Isabelle Veissier

Véronique Deiss

Mette Herskin

Emer Kennedy

Kenny Rutherford

Keywords: animal experimentation, ethics, 3 Rs, animal welfare, pain Methods in cattle physiology and behaviour research -

Introduction

There are ongoing philosophical, moral, and societal debates about experiments on live animals. Along with a consequentialist approach, it may be considered that an action -here an experiment on live animals -is morally acceptable if the knowledge it aims to produce can result in an overall benefit. In other words, it is acceptable if the constraints imposed on the animals involved are outweighed by the larger benefits expected for others (humans or animals). Alternatively, it can be argued that, because animals are sentient beings, they have a right not to be used by others. There may also be points of view in between, considering that animal experimentation is acceptable on the condition that no alternative ways to gain the relevant knowledge are possible and animal suffering is limited as much as possible. What is considered as an important knowledge that justifies experimentation may differ as it refers to individual values. It is not the intention of this chapter to hold a moral debate about animal experimentation (for reviews, see for instance [START_REF]The ethics of research involving animals[END_REF], [START_REF] Liou | The ethics of animal experimentation[END_REF]). Rather, we take a pragmatic approach that we hope will guide experimenters in their decision to undertake an experiment (or not), after having made explicit all arguments for or against that experiment.

A -Reducing animal suffering: The 3Rs approach

In 1959, the zoologist William Russell and the microbiologist Rex Burch published The Principles of Humane Experimental Technique [START_REF] Russell | The principles of humane experimental technique[END_REF]. These principles are known as the 3Rs: Replacement, Reduction, and Refinement. The 3Rs are now used worldwide, including in legislation (e.g. the EU Directive 2010/63/UE, Article 1).

Replacement

Russell and Burch insisted on the need to strive to replace sentient species by non-sentient species or by non-living models, e.g. cells, tissues or computer models. For instance, ruminal digestion processes have often been studied by fixing a cannula on the animals' rumen in order to monitor how feeds are digested by the rumen microbiota. In vitro fermentation techniques have been developed where small amounts of feeds are incubated with ruminal fluid (Example 1 detailed below). Although obtaining ruminal fluid still requires that few animals are cannulated this approach means that many plants or compounds can be tested in vitro [START_REF] Niderkorn | In vitro rumen fermentation of diets with different types of condensed tannins derived from sainfoin (Onobrychis viciifolia Scop.) pellets and hazelnut (Corylus avellana L.) pericarps[END_REF]. Another possibility to replace experiments is to collect data from farms. Such an approach is largely used by epidemiologists, e.g. to identify risk factors for a disease or the kinetics of its transmission. A similar approach has been used to study factors affecting the welfare of dairy cows [START_REF] De Boyer Des Roches | The major welfare problems of dairy cows in French commercial farms: an epidemiological approach[END_REF]. Nowadays, many farms are equipped with sensors so that data can be collected without any handling of the animals. This offers large datasets that can be processed for research purposes, as done by Veissier et al. [START_REF] Veissier | Short communication: Early modification of the circadian organization of cow activity in relation to disease or estrus[END_REF], that identified patterns of cows' activities in relation to their health status. Finally, meta-analyses of published results can also be used to clarify mechanisms [START_REF] Sauvant | Review: Use and misuse of meta-analysis in Animal Science[END_REF].

Example 1: Replacing in vivo studies on ruminal digestion by in vitro fermentation (personal communication from V. Niderkorn, INRAE)

Often, studies on ruminal degradation of feeds are performed using in situ methods, with nylon bags containing feeds incubated in the rumen. The substrates are diluted in the rumen and do not interfere with fermentation. Such a technique requires the animals to be fixed with a canula in the rumen, which is a very invasive method. In addition, measuring ruminal fermentation parameters and methane emissions is done using in vivo experiments with cannulated animals and heavy equipment, respectively. We now increasingly use in vitro fermentation, mimicking digestion within the rumen. Plant substrates are incubated in anaerobic conditions at 39°C in culture bottles containing buffered rumen juice from sheep or cows (Figure 1). After 24 h of fermentation, parameters such as pH, total gas and methane production, dry matter disappearance, concentrations and profiles of total volatile fatty acids, and ammonia in the fermentation medium, are measured (Figure 2). This method requires only three animal donors of rumen fluid which are cannulated, and can provide information on the rumen digestion of plant substrates or on effects of specific bioactive compounds or additives. In vitro fermentation can thus be used in a screening approach, by which many plants, compounds, or additives can be tested, allowing selection of the most promising ones according to the objectives of the study. Only these may be tested in situ or in vivo (that is provided to the animals in the food) for further validation.

Reduction

According to Russell and Burch, in the absence of full replacement, researchers must limit the use of sentient animals to experiments considered essential. What is considered essential remains under question (see discussion in the next section). One can at least limit the number of animals in an experiment to the minimum needed to ensure meaningful results. This number can be estimated by taking into account the variability between individuals in a population and the expected effect of a treatment, as well as the risks one is ready to take when rejecting or accepting a hypothesis (alpha and beta risks), in a so-called power analysis [START_REF] Cohen | Statistical power analysis for the behavioral sciences[END_REF]. The inter-individual variability can be estimated a priori from pilot studies or from the literature on the condition that similar measurements have already been reported. Alternatively, one can check a posteriori that the number of animals were sufficient to highlight effects of treatments applied in an experiment, given the observed variability and the magnitude of differences; if that number is not sufficient, then the experiment can be extended on more animals. Other authors call for a New Statistics approach whereby the null hypothesis significance test is replaced by estimates of effect sizes and confidence intervals [START_REF] Kruschke | The Bayesian New Statistics: Hypothesis testing, estimation, metaanalysis, and power analysis from a Bayesian perspective[END_REF]. Special attention shall be drawn to experimental designs and statistical models to ensure that the analyses will be powerful and is able to highlight significant effects. The power of a statistical analysis can be increased by reducing the error term. Therefore, limiting errors due to measurements (by using reliable measurement methods) is essential. In addition, the variability between animals can be reduced by using animals of same age, weight, production, and genetic background. However, the effort to reduce animal numbers may limit translation of findings to relevance under real-life conditions, if -for instanceonly one sex or breed are represented in a study, this may lessen how generalizable the results are to a wider population. The inherent trade-off here is often unavoidable but experimenters should at least be aware that it exists when making experimental design decisions. To overcome some diversity among animals, it is important to take full account of all factors that can affect results, e.g. by adding covariates such as the genetic potential. In case of a study using repeated measurements, choosing appropriate matrix correlation also contributes to increase the chance to highlight significant differences between treatments.

Refinement

Refinement refers to the use of methods that alleviate or minimize potential pain, suffering or distress, enhance animal welfare, and seek to optimise model validity. This requires defining good practices to perform specific measurements whereby the constraints on animals are minimised. For instance, digestibility measurements are often performed by measuring closely the intake of animals and their excretions in faeces, which requires the animals to be kept in small individual crates where faeces can be collected apart from urine. 'Four-star' digestibility crates were designed to offer as little discomfort as possible to the animals while allowing precise collection of samples ([10], Example 2) and studies are being carried out to reduce the duration of measurements in such stalls. Whenever possible, a more severe procedure should be replaced by an alternative method with less negative impact on the animal, e.g. digestibility measurements in individual crates can be replaced by the use of proxies in blood and faeces ( [START_REF] Nasrollahi | Natural 15N abundances in plasma and urea-N concentration in milk as biomarkers of urinary N excretion in dairy cows: a meta-analysis[END_REF], [START_REF] Andueza | Faecal-NIRS for predicting animal-to-animal variation in feed organic matter digestibility in cattle[END_REF], Example 3). In addition, refinements to the overall life experience of the animal can often be made whilst they are not on study; this includes ensuring that living conditions allow good welfare, e.g. physical comfort, possibility to express behaviour (incl. enough space), appropriate social groups, absence of stress (incl. a high standard of human handling, perhaps alongside appropriate training or habituation to experimental procedures and measurements), and good health.

There may be antagonisms among the 3Rs, e.g., reducing the number of animals results in more suffering for the remaining animals. In that case, it is usually recommended to prioritise refinement against reduction [START_REF]Ethical principles and guidelines for experiments on animals[END_REF].

Apart from aligning research projects to moral values, large advantages of following the 3Rs principles have been obtained, from limiting the cost of research by using alternatives to animals or reducing their number to obtaining more reliable results by reducing the constraints imposed on animals. Indeed, stress responses -whether due to poor handling, social isolation or another cause -interfere with the metabolism and immune functions and this can distort results of experiments [START_REF] Poole | Happy animals make good science[END_REF]. If a painful procedure is applied, the pain should be minimised by using painkillers -unless pain is the focus of the study. Some scientists argue that painkillers interfere with the results of experiments. Actually, pain also can affect the results of experiments. Peterson et al. [START_REF] Peterson | To treat or not to treat: The effects of pain on experimental parameters[END_REF] reviewed the effects of analgesics and of pain in common animal models used in therapeutic studies and provided guidance on the decision whether or not to use painkillers. Overall, painkillers must be used when a painful procedure is used, unless the experimenter can demonstrate that withholding of painkillers is necessary for the study.

