farms and has been optimized to operate with an average accuracy of 85%. From these, the emotional states of animals in real time are determined. The software detects 13 facial actions and an inferred nine emotional states, including whether the animal is aggressive, calm, or neutral. A real-time emotion recognition system based on YoloV3, a Faster YoloV4-based facial detection platform and an ensemble Convolutional Neural Networks (RCNN) is presented. Detecting facial features of farm animals simultaneously in real time enables many new interfaces for automated decision-making tools for livestock farmers. Emotion sensing offers a vast potential for improving animal welfare and animal–human interactions.

Measuring Farm Animal Emotions-Sensor-Based Approaches

Understanding animal emotions is a key to unlocking methods for improving animal welfare. Currently there are no ‘benchmarks’ or any scientific assessments available for measuring and quantifying the emotional responses of farm animals. Using sensors to collect biometric data as a means of measuring animal emotions is a topic of growing interest in agricultural technology. Here we reviewed several aspects of the use of sensor-based approaches in monitoring animal emotions, beginning with an introduction on animal emotions. Then we reviewed some of the available technological systems for analyzing animal emotions. These systems include a variety of sensors, the algorithms used to process biometric data taken from these sensors, facial expression, and sound analysis. We conclude that a single emotional expression measurement based on either the facial feature of animals or the physiological functions cannot show accurately the farm animal’s emotional changes, and hence compound expression recognition measurement is required. We propose some novel ways to combine sensor technologies through sensor fusion into efficient systems for monitoring and measuring the animals’ compound expression of emotions. Finally, we explore future perspectives in the field, including challenges and opportunities.

Welfare Quality® for dairy cows: towards a sensor-based assessment

This Research Reflection addresses the possibilities for Welfare Quality® to evolve from an assessment method based on data gathered on punctual visits to the farm to an assessment method based on sensor data. This approach could provide continuous and objective data, while being less costly and time consuming. Precision Livestock Farming (PLF) technologies enabling the monitorisation of Welfare Quality® measures are reviewed and discussed. For those measures that cannot be assessed by current technologies, some options to be developed are proposed. Picturing future dairy farms, the need for multipurpose and non-invasive PLF technologies is stated, in order to avoid an excessive artificialisation of the production system. Social concerns regarding digitalisation are also discussed.

Effects of Different Stroking Styles on Behaviour and Cardiac Parameters in Heifers

Simple Summary

Positive emotions can improve the welfare of animals. Humans can induce positive emotions in cattle via gentle interactions, such as stroking. While previous studies showed that stroking at the lower side of the neck elicited the most positive reactions in cows, cattle groom each other on different body regions and probably react to each other’s signals. We compared the reactions of dairy heifers to two different stroking styles: stroking exclusively on the lower neck or stroking the whole head/neck region and reactively following the signals of the animal. For both styles, we observed longer durations of behaviours indicating positive emotions and relaxation during stroking, suggesting that the animals enjoyed the treatment. The different stroking styles led to differences in the positions of the heifers’ ears: during “reactive” stroking, the animals held their ears longer in low positions, whereas during stroking of the lower neck, the ears spent longer pointing backwards-upwards. However, we did not observe significant differences in other behaviours, indicating that the manner of stroking of the head/neck region seemed to be not very important for the positive perception of stroking. We conclude that both ways of stroking can elicit positive emotions in cattle and increase the animals’ well-being.

Abstract

Gentle animal–human interactions, such as stroking, can promote positive emotions and thus welfare in cattle. While previous studies showed that stroking at the ventral neck elicited the most positive reactions in cows, intra-specific allogrooming in cattle includes different body regions and is probably guided partly by the receiver. Thus, we compared heifers’ (n = 28) reactions to stroking with the experimenter either reactively responding to perceived momentary preferences of the heifers or exclusively stroking the ventral neck. Independently of the stroking style, longer durations of neck stretching and contact occurred during stroking, supporting our hypothesis of a positive perception of stroking. We did not confirm the predicted decrease in heart rate and increase in heart rate variability, but instead found a slightly increased mean heart rate during stroking. The different stroking styles elicited differences in the heifers’ ear positions: “reactive” stroking led to longer durations of low ear positions during stroking, while during “ventral neck” stroking, the duration of back up increased. However, no other behaviours differed significantly between different stroking styles, indicating that the exact manner of stroking applied in our treatments seemed to be less important in the promotion of positive affective states in cattle through gentle human–animal interactions.

How Can We Assess Positive Welfare in Ruminants?

Until now, most research has focused on the development of indicators of negative welfare, and relatively few studies provide information on valid, reliable, and feasible indicators addressing positive aspects of animal welfare. However, a lack of suffering does not guarantee that animals are experiencing a positive welfare state. The aim of the present review is to identify promising valid and reliable animal-based indicators for the assessment of positive welfare that might be included in welfare assessment protocols for ruminants, and to discuss them in the light of the five domains model, highlighting possible gaps to be filled by future research. Based on the existing literature in the main databases, each indicator was evaluated in terms of its validity, reliability, and on-farm feasibility. Some valid indicators were identified, but a lot of the validity evidence is based on their absence when a negative situation is present; furthermore, only a few indicators are available in the domains of Nutrition and Health. Reliability has been seldom addressed. On-farm feasibility could be increased by developing specific sampling strategies and/or relying on the use of video- or automatic-recording devices. In conclusion, several indicators are potentially available (e.g., synchronisation of lying and feeding, coat or fleece condition, qualitative behaviour assessment), but further research is required.