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National audience; Les produits animaux occupent une place importante dans notre régime alimentaire en apportant des nutriments indispensables à notre équilibre physiologique. Au-delà de cette qualité nutritionnelle, ils doivent aussi répondre à des objectifs de qualité sanitaire, sensorielle et de service ainsi qu’aux attentes des consommateurs. L’objectif de cet ouvrage est de faire la synthèse des connaissances scientifiques sur les relations entre ces différentes qualités et l’alimentation des animaux. La formulation des régimes alimentaires a évolué pour assurer une qualité optimale des produits issus des élevages tout en satisfaisant au mieux les besoins des animaux. Après un chapitre introductif sur la notion de qualité et son sens actuel, Alimentation des animaux et qualité de leurs produits aborde en 13 chapitres les thématiques suivantes : • Alimentation animale, formulation des régimes et réglementation • Déterminants alimentaires et non alimentaires en élevage de la qualité des produits • Qualité des produits animaux et attente des consommateurs : intégration du volet alimentation et mise en œuvre par les acteurs des filières.

The aim of this study was to quantify the effects of progesterone profile features and other cow-level factors on insemination success to provide a real-time predictor equation of probability of insemination success. Progesterone profiles from 26 dairy herds were analyzed and the effects of profile features (progesterone slope, cycle length, and cycle height) and cow traits (milk yield, parity, insemination during the previous estrus) on likelihood of artificial insemination success were estimated. The equation was fitted on a training data set containing data from 16 herds (6,246 estrous cycles from 3,404 lactations). The equation was tested on a testing data set containing data from 10 herds (8,105 estrous cycles from 3,038 lactations). Predictors were selected to be implemented in the final equation if adding them to a base model correcting for timing of insemination and parity decreased the overall likelihood distance of the model. Selected variables (cycle length, milk yield, cycle height, and insemination during the previous estrus) were used to build the final model using a stepwise approach. Predictors were added 1 by 1 in different order, and the model that had the smallest likelihood distance was selected. The final equation included the variables timing of insemination, parity, milk yield, cycle length, cycle height, and insemination during the previous estrus, respectively. The final model was applied to the testing data set and area under the curve (AUC) was calculated. On the testing data set, the final model had an AUC of 58%. When the farm effect was taken into account, the AUC increased to 63%. This equation can be implemented on farms that monitor progesterone and can support the farmer in deciding when to inseminate a cow. This can be the first step in moving the focus away from the current paradigm associated with poorer estrus detection, where each detected estrus is automatically inseminated, to near perfect estrus detection, where the question is which estrous cycle is worth inseminating?

International audience; As the environments in which livestock are reared become more variable, animal robustness becomes an increasingly valuable attribute. Consequently, there is increasing focus on managing and breeding for it. However, robustness is a difficult phenotype to properly characterise because it is a complex trait composed of multiple components, including dynamic elements such as the rates of response to, and recovery from, environmental perturbations. In this review, the following definition of robustness is used: the ability, in the face of environmental constraints, to carry on doing the various things that the animal needs to do to favour its future ability to reproduce. The different elements of this definition are discussed to provide a clearer understanding of the components of robustness. The implications for quantifying robustness are that there is no single measure of robustness but rather that it is the combination of multiple and interacting component mechanisms whose relative value is context dependent. This context encompasses both the prevailing environment and the prevailing selection pressure. One key issue for measuring robustness is to be clear on the use to which the robustness measurements will employed. If the purpose is to identify biomarkers that may be useful for molecular phenotyping or genotyping, the measurements should focus on the physiological mechanisms underlying robustness. However, if the purpose of measuring robustness is to quantify the extent to which animals can adapt to limiting conditions then the measurements should focus on the life functions, the trade-offs between them and the animal's capacity to increase resource acquisition. The time-related aspect of robustness also has important implications. Single time-point measurements are of limited value because they do not permit measurement of responses to (and recovery from) environmental perturbations. The exception being single measurements of the accumulated consequence of a good (or bad) adaptive capacity, such as productive longevity and lifetime efficiency. In contrast, repeated measurements over time have a high potential for quantification of the animal's ability to cope with environmental challenges. Thus, we should be able to quantify differences in adaptive capacity from the data that are increasingly becoming available with the deployment of automated monitoring technology on farm. The challenge for future management and breeding will be how to combine various proxy measures to obtain reliable estimates of robustness components in large populations. A key aspect for achieving this is to define phenotypes from consideration of their biological properties and not just from available measures.

International audience; Until now, the development of precision livestock farming has been largely based on data acquisition automation. The future challenge is to develop interpretative tools to capitalize on high-throughput raw data and to generate benchmarks for phenotypic traits. We developed a dynamic model of female BW that converts BW time series into a vector of biologically meaningful parameters. The model is based on a first submodel that split a female's weight into elementary mass changes related to biological functions: growth (G component), reserves balance (R component), uterine load (U component), and maternal investment (M component). These elementary weight components are linked to the second submodel, which represents the litter developmental stages (oocyte, fetus, neonate, and juvenile) that drive elementary components of dam weight over each reproductive cycle. The so-called GRUM model is based on ordinary differential equations and laws of mass action. Input data are BW measures, age, and litter weight at birth for each parturition. Outputs of the fitting procedure are a vector of parameters related to each GRUM component and indexed by reproductive cycle. We illustrated the potential application of the model with a case study including growth and successive lactations (n = 202) from 45 dairy goats from the Alpine (n = 27) and Saanen (n = 18) breeds. The fitting procedure converged for all individuals, including goats that went through extended lactations. We analyzed the fitted parameters to quantify breed and parity effects over 4 reproductive cycles. We found significant differences between breeds regarding gestation components (fetal growth and reserves balance). We also found significant differences among reproductive cycles for reserves balance. Although these findings are based on a small sample, they illustrate how use the model can be to adapt herd management and implement grouping strategies to account for individual variability.