The best advantages were obtained when there is an institutional strategy to commit to the 3Rs. Indeed, analysing projects from pharmaceutical industries, Tornqvist et al. [START_REF] Törnqvist | Strategic Focus on 3R Principles Reveals Major Reductions in the Use of Animals in Pharmaceutical Toxicity Testing[END_REF] showed that applying the 3Rs can result in a large decrease in the number of animals used, thanks to improvement of the design of experiments, refining methods of investigation, and better coordination of research projects. The authors concluded that: "in silico-, in vitro-and in vivo-methods all hold the potential for applying the reduction R and should be consequently coordinated at a strategic level". For 'gold standard' measurement of digestibility, cattle are maintained in stalls restraining their movements to separately collect faeces and urine. We designed a device to improve the housing of cattle for digestibility measurements so that the constraints for the animal are reduced while the sampling of faeces and urine are easier and more precise (Figure 3). Total tract digestibility and nitrogen (N) excretion are often measured by separately collecting faeces and urine from cattle placed in so-called metabolic cages for at least 10-14 d. We propose alternative methods to predict total tract digestibility and urinary N excretion that require only restraining animals for a few minutes to collect faeces, blood, or milk. The formula to calculate total digestibility or N excretion will be available soon (articles in prep.).

We propose to assess total tract digestibility by faecal visible/near infrared spectroscopy (VIS/NIRS). Faeces are obtained by hand rectal collection while animals are temporally immobilized by head holding devices. The spectra obtained from faeces allow diets to be discriminated according to their total tract organic matter digestibility (OMD, Figure 4). It may also reflect inter-individual variations in digestibility from animals fed the same diet.

Figure 4: Relation between organic matter digestibility predicted by NIRS from faeces and measured organic matter digestibility by the 'gold standard' method using metabolic cages. Each symbol represents an experimental diet within a particular study. r 2 =0.89 (P<0.001).

We propose to assess urinary N excretion by two biomarkers: the natural 15 N enrichment of animal proteins (in plasma or milk) over the consumed diet and the urea concentration (in plasma or milk) (Figure 5). Both biomarkers vary with N partitioning between anabolism (animal proteins in body or milk) and catabolism (urinary N). Measuring these biomarkers require blood sampling, e.g. by venepuncture of the coccygeal vein, and milk sampling, taken during conventional milking.

B -How to assess and minimise harms imposed on animals

The 3Rs approach prompts scientists to better consider the constraints they apply on experimental animals. Several methods have been proposed to assess these constraints together with ways to alleviate them.

Assessment of constraints imposed to animals

According to the Nuffield Council on Bioethics [START_REF]The ethics of research involving animals[END_REF], assessing the harms imposed on animals includes the evaluation of clinical signs, the study of animals' choices, the familiarity with ethological and ecological data, and the consideration of physiological and neurological features.

Clinical signs of poor welfare can be detected from the behaviour of animals and physiological indices of stress. Such signs are widely described in the literature. To cite the most common ones: Acute responses can be seen in attempts to escape from a situation, distress vocalisations, tachycardia and increased blood cortisol as observed when animals not used to handling are put in a holding cage [START_REF] Veissier | Adaptability of calves during weaning[END_REF]. More subtle signs can be seen in ear postures, with animals turning their ears back when exposed to a frightening stimulus [START_REF] Boissy | Cognitive sciences to relate ear postures to emotions in sheep[END_REF]. When animals are submitted to prolonged stressful situations, their behavioural reactivity can be altered leading to hyperactivity or on the contrary to hyporeactivity (sometimes referred to as 'apathy') and the functioning of the corticotropic axis is modified [START_REF] Mormède | Exploration of the hypothalamic-pituitary-adrenal function as a tool to evaluate animal welfare[END_REF]. More subtle signs can be a reduction in food or water consumption, decrease in body weight, isolation from peers, or hypo activity.

In addition, diseases lead to clinical signs such as dull hair or hyperthermia or more specific signs such as nasal discharge, diarrhoea, dyspnoea,… which often do not require veterinary skills to be noticed [START_REF]Welfare Quality® assessment protocol for cattle (fattening cattle, dairy cows, veal calves[END_REF]. Indices of pain have been extensively described in laboratory animals. Although less documented in farm animals, pain indicators have been proposed, e.g. for cattle [START_REF] Boyer | Behavioral and patho-physiological response as possible signs of pain in dairy cows during Escherichia con mastitis: A pilot study[END_REF], [START_REF] Gleerup | Pain evaluation in dairy cattle[END_REF]: Isolation: a cow experiencing pain is often isolated from the rest of the herd and her activity is less synchronized with that of the other cows. Low head posture: an active cow has generally the head at or above the line of the spinal column whereas a cow not active, not sleeping nor ruminating, and with the head below the line of the spinal column can be in pain. Facial expression of pain: strained look, furrows above nostrils, ears back or in a 'lamb' position (low ears with the opening facing downwards). Antalgic 'guarding' postures to reduce stimulation on the painful area: a cow with a painful limb may stand unsteadily, sometimes the body leaning against a wall, or back arched, or with weight shifting on hind legs to release the weight on a painful forelimb. Behaviours directed towards the painful area (up to selfmutilation in extreme cases) Vocalisations: Pain can induce more vocalisations with a high frequency. Reduced feed intake, decrease in time spent ruminating, this affecting milk yield in dairy cows and body condition Failure to perform normal behaviours, such as selfgrooming or play, or changes in time spent lying (either increase or decrease) Clinical signs: erect hair, shivering of muscles, shivering or panting Most of these indicators are not specific. For instance, fever can induce isolation-seeking and a stressed cow can have her ears backward and flattened. It is necessary to combine indicators before concluding that the animal is or is not in pain. In case of doubt, additional observations should be performed such as looking at the threshold for withdrawal movements in response to a noxious stimulation (an animal in pain often reacts at a lower threshold, which is called hyperalgesia) or checking if the animal displays such a withdrawal movement to a stimulation that would normally not induce withdrawal (allodynia). A scoring system was proposed by which a given clinical sign is assigned a specific weight and the final score is expressed on a 0-16 scale [START_REF] Boyer | Behavioral and patho-physiological response as possible signs of pain in dairy cows during Escherichia con mastitis: A pilot study[END_REF]. The authors consider that a cow is probably in pain if the score is 5 or more. However, different conditions will lead to different responses, and such scales should only be used for guidance.

The study of animal choices provides knowledge on animals' preferences vs. avoidances. One can allow animals choices between several options or ask them to work to obtain a putative preferred option [START_REF] Dawkins | Battery hens name their price: consumer demand theory and the measurement of ethological "needs[END_REF]. For instance, using such methods, it was shown that cattle avoid people shouting or making rapid erratic movements, that they search the company of familiar animals, and prefer to lie down on a soft and dry bedding, etc. [START_REF] Munksgaard | The ability of dairy cows to distinguish between people[END_REF], [START_REF] Fregonesi | Effects of bedding quality on lying behavior of dairy cows[END_REF], [START_REF] Raussi | The formation of preferential relationships at early age in cattle[END_REF]. This knowledge helps to design animal living conditions that offer what animals favour and to avoid producing stress during experimental procedures.

The study of the ethological repertoire and the ecology of a species provides knowledge on the behavioural repertoire of a species, which is the range of behaviours the animals from this species are likely to express in their natural environment. There is evidence that animals are motivated to express at least some of the behavioural patterns from their repertoire, even when not in their natural habitat: performing this behaviour is rewarding and preventing it is frustrating, possibly leading to abnormal behaviour. For instance, calves are motivated to suck a teat and to eat solid foods. By contrast, for a long time, veal calves were fed only liquids that they had to drink from buckets, which resulted in non-nutritive activities (cross sucking, nibbling, tong-playing) [START_REF] Veissier | Non-nutritive oral activities and stress responses of veal calves in relation to feeding and housing conditions[END_REF], [START_REF] Veissier | Providing social contacts and objects for nibbling moderates reactivity and oral behaviors in veal calves[END_REF]. Similarly tethering prevents cows from walking although they are motivated to do so [START_REF] Veissier | The motivation of cows to walk as thwarted by tethering[END_REF]. The conditions in which experimental animals are kept should allow them to express activities they are motivated for, at least during some parts of the day.

Last, knowing the physiological and neurological features of a species can help to assess their degree of consciousness or the extent to which they can feel pain. For a long time only vertebrates and cephalopods were thought to be able to experience pain. However, this assumption was challenged by studies on invertebrates such as prawns [START_REF] Barras | Invertebrates can feel pain, suggests study on prawns[END_REF]. Scientists now question the ethics of experimentation on insects [START_REF] Freelance | To Regulate or Not to Regulate? The Future of Animal Ethics in Experimental Research with Insects[END_REF]. Across species, animals should be given the benefit of the doubt regarding their ability to suffer. The same applies when considering life stages within a species, particularly in the highly debated area of foetal and neonatal sentience [START_REF] Mellor | Onset of sentience: The potential for suffering in fetal and newborn farm animals[END_REF].

All these aspects of animal welfare should be assessed a priori -that is during the design of an experiment -from the knowledge available in the literature, from pilot studies or from experienced experts. Then during an experiment, the state of the animals should be monitored closely in order to detect any signs of reduced welfare.

Monitoring animal welfare and setting of end-points

Animals should be monitored closely during experiments. As a minimum, there should be a daily observation taking into account clinical and behavioural signs as well as feed intake and milk production, if applicable. The animals should be weighed or their body condition scored regularly. In addition, for each experiment that is likely to impair the welfare of animals, it is necessary to adjust the monitoring to the disorders that may occur: indices of stress if the procedure is likely to be stressful, monitoring of specific clinical signs or blood parameters in case a disease is induced.

Such a monitoring will enable the experimenter to take corrective actions, e.g. administration of pain killers or reduction of stress. In addition, it is essential to document the condition of the animals during studies so that the results are reproducible. Thresholds should be decided beforehand to decide that corrective actions are needed. Such thresholds are called 'Endpoints': "A humane endpoint can be defined as the point at which an experimental animal's pain and/or distress can be terminated, minimized, or reduced by actions such as killing the animal humanely, terminating a painful procedure, or providing treatment to relieve pain and/or distress." [START_REF]Guidelines on Choosing an Appropriate Endpoint in Experiments Using Animals for Research, Teaching and Testing[END_REF] The purpose of the application of endpoints is to be able to predict severe pain, distress, suffering, or impending death, and to act before the animal experiences these effects. Typically an experiment should be terminated in case of [START_REF]Guidelines on Choosing an Appropriate Endpoint in Experiments Using Animals for Research, Teaching and Testing[END_REF]: significant loss of body weight, loss of appetite and change in water consumption, important changes in physical appearance (e.g. posture, coat appearance), severe clinical signs, e.g. high body core temperature, increased heart rate and respiration rate, hematological indictors of a disease, marked changes in behaviour, e.g. selfmutilation, abnormal vocalizations, changes in responsiveness to external stimuli.

For each experiment where endpoints are required, the experimenter, in consultation with a veterinarian, must develop a checklist specific to the research program. All signs need to be measurable or described precisely, and a clear limit has to be set, e.g. beyond which weight loss or which score on a pain scale the experiment must be ended. Then a plan must be defined to specify the actions to be undertaken when an endpoint is reached.

C -Balancing issues between constraints on animals and expected benefit of an experiment

Following the 3Rs approach and the application of appropriate end-points should result in the minimisation of harm for animals used in experiments. Yet, one may still contend that such remaining harm is not justified. This poses the question of how to balance issues between animal harm and potential benefits from the research results. In his seminal paper, Bateson [START_REF] Bateson | When to experiment on animals. Conflicts of interest between experimenters and their critics might be resolved by weighing up the degree of suffering againts the value of the research[END_REF] proposed to weigh up the degree of animal suffering against the quality of the research. Bateson did not, however, clearly define how research quality should be judged; although one may understand that he means the importance of the expected results. Bateson [START_REF] Bateson | When to experiment on animals. Conflicts of interest between experimenters and their critics might be resolved by weighing up the degree of suffering againts the value of the research[END_REF] then added that the certainty of medical benefits needs to be taken into account. It is not clear if this dimension is independent from the quality of research or is part of the quality of research, focused on benefits to humans. Anyway, the scene was set that issues needs to be balanced between constraints for animals and benefits that could be taken from the knowledge gained from an experiment.

How to consider the potential benefits of an experiment? The Australian National Health and Medical Research Council (1997) [START_REF]Australian Code of Practice for the Care and Use of Animals for Scientific Purposes[END_REF] proposed that any experimentation on animals should be appraised according to five potential objectives: understanding humans or animals; maintaining or improving the health and well-being of humans and animals; improving breeding techniques, ecology, and education. In some cases, the links between the expected results and one or several of these objectives can be easily estimated beforehand. However, there are many examples where a piece of knowledge was produced from so-called blue-sky research and lead to very important application that had not been foreseen. Grimm et al. [START_REF] Grimm | The road to hell Is paved with good intentions: why Harm-Benefit analysis and its emphasis on practical benefit jeopardizes the credibility of research[END_REF] argued that "whether practical benefits are realized is (a) impossible to predict and (b) exceeds the scope and responsibility of researchers". Forcing researchers to address the potential impacts of their research often leads them to promise too much from their research, which can in turn impair scientific credibility. Grimm et al. [START_REF] Grimm | The road to hell Is paved with good intentions: why Harm-Benefit analysis and its emphasis on practical benefit jeopardizes the credibility of research[END_REF] thus proposed to take into account the contributions that the research will make to a specific scientific area or to a research program. They concluded that the value of the expected knowledge from research can be understood in terms of (a) the scientific value of knowledge -i.e. its contribution to a given research field -and (b) the societal value of knowledge -i.e. potential benefits for a given society. Moreover, deciding if a research field is important is a political decision.

The rigour and the reproducibility of experiments are also part of their quality [START_REF] Aske | Expanding the 3R principles[END_REF], [START_REF] Pritt | The Interplay of ethics, animal elfare, and IACUC oversight on the reproducibility of animal studies[END_REF]. Research results do not always make their way up to publication. From our own experience in reviewing manuscripts, the poor design of experiments which prevent from drawing firm conclusions is actually the major cause of rejection. An unpublished piece of research using animals is definitively a waste of animals since no scientific knowledge will be produced. Poor reporting of the exact methods used is another cause of rejection. Editors of scientific journals report of a 'reproducibility crisis', in which a result cannot be consolidated by similar findings obtained by other researchers. The poor reproducibility can come from poor statistical analyses, incorrect data interpretation, technical issues, inappropriate experimental design (e.g. absence of control group), reporting only a subset of data that fits to the hypothesis, or even results falsification (summarised in [START_REF] Pritt | The Interplay of ethics, animal elfare, and IACUC oversight on the reproducibility of animal studies[END_REF]). This problem is amplified by the fact that negative results are often not published although they can be of significant value. According to Pritt and Hammer [START_REF] Pritt | The Interplay of ethics, animal elfare, and IACUC oversight on the reproducibility of animal studies[END_REF], poor animal welfare can also be a cause of poor reproducibility. Reporting precisely how an experiment was carried out and what were the statistical models should improve the reproducibility of results. To fill in this gap, the UK National Centre for the Replacement Refinement & Reduction of Animals in Research published the ARRIVE guidelines (Animal Research Reporting of in vivo experiments, available at https://arriveguidelines.org/). Several publishers now ask authors of manuscripts to follow the ARRIVE guidelines. Aske and Vaugh [START_REF] Aske | Expanding the 3R principles[END_REF] argued that it would be more efficient that funding bodies required that applicants provide a clear description of their intended work. This however can sometimes be difficult: the first study of a project may be easy to describe precisely but experimenters may learn from this study and refine the following studies accordingly. We suggest that the analysis of how the study is described could take place during the ethical evaluation of a protocol.

In conclusion, three main issues must be considered to evaluate the acceptability of a study: the constraints imposed on animals, the expected benefits of the research (for the society or a discipline), and the likelihood of obtaining research (quality of the design).

D -Who should decide and how?

Balancing issues between pros and cons of an experiment is based on values: the values attributed to animals and their suffering, the values attributed to a research piece. Scientists alone cannot decide on these values [START_REF] Bateson | When to experiment on animals. Conflicts of interest between experimenters and their critics might be resolved by weighing up the degree of suffering againts the value of the research[END_REF]. Ethical committees for experiments on animals have thus been set up in various countries and organisations to help to take decisions. They generally include veterinarians, scientists, animal technicians and other people such as ethicists, animal protectionists, or laypeople.

Several metrics have been proposed to balance issues regarding experiments on animals and help ethical committees in their evaluation of protocols. In the context of human medical research, Liguori et al. [START_REF] Liguori | Ethical Issues in the use of animal models for tissue engineering: Reflections on legal aspects, moral theory, three Rs Strategies, and Harm-Benefit analysis[END_REF] propose a metric for assessing expected benefits and animal harm, with 3-level scales.

Expected human benefits:

Small is for an increase in basic biological or medical knowledge. Medium is for new or better treatment for a nonlifethreatening disease. Large is for new or better treatment for a lifethreatening disease.

(Note that in this context of human medical research, only benefits for human health were considered. A similar reasoning could be applied to define other benefits for humans or benefits to animals whereby for instance benefits are qualified high if there is large impacts on animal production, health and welfare (which in turn would benefit to humans).

Expected animal harm:

Mild is for shortterm mild pain or distress with no significant impairment of the well-being or general condition. Moderate is for shortterm moderate pain, suffering, or distress, or long-lasting mild pain, suffering, or distress, likely to cause moderate impairment of the well-being or general condition. Severe is for severe pain, suffering, or distress, or longlasting moderate pain, suffering, or distress, likely to cause severe impairment of the well-being or general condition.

Then the probability that the results can be translated from animals to humans is estimated. The authors propose an explicit weighing scheme to combine the three scores, with a pre-defined threshold above which an experiment shall not be carried out. Such a metric approach allows harmonising the evaluation of protocols. However, it appears very technocratic and it largely limits ethical discussion among committee members. In addition, one can question if a ratio between harms and benefits is adequate to take ethical decisions: if an experiment is supposed to produce intense pain, is it acceptable even if the potential benefits are very high? If the research is of poor quality, can an experiment be carried out because it does not impose any constraints on animal? This raises the question of acceptable minima, which cannot be addressed in a cost/benefit analysis. By contrast, a discourse approach is based on discussions between committee members to assess and weigh the various issues before taking a decision. Such an approach is criticised on the ground that there is no pre-defined method and thus the process lacks transparency, consistency and fairness [START_REF] Grimm | Harm-benefit analysis -what is the added value? A review of alternative strategies for weighing harms and benefits as part of the assessment of animal research[END_REF]. Grimm et al. [START_REF] Grimm | Harm-benefit analysis -what is the added value? A review of alternative strategies for weighing harms and benefits as part of the assessment of animal research[END_REF] recommended mixing the metric and the discourse approaches. A metric approach can guide the discussions among committee members and such discussions can contribute to establish metrics. Summarising the points raised in the present paper, we propose a list of issues to be addressed during an ethical evaluation of a protocol (Table 1). We do not establish scores and let ethical committee members discuss the decision to be taken based on the results of the assessment of each issue.

E -Conclusions and further discussion

There is strong consensus in the scientific community and beyond that the 3Rs are not optional. They need to be addressed in all animal experiments. As mentioned above, this requirement is explicit in EU legislation (Directive 2010/63/UE, Article 1). Taking into consideration ethical issues in animal experimentation shall not be seen as a limitation to experiments but rather as a help to better perform such experiments:

Reducing the imposition of suffering on animals can help to reduce the variability between individuals and to ensure soundness of results. Taking full account of the 3Rs approach helps design adequate studies. The reduction and refinement should be part of the study design. A clear description of what is planned to do helps assessing protocols and increases the robustness and reproducibility of results.

Researchers should not consider ethical requirements as arguments to be filled in an application to an ethical committee. Rather they should include an ethical reasoning when designing their research, as part of their quality system, whereby research is made as efficient as possible in terms of reducing animal use by improving measurement methods -making them more precise -, taking most information from experiments by sharing protocols with other researchers and allowing re-use of samples and data, and making clear account of what has been done. We encourage leaders of research programs and institutions to put in place an 'animal experimentation policy' to encourage following the 3Rs principles and sharing of information between researchers on their methods, their procedures, their experiments and data.

An ethical attitude in research using animals will become even more critical in the context of Responsible Research and Innovation (RRI) introduced by Owen et al. [START_REF] Owen | A Framework for Responsible Innovation[END_REF] and put forward in the Horizon 2020 research program of the EU. The RRI concept is based on: Anticipation of potential impacts of research Reflection on the motivations for a given work and the sets of values related to this work Deliberation with a broad range of stakeholders (sometimes called Inclusion) Responsiveness, that is the ability for adaptive learning As argued by [START_REF] Mcleod | Responsibility and Laboratory Animal Research Governance[END_REF], RRI can help meeting ethical principles in experiments on animals. RRI explicitly recognises the need to assess the potential benefits of a research, it forces clarity regarding values related to assessing harms and benefits, it calls for discussion with a broad range of experts and nonexperts to take decisions about research, as in ethical committees, and calls for addressing adequately values and expectations to refine research projects. Table 1. List of issues to be addressed when evaluating a protocol. This list should help to check that all necessary measures are taken to reduce animal constraints and that the remaining constraints are counterbalanced by the expected benefits from the experiment and the likelihood of obtaining reliable results. Addressing these issues should lead to a discussion among ethical committees to decide to accept or reject a proposed experiment. It can also be used to request scientists to refine their proposal.

Issue Outcome

A -Is there an institution/personal strategy to commit with the 3Rs approach (including checking that no other studies are carried at the same time with a similar approach, reuse of collected data, metaanalysis of published work,…) YES/NO B -How the 3Rs were taken into account in the current work:

Have alternatives to the use of animals been sought and adequately assessed? Is the number of animals at minimum (incl. reliability of how this was calculated) Have the constraints on animals been minimised? YES/NO C -What are the (remaining) harms being imposed on animals, taking into account the sensitivity of the species, the number of animals and the procedures applied (including conditions before experiment)? low -moderate -high D -What is the importance of the expected results: What knowledge will be produced that benefits a given research program or a discipline? Can that knowledge benefit society?

detail the argumentation very likely -maybe -unlikely E -Are the expected results likely to be obtained:

Is the protocol described in sufficient precise terms? Do the experimental design sound and the statistical models ensure to obtain exploitable results? 1If not, ask for more information. YES/NO (NO may lead to rejection or to requesting changes.)

Figure 1 :Figure 2 :

 12 Figure 1: Batch fermenters containing forage substrate and buffered rumen fluid (photo by V. Niderkorn)

Example 2 :

 2 'Four-stars' stalls to measure digestibility in cattle (personal communication from H. Tournadre, INRAE)

Figure 3 :Example 3 :

 33 Figure 3: Four-star stalls to measure digestibility. The access is facilitated by an inclined plane (photo by H. Tournadre).

Figure 5 :

 5 Figure 5: Relation between urinary nitrogen excretion measured by 'gold standard' methods using metabolic cages and either natural 15 N enrichment of animal proteins over the diet (Δ 15 N animal-diet ) or milk urea nitrogen concentration.

Methods in cattle physiology and behaviour research -Recommendations from the SmartCow consortium

The experimental design should be clearly described in terms of number and type of animals per treatment incl. controls. Potential confounding factors should be adequately addressed in the experimental design and/or the statistical models. The statistical models planned shall be able to highlight potential effects with no doubt.

Ethics in experiments on live cattle: a pragmatic approach


Matthieu Bouchon

Alex Bach

Bruno Meunier

Emma Ternman

Kees Van Reenen

Isabelle Veissier

Lene Munksgaard

A checklist to validate sensor output for the recording of cattle behaviour

Keywords:

Introduction

A process of validation assesses the appropriateness and usefulness of a tool for its intended purpose within a specific context. Ideally, the validation of a tool should describe the range of purposes and contexts in which it is appropriate. In general this cannot be accomplished completely. Therefore, when such a wide validation cannot be done, the validation process needs to refer clearly to the purpose of the use of the tool and to which animals it is going to be applied.

The technological development has led to an increase in the number of sensors and devices that are available for measuring cattle behaviour. The technical solutions behind the sensors can differ substantially, sensors use accelerometer technology, sound recording or image analysis to mention some, and even within each solution, there is a large amount of factors that can influence the quality of the sensor's information output or battery capacity. The raw data from the sensor is usually translated through algorithms to estimate the behaviours in question and such algorithms may vary in the way they work. There might be data points for individual animals or whole groups missing for some periods. The attachment of the sensor itself sometimes may affect the animals' behaviour. Furthermore, some sensors are developed for use on commercial farms and others for research use only, with differences in precision and accuracy. A careful evaluation of the purpose and validation of the outputs from sensors for measuring cattle behaviour is required before use (Figure 1). To be able to compare the output from different devices across facilities a standardized validation protocol would be helpful. Therefore, a sensor validation guidance has been included with this chapter which discusses important factors that can affect the outcome of a validation. For instance: be aware that a system that has been validated for small ruminants may not be valid for cattle, and vice-versa. Indeed the anatomy of the animal is already a difference that should be considered when testing a behaviour sensor.

Prerequisites

This guideline is developed in the SmartCow project as collaboration between the partners in working package 7 with input from other partners in the project working with devices that automatically measure behaviour. The guideline is not a detailed description of how to validate specific sensor output, but a list of items to consider, thus it is more of a checklist to consult before a study to validate a sensor for measuring cattle behaviour.

A -Description of the equipment used

In order to compare the outcome of validation studies, it is important that a proper description of the equipment in use is provided. A description should include minimum requirements, described in the two following paragraphs (sensor technology and data from the sensor), and non-exhaustive additional information, which can be added if relevant to interpret the dataset provided by the device. Criteria retained to describe devices have been chosen as a result of literature review of validation studies. We will illustrate most of the retained items by examples taken from the literature or built by our own when nothing relevant was found. Some basic information is needed to describe the sensor, this information is mainly provided by the manufacturer and easy to catch. It can help understanding how the device works and what implication it might have on data acquisition and/or animal behaviour.

1. Type of sensor technology: This information is the most important to describe the sensor under study. Technological solutions vary between sensors, for example accelerometer, Real Time Location System (RTLS), Global Positioning System (GPS), weighing scales -thus it is important to be precise in the technology description. 2. Commercial Name/Company/Version of the Sensor: The aim is to give information about the exact model/version of the sensor used, to easily identify it and make it findable for other applications. This is information given by the manufacturer.

Example: "The acceleration sensor used was the ADXL335 (Analog Devices, One Technology Way, P.O. Box 9106, Norwood, MA 02062-9106, USA), a complete tri-axial accelerometer." [START_REF] Giovanetti | Automatic classification system for grazing, ruminating and resting behaviour of dairy sheep using a tri-axial accelerometer[END_REF] 3. Sensor weight and size, mounting system and recoverability: This is meaningful information to estimate the interaction between the sensor and the natural behaviour of the cow. Indeed, a small lightweight accelerometer mounted on a collar does not have the same impact on cow behaviour as a large and heavy GPS device fixed on a halter. From an ethical and economic point of view, it also seems relevant to describe the recoverability of the sensor, e.g. an intra-ruminal bolus that cannot be taken back from the animal may need specific authorization, as it might be considered an invasive measurement.

Example 1: Moreau [START_REF] Moreau | Use of a tri-axial accelerometer for automated recording and classification of goats' grazing behaviour[END_REF] used GPS tracking collar on goats: "The components were placed in a sturdy casing and mounted on a polyester harness adjustable to the animal's neck. Gross mass of the collar was 610 g." Meunier [START_REF] Meunier | Image analysis to refine measurements of dairy cow behaviour from a real-time location system[END_REF] equipped dairy cows with "a counter-weighed collar (565 g) on which active tag (6×5×4 cm -146 g) was mounted". On these two examples, we can easily assess that 600 g on a goat (which represent 1% of its BW), has not the same impact than 600 g on a dairy cow (which represent approximately 0.1% of its BW).

Example 2: "Rumen pH was monitored continuously throughout the experiment using a commercial sensor […] immersed in the reticulum through the oesophagus with the use of dedicated balling gun." [START_REF] Villot | Relative reticulo-rumen pH indicators for subacute ruminal acidosis detection in dairy cows[END_REF] 4. Memory capabilities and battery life: This point aims at ensuring the device will work well during the validation trial. It has to be expressed in terms of duration. Special attention will be paid to the adequacy between the duration of the study and these two criteria: memory capability and battery life. Additionally, technology used to store data and battery technology may be described.

Example 1: "Onset Pendant G data loggers […] were set to record […] at a 6-s interval until the memory storage in the data loggers was full (i.e., approximately 1.5 d)." [START_REF] Ledgerwood | Evaluation of data loggers, sampling intervals, and editing techniques for measuring the lying behavior of dairy cattle[END_REF] Example 2: "The duration of recording varies between 1.5 and 681.3 d (e.g. 45 d at a sampleinterval of 1 min)." [START_REF] Müller | A new method to measure behavioural activity levels in dairy cows[END_REF] Example 3: "Such batteries would need to operate properly and autonomously for long periods of time (e.g., ve years) without being recharged or replaced." [START_REF] Benaissa | On the use of oncow accelerometers for the classification of behaviours in dairy barns[END_REF] 5. Sampling rate: If known, sampling rate could be useful in understanding how the measurement is done and/or processed (see below). It has to be expressed in terms of frequency or period (e.g. in Hz or points per min).

Example: "The collars were programmed to collect GPS data at 4 Hz (i.e. 345,000 data points/day) and accelerometer data at 10 Hz (i.e. 862,500 data points/day)." [START_REF] González | Behavioral classification of data from collars containing motion sensors in grazing cattle[END_REF] 6. Data storage/transmission. The description of the technology used to transmit data (e.g. wireless transmission such as Bluetooth, Wi-Fi or Radiofrequency, or manual data transmission) is relevant because it can have an influence on cow behaviour: data that are automatically transmitted do not need intervention on the animal, whereas data manually downloaded (USB, SD-card) may disturb the animal. On the other hand, wireless data often entail a loss of data. If data loss occurs, it would be good to quantify and specify when and how much data are missing. A second step to describe the sensor consists in describing the data it provides, as every system has its own way to process, deliver, present, aggregate, etc. the data.

Example 1: On MSR RumiWatch pressure noseband, used to register chewing or ruminating behaviour, data are stored on a SD-card [START_REF] Rombach | Evaluation and validation of an automatic jaw movement recorder (RumiWatch) for ingestive and rumination behaviors of dairy cows during grazing and supplementation[END_REF], [START_REF] Werner | Evaluation of the RumiWatchSystem for measuring grazing behaviour of cows[END_REF]. If there is a need to collect the data during the trial, it could create a disturbance in cow behaviour, as the halter has to be unmounted to download the SD-card through a computer.

Example 2: "The collar-mounted accelerometers […] measurements were gathered once a second using wireless data acquisition network […]. Data packets were then sent to a PC." [START_REF] Martiskainen | Cow behaviour pattern recognition using a three-dimensional accelerometer and support vector machines[END_REF] Example 3: "Data were downloaded every 15 d using eCow handset (smartphone + antenna) with eCow android application." [START_REF] Villot | Relative reticulo-rumen pH indicators for subacute ruminal acidosis detection in dairy cows[END_REF] 7. Nature and type of data collected: The nature of the data obtained using sensor varies: acceleration, voltage, weight, inclination, position, and duration. Moreover, some sensors can provide already processed data, like activity levels or direct behaviour (e.g. ingestion or rumination), or simply filtered or averaged values. Thus, a proper description of the nature (including units) and the type (raw vs processed) is required. Data processing will be described later.

Example 1: "The data recorded by the GPS included the spatial position of the animal on the earth-centered earth-fixed coordinate system (X-, Y-and Z-axis coordinates in cm) the time as in the GPS system, and the 3-dimensional travel speed (cm/s)." [START_REF] González | Behavioral classification of data from collars containing motion sensors in grazing cattle[END_REF] Example 2: "Five variables were recorded by the accelerometers over each epoch: average acceleration in each of the three axes (XavgG, YavgG, ZavgG), Vector Magnitude Average (VMavgG), and Vector Magnitude Max (VMmaxG). Average axis acceleration (XavgG, YavgG, ZavgG) and Vector Magnitude Average (VMavgG) were calculated by summing the inputs (100 samples/s) and dividing by the specied reporting interval (3, 5, or 10 s). Vector Magnitude is calculated by

The VMmaxG is simply the highest combined axis instance per reporting interval." [START_REF] Robert | Evaluation of three-dimensional accelerometers to monitor and classify behavior patterns in cattle[END_REF] 8. Data rate and timestamp/dating: Data rate can be rather different to sampling rate, mainly in cases where data are processed. It can be expressed in terms of frequency, epochs, etc. A precise description of time-and date-related information is also necessary, as it has repercussions on data analysis, and especially in data comparison with gold standard. Indeed, data can be summarized in UTC (Coordinated Universal Time), GMT±h (Greenwich Mean Time), or collected with a non-synchronized clock (e.g. chronometer and sensor synchronized at the beginning of the trial.

Example 1: "The clocks of the observer, the video recording system, and the sensors were synchronized at the start and at the end of the observation period so that observation data could be aligned accurately with the tri-axial accelerometer data retrieved from the sensors." [START_REF] Benaissa | On the use of oncow accelerometers for the classification of behaviours in dairy barns[END_REF] Example 2: "The device is connected to Ethernet to ensure a perfect clock synchronisation using the Network Time Protocol (NTP), dating in the epoch time system." [START_REF] Meunier | Image analysis to refine measurements of dairy cow behaviour from a real-time location system[END_REF] 9. Data processing: Some pieces of information are helpful to interpret the dataset. The point here is not to describe precisely the algorithm used, but more to describe its impact on the dataset. Data can be acquired by a single-shot measurement, but it can also be averaged, filtered, or processed by an algorithm, and thus it can introduce a delay in -for example -data presentation that has to be characterized.

Example 1: Axel Medria normalized dataset present data obtained by the identification of the main behaviour registered during the previous 5 min. For example, if the dataset indicates that the cow was grazing at 0815 h, it means that between 0810 h and 0815 h, the algorithm has calculated that the cow was mainly grazing during this period.

Example 2: Various filters (e.g. Kalman filter, median filter) can be applied to clean the data provided by RTLS, as Pastell [START_REF] Pastell | Filtering methods to improve the accuracy of indoor positioning data for dairy cows[END_REF] does, leading to a reduced data output or data capturing frequency.

10. Data calibration: Some systems need to be calibrated regularly, in order to improve the matching between the physical measurement and the data it produces. This calibration schedule needed has to be expressed in frequency (e.g. monthly).

Example: Weighing scales, like those used in BioControl weighing trough, which basically measure voltages and convert it in weights, need to be calibrated at least monthly to ensure that there is no deviation into the converting process.

For some sensors, a 'training' period can also be necessary. Devices might indeed require an auto-calibration or recalibration period, e.g. an accelerometer need to 'find' earth acceleration to determine the real acceleration direction it records. Manufacturers often provide this information, and a validation study needs to respect at least these minimum requirements.

Example 1: CowView RTLS used fixed tags to auto-evaluate its performance [START_REF] Meunier | Image analysis to refine measurements of dairy cow behaviour from a real-time location system[END_REF], [START_REF] Pastell | Filtering methods to improve the accuracy of indoor positioning data for dairy cows[END_REF], [START_REF] Veissier | Short communication: Early modification of the circadian organization of cow activity in relation to disease or estrus[END_REF].

Example 2: "It records both dynamic accelerations, related to changes in the movements of the sheep and static accelerations (-9.8 m s -2 ) caused by earth's gravity." [START_REF] Giovanetti | Automatic classification system for grazing, ruminating and resting behaviour of dairy sheep using a tri-axial accelerometer[END_REF] 11. Theoretical accuracy, resolution and range of measurement: Manufacturers can provide information on the precision of the measurement made by the sensor. When it is available, it is relevant to characterize what can be expected from the device in use. It can also provide useful information in the discussion of the results obtained from the validation trial.

Vector Magnitude = √XavgG 2 + Y avgG 2 + ZavgG 2
Example 1: CowView RTLS system is given to have an accuracy of 50 cm in detecting the position of an individual in the barn [START_REF] Tullo | Technical note: Validation of a commercial system for the continuous and automated monitoring of dairy cow activity[END_REF], based on the capabilities of its electronic. Meunier [START_REF] Meunier | Image analysis to refine measurements of dairy cow behaviour from a real-time location system[END_REF] have shown that in real condition, it could be better, with a 16 cm precision to detect a precise activity (eating salt).

Example 2: "The accelerometer measured a range of ±3.2 g with an accuracy of 0.075 g." [START_REF] Chapinal | Measurement of acceleration while walking as an automated method for gait assessment in dairy cattle[END_REF]

B -Test environment

This part will provide a description of the important factors to be aware of, both from an animal behaviour point of view and from a technologal point of view. The environment of the animals can have important impact on the results. Ideally, the range of environments in which the tool will provide valid results should be described. Because this can hardly be done, the tool should at least be validated for later use in the same type of environments. A large number of environmental factors can affect the behaviour of cattle, and since many of the sensors in use are measuring the movement of different parts of the body of the animal, it is important to keep the animals in an environment that allows for the movements that later on is in focus. Furthermore, since direct observations or video recordings very often are used as gold standard, the environment should allow for proper observations of the behaviour of the animals. Thus a clear description of housing (including size, floor type, bedding, cubicle type, feeding area etc.), milking, group size, climate conditions etc. should be included in the materials and methods section of a validation study.

Example 1: "Cows were housed in free stalls with mattress and sawdust bedding and concrete slatted floors. They were milked twice daily and supplied with fixed amounts of concentrates and ad libitum roughage." [START_REF] Kok | Technical note: Validation of sensor-recorded lying bouts in lactating dairy cows using a 2-sensor approach[END_REF] Example 2: "Lactating cows were kept in a loose-house system with slatted floor and cubicles with mattresses (Comfi Cushion, with permeable rubber, Egtved, Denmark). The facility was equipped with a free cow traffic automatic milking system (DeLaval, Tumba, Sweden) with an automatic milking unit for each section. Dry cows were kept in pens with deep bedding in the lying area and with slatted floors in front of the feeders." [START_REF] Henriksen | Validation of AfiTagII, a device for automatic measuring of lying behaviour in Holstein and Jersey cows on two different bedding materials[END_REF] From a technological point of view, it is important to consider that some environmental conditions can influence the quality of the dataset. Some information can be relevant to assess that pitfalls have been avoided or taken into account during the validation study. Respect of environmental condition of use of the sensor and its electronics is important. As every electronic devices, sensors are made to operate under given environmental conditions. The sensor first can be sensitive to physical disturbance (e.g. altitude can influence the measurement made by an accelerometer as it modifies its reference acceleration due to a different gravity) and the on-board electronic is also designed to run under appropriate climate conditions (e.g. electronic components are given to run in a precise range of temperature, clock and sensor's precision are often deviating with temperature). This information is often provided by the manufacturer too. It may also imply that a record of the environmental conditions during the study should be recorded and reported.

Example: Medria recommend to use Axel accelerometers between -20° C and +55° C, at an altitude lower than 2,000 m asl.

Some information can be relevant to assess that pitfalls have been avoided or taken into account during the validation trial. Here are some examples of pitfalls that have been avoided before the experiment, or discovered a posteriori, based on users' feedback.

Example 1: When a cow is lying on one side, is the CowView sensor masked by the cow posture or by the cubicle structure? When a cow is in the milking parlour, which is not covered by the antennas, what activity is it associated with? Example 2: Accelerometers interpret feeding behaviour using the inclination of the cow head. In case cows are fed with an automatic concentrate feeder, the angle can be insufficient to detect a feeding behaviour when the animal eats concentrate. Thus, using accelerometers with such feeding systems can lead to poor results in the validation process. This can also be the case with animals grazing in high grass or animals fed on a weighing trough.

Example 3: Gyroscope based sensors are very sensitive to metallic environment, and motions recorded with such devices can be false, whereas UWB signals are absorbed by wood, which can lead to a distortion of the signal.

Example 4: MSR RumiWatch pressure noseband is very sensitive to low temperature and altitude. As they work with propylene glycol, there is a need to ensure that its density is stable and that it is in a liquid state.

In every case encountered, it is essential to observe and annotate abnormal events with the aim to be able to discuss the results.

Example 1: D'Andrea [START_REF] D'andrea | Validation of a pedometer algorithm as a tool for evaluation of locomotor behaviour in dairy Mediterranean buffalo[END_REF] encountered issues of misclassified behaviours due to prolonged activity of body scratching by one cow with the leg equipped of a pedometer.

Example 2: Feeding visit at the weighing trough could be allocated to the wrong animal due to a smart 'animal thief', able to eat over the gate.

C -Ethic and need for permission

Remember to get the permissions needed for the handling and care of the animals included in the validation, and considere whether the impact on the animals' welfare can be justified. These considerations should also include facts about the effects of longer terms use.

D -Animals and feeding

The type of animal (species, age, size, feeding regime, etc.) can have important impact on the results. Ideally, the range of animal types for which the tool will provide valid results should be described.

Because this can hardly be done, the tool should at least be validated for later use with the same type of animals. Therefore, the description of the animals included in the validation needs to include minimum information about the animals and their feeding.

Several animal characteristics to consider during the validation process will help for the interpretation of results:

1. Breed: defining if sensors are tested in dairy and beef ruminants is important since they have different routines that may entail differences in the validation process. 2. Physiological status: animals will behave differently depending of their physiological status (i.e., lactating or not, high vs. low producing milk cows, unhealthy animals). Therefore, including animals in different physiological stages or defining them will be required for the validation process. 3. Animal age: young and adult ruminants have different sizes and routines that may alter the results of the validation or the adaptability of the sensor to the animal. Thus, young and adult animals will require different validations processes.

Example 1: Eating time may differ between high and low producing cows; thus a validation with the use of low producing cows may not tell anything about the validity for cow with a longer eating time.

Example 2: Calves may run and jump more than older animals; thus, a device for measuring movement may not show the same results on calves and cows.

4. Type of diet: the type of feeds animals have access to (i.e., TMR, hay, pasture) should be described to help the interpretation of the validation process.

Example: A sensor that measures eating at pasture may not measure eating in a barn due to differences in the movements of cows when eating.

For the number of animals and the number of observations to be included in the study, see chapter on sample size.

E -Position of the sensor on the animal and need for a habituation period

The position of the sensor on the animal is very important, because in many cases, it is highly correlated with the measurement, and thus with the studied behaviour. A complete description of the position of the sensor should include at least:

1. Anatomic indication (e.g. retro-mandibular microphone, leg-or neck-mounted accelerometer, reticulum pH boluses, ear-tag, etc.) 2. Symmetry (e.g. right/left, front/rear) if relevant.

Example: "accelerometers were attached to the lateral face of the rear leg, just proximal to fetlock" [START_REF] Robert | Evaluation of three-dimensional accelerometers to monitor and classify behavior patterns in cattle[END_REF] In some cases, it could be meaningful to describe the orientation of the sensor. For example, with an accelerometer, indicating where the x-, y-and z-axis are pointing can be essential to understand the data.

Example: "During the experiment, the bold end of the logger always pointed towards the animal's head and the truck ridge pointed to the top. Thus the instrument's X-axis corresponded to the vertical dimension, the Y-axis corresponded to one horizontal dimension, measuring the acceleration sidewise to the left and right, and the Z-axis corresponded to the second horizontal dimension measuring the acceleration forwards and backwards." [START_REF] Moreau | Use of a tri-axial accelerometer for automated recording and classification of goats' grazing behaviour[END_REF] In general, several questions have to be addressed while choosing how to equip the animal with a particular sensor, and could help in describing and justifying how the sensor is placed on the animal.

Which sensor for which position and for which behaviour?

Example 1: Benaissa [START_REF] Benaissa | On the use of oncow accelerometers for the classification of behaviours in dairy barns[END_REF] showed that leg-mounted accelerometers are more accurate than neckmounted accelerometers to detect lying behaviour, whereas it is the opposite in identifying feeding behaviour.

Example 2: For RTLS tag, "the dorsal position was chosen to minimize possible shielding of the signal by the body of the cow." [START_REF] Pastell | Filtering methods to improve the accuracy of indoor positioning data for dairy cows[END_REF] 4. Is there a risk of negative interaction if several sensors are placed on the same mounting system? Does the sensor measure the animal or the device (i.e. collar) behaviour? How to ensure a stable position of the sensor over time?

Example 1: CowView weighted-collar are designed to receive a CowView tag, and ensure its positioning on the top of the cow neck. What would happen if we had a retro-mandibular microphone on this collar? Would the RTLS tag stay at the right place?

Example 2: Some authors have shown that for certain sensors, tightly or loosely mounted collars have no significant impact on the quality of the dataset provided by an accelerometer [START_REF] Oudshoorn | Estimation of grass intake on pasture for dairy cows using tightly and loosely mounted di-and tri-axial accelerometers combined with bite count[END_REF].

5. Is there a known risk of injury by the sensor if placed in a certain position/on certain mounting system? How can it influence the natural behaviour of the animal?

Example: RumiWatch halter is less adapted to young bulls. They may over-express scratching behaviour because the halter embarrasses them.

Lastly, the user needs to describe whether a habituation period is required by the animal (do not confuse with the training period of the sensor, as has previously been described). This can be particularly relevant in case mounting the sensor affects animal behaviour for a few days.

Example 1: For pedometers, D'Andrea [START_REF] D'andrea | Validation of a pedometer algorithm as a tool for evaluation of locomotor behaviour in dairy Mediterranean buffalo[END_REF] applied a 2-day habituation period, allowing cows to return to a normal activity. Rombach [START_REF] Rombach | Evaluation and validation of an automatic jaw movement recorder (RumiWatch) for ingestive and rumination behaviors of dairy cows during grazing and supplementation[END_REF] proceeds similarly with RumiWatch halters, which needed 4 d of habituation for the animal.

Example 2: While giving access to feed into a weighing trough, cows may need a few days to learn the gate access process.

F -How to measure/record the 'gold standard'

The 'gold standard' is the best estimate of the true behaviour performed or true status of the animal that is used to validate the accuracy, precision, etc. of the output of the sensor. The quality of the 'gold standard' is therefore very important for the outcome and sets the limit for the quality of the validation. It may be difficult to get 'gold standards' that are correct/true for some type of behaviour. It is relatively easy to define whether a cow is standing or lying, but determining from either direct observation or video recordings whether a cow is walking, standing or even taking a step can be much more complicated. Feeding behaviour is another example, feeding can be defined as when a cow is chewing or it can also be defined as when a cow has the head above the feeder. The choice of definition of the 'gold standard' may have a huge impact on the outcome of validation. Furthermore, sometimes other types of equipment may provide better 'gold standard' than observations of the behaviour. For instance, may brush rotation provide a better estimate of grooming towards a brush than direct observation of the behaviour? Therefore, providing a careful description on how the 'gold standard' is obtained is important. Furthermore, there is a number of other factors to consider:

1. Description of the behaviour: How does the behaviour in question look like, if including drawings or pictures of the behaviour/position of the animal? 2. The choice of data sampling method, duration, etc. should match the question that is addressed. If the question is whether a specific sensor measures rumination per day, observations of ruminations per day may be enough, and here minor deviations in when rumination start and stop may not be important. If the question is: can the output from this sensor tell me exactly when a cow starts/stops to ruminate, then exact recordings of rumination including start and stop time stamps is needed. 3. The duration of the sampling as the 'gold standard'. In which time windows should data be collected and for how long on each animal. 4. Synchronization of time between recording 'gold standard data' and sensor output. 5. Intra-and inter-observer repeatability should be addressed. Well trained observers are needed; and it is important to check intra-and inter-observer repeatability and report that along with the results.

G -Sample size and analysis

A validation of the output of a sensor or device to automatically measure cow behaviour should include both information about how accurate is the measure (how close to the true value) and how precise is the measure (will repeated measures show the same). Furthermore, there might be a variation in the accuracy and precision depending on the level of the response (e.g. accuracy in the measures of short lying periods may be larger than accuracy in longer lying bouts). Most validations include an estimate of the average accuracy and precision in terms of an expression of the agreement between the gold standard and the automatic measure [START_REF] Borchers | A validation of technologies monitoring dairy cow feeding, ruminating, and lying behaviors[END_REF]. It will be more useful if information about the variation at different response levels is reported (Figure 2). Since we are dealing with live animals, the accuracy and precision may also vary due to variation between animals, e.g. the same sensor may work really well on some cows but not on other cows due to, for instance, slight differences in the position of the sensor. Therefore, it is not a simple task to choose how many animals and how many repeated measures per animal should be included in the validation. In order to choose the sample size consider the following:

1. How is the data distributed and what are the highest and lowest values that you wish to estimate using the equipment? 2. Do the manufacturers suggest a lowest and highest value the device can measure and what is the resolution? 3. Decide, based on 1. and 2., which interval the validation should cover, and the resolution of the 'gold standard' data. 4. Decide whether the validation should give an estimate of the average agreement or better also report the variation in the agreement over the interval the validation shall include. 5. Perform appropriate power analysis, based on 1. or 2. and best estimate of the variation in the response, both within and between animals at a given response level.

It is beyond this guideline to give exact information about power analysis, since this may vary depending on the type of data and the questions that the validation shall address and the methods of analysis. We therefore suggest that you either contact a statistician or study the literature about power analysis.

Figure 2: Illustration of the relationship between sensor data (X-axis) and 'gold standard' (Y-axis), and the variation in the accuracy depending on the response level.

Basically, the analysis of the data should give information about the agreement between the gold standard and the behaviour recorded with the sensor (e.g. the sensor data should predict the behaviour of the animal). Previously, simple correlations coefficient has often been used, but this cannot be recommended. The Bland-Altman method [START_REF] Altman | Practical Statistics for Medical Research[END_REF], [START_REF] Bland | Statistical methods for assessing agreement between two methods of clinical measurement[END_REF] has been used widely in medical research. The most appropriate choice of analysis depends on the type of data (e.g. distribution, continuous or categorical). Another approach is linear regression analysis including a confidence interval. An intercept of 0 and a slope close to 1 will indicate a good agreement, and a proper confidence interval can show the variation at different response levels. Whether this method can be used depends on whether the assumptions are fulfilled.

1. Plot and check the quality of the data, give a clear description of data that eventually are omitted from the data included in the analysis and any other pre-handling of both 'gold standard' data and automatically collected data. 2. Check the distribution of the data. 3. Check the assumptions for choice of statistical model are fulfilled.

H -Robustness of the system in use

Besides the actual validation of the output from a specific device, it will be helpful for other users to have as much information as possible on the following:

1. Effects on the animals: Any injuries on the animals derived from the devices depending on how and where on the animal the sensor is attached, and for how long the sensors have been attached, to the animal to estimate the length of time a specific sensor can be used. 2. Drift in output over time: Some sensors may show a drift for instance in the timestamp or the actual output from the sensor. This type of information should be provided by the manufacturer but, in some instances it may be lacking, any information about this will help other users. 3. Need for calibration: This type of information should be provided by the manufacturer but, in some occasions, it may be lacking, thus any information about this will help other users. 4. Maintenance of the sensor and the system is needed.

Figure 1 :

 1 Figure 1: Illustration of the pathways automatic recording of behaviour and the use as a management tool

Methods in cattle physiology and behaviour research -Recommendations from the SmartCow consortium


Lene Munksgaard

Emma Ternman

Isabelle Veissier

Carol-Anne Duthie

René Baumont

Lying, standing, and eating behaviour

Keywords: leg strap, neck collar, ear tag, real time locating systems (RTLS)

Introduction

Standing and lying behaviours are well-defined. Lying is often described as when the flank or sternum of the animal is in contact with the ground, and end of lying when all four legs are perpendicular to the body (see [START_REF] Ledgerwood | Evaluation of data loggers, sampling intervals, and editing techniques for measuring the lying behavior of dairy cattle[END_REF]). The transition from lying to standing and vice versa requires only a few seconds, and therefore differences in the description of lying do not greatly affect the calculation of time spent lying or standing. By contrast, if the transition between lying and standing is the subject under study, then the description of the behaviour is crucial, especially when one wants to compare results from different studies. For instance, if one investigates the comfort of cubicles, the total duration of lying may reflect the comfort of the cubicle when the animal is lying, while a low frequency of lying bouts may reflect difficulties in lying down/getting up due to poor design of separations [START_REF] Veissier | Cubicle housing systems for cattle: comfort of dairy cows depends on cubicle adjustment[END_REF]. Likewise, standing and walking can be defined in different ways. For instance, counting every second as walking when a leg is moving is not necessarily the same as counting the time when the animal's body is moving forward or backwards.

Eating behaviour can be defined as the whole process by which the animal ingests feeds, able to satisfy organic needs, and rejects non-alimentary or toxic compounds [START_REF] Baumont | Feeding in domestic vertebrates: a comprehensive approach from structure to behaviour[END_REF]. In practice, measuring eating behaviour often consists of assessing the number and duration of eating bouts over a specified time interval. In cattle, eating behaviour can be difficult to describe because they often take small breaks during a meal where they lift their head from the feeder whilst still chewing -or not, and they often move from one location to another to explore and select food. Therefore, a precise description of the variable 'eating' is necessary. One must be specific as to what metric is to be measured over what time interval, as the specific research question will be dependent on this. Sometimes, duration per day is appropriate to address a particular research question, while the frequency of bouts (i.e. sequences when the behaviour is uninterrupted) and average duration of bouts will be more appropriate for a different question. Again these latter metrics can be measured on a whole day or over specified time intervals.

Because there can be large variations in behaviour within and between animals, it is suggested that data should be collected for a few days to get representative estimates of daily lying duration [START_REF] Ito | Lying behavior: assessing within-and between-herd variation in freestall housed dairy cows[END_REF], [START_REF] Vasseur | Sampling cows to assess lying time for on-farm animal welfare assessment[END_REF], [START_REF] Dong | Estimating optimal observational sampling frequency of behaviors for cattle fed high-and low-forage diets[END_REF] or eating behaviour [START_REF] Dong | Estimating optimal observational sampling frequency of behaviors for cattle fed high-and low-forage diets[END_REF]. If eating behaviour is to be combined with feed intake in digestion studies, at least 5-6 d of measurements are necessary to align all measurements (intake, digestibility, etc.). However, different research objectives often require different levels of accuracy and precision.

New equipment for automatic recording of lying/standing/eating behaviour has been developed for both research and commercial use. This increases the available opportunities for collecting data. However, it is not always possible to use sensors for data collection. Direct observations or analysis of video recordings can be a suitable alternative. Continuous focal animal sampling will provide the most accurate and precise data. However, this method is very time-consuming. Therefore, instantaneous scan sampling, where the behaviour of each animal in a group is recorded over a specific time interval, can be more efficient. The choice of sampling method is very important for the accuracy and precision. This is detailed in the book introduction to 'Measuring behaviour' [START_REF] Martin | Measuring behaviour. An introductory guide[END_REF].

Prerequisites

The Animal Trait Ontology for Livestock (ATOL) numbers linked with lying, standing and eating behavior are: ATOL_0000363, ATOL_0000837 and ATOL_0000835 (https://www.atol-ontology.com/en/erter-2/).

A -Measures based on visual observation or video recordings

1. The animals must be marked so that each animal can be identified. For video or visual observation, this can be done by painting numbers or specific symbols or combinations of them on the animal's back and flanks such that they are clearly visible at distance and/or on the video footage. Care must be taken to ensure the identification system remains intact throughout the duration of the study, or reapplied where necessary. This can also be achieved by using collars of different colours or the use of discoloration. 2. Video equipment should be placed and tested to cover the entire area in question, and the number of frames per second adjusted to the behaviour under observation. We recommend 25 fps to achieve video footage which is comfortable to look at whilst being analysed. Nevertheless, 12 fps can be sufficient to detect lying, standing and walking time as well as duration of lying down/standing up movements. If less frames per second are to be used, it is essential to check that the observer will be able to adequately visualise the targeted behaviour from the video footage. 3. It is necessary to establish a clear description (ethogram) of each behaviour. 4. Intra-and inter-observer concordance should be estimated, and the observer(s) trained if needed. 5. The observer should be able to identify both the behaviour and the animal from a position where the presence of the observer does not affect the behaviour of the animals. If the animals are able to see the observer, then they should be acclimatised to the observer's presence, and the observer should adopt smooth movements and speak quietly. 6. If instantaneous scan sampling is used, the interval between scans should reflect the accuracy and precision needed to answer the research question. For frequency of lying bouts, previous research suggests ≤3 min [START_REF] Chen | Technical note: Comparison of instantaneous sampling and continuous observation of dairy cattle behavior in freestall housing[END_REF], and for accurate estimates of duration ≤30 min [START_REF] Chen | Technical note: Comparison of instantaneous sampling and continuous observation of dairy cattle behavior in freestall housing[END_REF] or ≤15 min [START_REF] Dong | Estimating optimal observational sampling frequency of behaviors for cattle fed high-and low-forage diets[END_REF].

For high accuracy and precision estimates of eating duration intervals of 15 min, less than 5 min and 4 min between scan sampling has been suggested [START_REF] Dong | Estimating optimal observational sampling frequency of behaviors for cattle fed high-and low-forage diets[END_REF], [START_REF] Chen | Technical note: Comparison of instantaneous sampling and continuous observation of dairy cattle behavior in freestall housing[END_REF], [START_REF] Madruga | Technical note: Recording rules for behavioral studies in growing heifers fed high-concentrate diets[END_REF]. For estimates of frequency, [START_REF] Chen | Technical note: Comparison of instantaneous sampling and continuous observation of dairy cattle behavior in freestall housing[END_REF] suggest that continuous observations is required. However, both lying and eating behaviour can vary within and between animals due to a variety of factors such as feed type etc., and the shorter the duration of bouts, the shorter the time interval between scans is needed. The authors of [START_REF] Hämäläinen | Measuring behaviour accurately with instantaneous sampling: A new tool for selecting appropriate sampling intervals[END_REF] have developed a software programme that can help in the choice of length of the interval between scans, based on pilot studies.

B -Automated recording of lying, standing and eating

Most available systems to measure standing and lying behaviour are based on accelerometer technology and placed either on the leg (strap), neck (collar) or the ear (tag) of the animal. Eating behaviour can also be measured using accelerometer technology placed on a neck collar or using a noseband pressure sensor to detect jaw movements of the animal. Another option to measure eating behaviour is to combine RFID technology with feed bins placed on a weighting scale. These systems are generally restricted to housed environments. Alternatively, some systems are entirely based on the position of the animal (Real time Locating Systems, RTLS), and use for example the term 'resting' for when the cow is present in a cubicle, and 'feeding' when the cow is next to a trough.

There is an increasing number of commercially available loggers for automatic recording of eating, lying and standing behaviour. For instance, AfiAct Pedometer Plus, CowAlert, Iceqube, and HOBO Data logger use accelerometers to detect the activity of the animal [START_REF] Borchers | A validation of technologies monitoring dairy cow feeding, ruminating, and lying behaviors[END_REF]; Rumiwatch uses a noseband pressure sensor to detect eating [START_REF] Zehner | System specification and validation of a noseband pressure sensor for measurement of ruminating and eating behavior in stable-fed cows[END_REF]; BioControl and Record Feed Intake, HOKO Farm Group Insentec Roughage Intake Control, GrowSafe, and MooSystem Intake Control Feeding Systems utilise feed bins on weighing scales [START_REF] Ternman | A validation study of eating duration assessment from automatic feeder systems[END_REF]; and CowView is an RTLS device [START_REF] Meunier | Image analysis to refine measurements of dairy cow behaviour from a real-time location system[END_REF]. All these systems have been validated by scientists. New loggers from new companies are continually coming onto the market. It is recommended either to use a validated sensor or to perform a validation study before using a new sensor for research purposes [START_REF] Bouchon | Guidelines for validation of sensor output[END_REF].

A leg-mounted logger often estimates standing and lying behaviour more accurately and more precisely compared to when placed on the neck collar or an ear tag. For eating behaviour, systems based on accelerometer technology need to be placed on the neck or the ear. Systems using accelerometer technology are often less accurate than systems that record jaw movements, but there is a significant cost difference between the technologies. All systems need to be carefully validated against direct visual observations, especially when animals can eat without completely dropping their heads down. Recording jaw movements also allows the measurement of rumination behaviour, but needs an appropriate algorithm to separate rumination from eating jaw movements. Automatic feed bins can give accurate estimation of eating duration and number of meals together with the quantification of feed intake, but are less suited to the analysis of more specific feeding behaviours, e.g. to distinguish activities such as taking food and ingestive chewing.

The data granulation level for the sensors also differs. Some sensors provide information per second (Icetags, IceRobotics, Scotland), whereas other systems provide information at for instance 15 min intervals (AfitagII, AfiMilk, [START_REF] Henriksen | Validation of AfiTagII, a device for automatic measuring of lying behaviour in Holstein and Jersey cows on two different bedding materials[END_REF]). It is important to take the technology and the sampling frequency into consideration. Careful examination of the output from the sensors is needed to choose the optimal solution for each experiment.

1. Sensors should be correctly positioned on the animal during the whole sampling period. 2. Cow ID and sensor ID should be carefully related to each other and checked both when attaching the sensor and when removing it. Record any sensor replacements, made during the course of the study. 3. Time synchronisation between sensors and other equipment should be checked regularly and, if needed, adjusted. The best is to synchronise all equipment to the Coordinated Universal Time (UTC). 4. When possible, performing a daily check of data coming from sensors is recommended. 5. It is necessary to check the data to detect outliers and remove them.