Faces are an essential source of information for social species. Sheep are one of the most studiedfarm species in terms of their ability to process information from faces, but little is known abouttheir face-based emotion recognition abilities. We investigated whether sheep could use imagesof faces displaying different emotional states as cues in a simultaneous discrimination task. Tothat end, we took photos of faces of four sheep in three social situations: two with a negativevalence (social isolation or aggressive interaction) and a neutral situation (ruminating in thehome pen). In a two-armed maze, sheep (n=16) were then presented with pairs of images ofthe same familiar individual taken in the neutral situation and one of the negative situations.Sheep had to learn to associate one type of image from a pair with a food reward. Once they hadreached the learning criterion, sheep then had to generalise the task to new pairs of images ofdifferent conspecifics displaying the same emotions as in the previous phase. For every run inthe maze, the latency to choose an arm and the outcome of the choice (success or error) wererecorded, as well as the total number of runs needed to learn the task (learning speed). Influenceof the type of image rewarded and of the side of presentation of the rewarded image wereanalysed by linear mixed models and learning speed was analysed by Mood’s median test. Allsheep learned the task with images of faces. Sheep that had to associate a negative image with areward learned faster that sheep that had to learn the neutral-reward combination (medians: 40vs 75 runs, χ2=4.00, df=1, P=0.046). With the exception of sheep from the Aggression-rewardedgroup, sheep could generalise the discrimination task to images of new faces (F3,26.6=3.37,P=0.033). Sheep chose an arm correctly more often (F1,288.1=5.02, P=0.026) and more quickly(F1,289.3=23.92, P

Chantier qualité GA; Recently, the French National Institute for Agricultural Research appointed an expert committee to review the issue of pain in food-producing farm animals. To minimise pain, the authors developed a ‘3S’ approach accounting for ‘Suppress, Substitute and Soothe’ by analogy with the ‘3Rs’ approach of ‘Reduction, Refinement and Replacement’ applied in the context of animal experimentation. Thus, when addressing the matter of pain, the following steps and solutions could be assessed, in the light of their feasibility (technical constraints, logistics and regulations), acceptability (societal and financial aspects) and availability. The first solution is to suppress any source of pain that brings no obvious advantage to the animals or the producers, as well as sources of pain for which potential benefits are largely exceeded by the negative effects. For instance, tail docking of cattle has recently been eliminated. Genetic selection on the basis of resistance criteria (as e.g. for lameness in cattle and poultry) or reduction of undesirable traits (e.g. boar taint in pigs) may also reduce painful conditions or procedures. The second solution is to substitute a technique causing pain by another less-painful method. For example, if dehorning cattle is unavoidable, it is preferable to perform it at a very young age, cauterising the horn bud. Animal management and constraint systems should be designed to reduce the risk for injury and bruising. Lastly, in situations where pain is known to be present, because of animal management procedures such as dehorning or castration, or because of pathology, for example lameness, systemic or local pharmacological treatments should be used to soothe pain. These treatments should take into account the duration of pain, which, in the case of some management procedures or diseases, may persist for longer periods. The administration of pain medication may require the intervention of veterinarians, but exemptions exist where breeders are allowed to use local anaesthesia (e.g. castration and dehorning in Switzerland). Extension of such exemptions, national or European legislation on pain management, or the introduction of animal welfare codes by retailers into their meat products may help further developments. In addition, veterinarians and farmers should be given the necessary tools and information to take into account animal pain in their management decisions.

Faces of conspecifics convey information about identity, but also gaze, and attentional or emotional state. As a cognitive process, face-based emotion recognition can be subject to judgment bias. In this study we investigated whether dairy goats (n=32) would show different responses to 2-D images offaces of familiar conspecifics displaying positive or negative emotional states. We also examined the possible use of images of faces as stimuli in cognitive bias studies. The faces of four subjects were photographed in a positive and a negative situation. Three types of images of ambiguous facial expressions were then created using morphing software (75% positive, 50% positive, and 25%positive). In a test-pen, each goat was exposed for 3 seconds to each type of image, obtained from the same goat. All goats were shown non-morphed faces first, before being shown the three types of morphed faces, balanced for order. Finally, the first non-morphed face was shown again. Spontaneous behavioural reactions including ear postures (forward, backward and asymmetrical) and interactions with the screen (time spent looking or touching) were recorded during the 3 seconds. Results were analysed using REML with repeated measurements. Goats spent more time with their ears forward when the negative was shown compared to the positive(F4,121.3 = 2.51, P = 0.018), indicating greater interest in negative faces. Identity of the photographed goat influenced the time spent with the ears forward (F2,57.4 = 7.01, P = 0.002). We conclude that goats react differently to images of faces displaying different emotional states and that they seem to perceive the emotional valence expressed in these images. Response to morphed faces was not necessarilyintermediate to response to negative and positive faces, and not on a continuum. Further study is thus needed to clarify the potential use of faces in cognitive bias studies.

Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a) whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b) whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emotional states of neutral (ruminating in the home pen) or negative valence (social isolation or aggressive interaction). Sheep (n = 35) first had to learn a discrimination task with colored cards. Animals that reached the learning criterion (n = 16) were then presented with pairs of images of the face of a single individual taken in the neutral situation and in one of the negative situations. Finally, sheep had to generalize what they had learned to new pairs of images of faces taken in the same situation, but of a different conspecific. All sheep that learned the discrimination task with colored cards reached the learning criterion with images of faces. Sheep that had to associate a negative image with a food reward learned faster than sheep that had to associate a neutral image with a reward. With the exception of sheep from the aggression-rewarded group, sheep generalized this discrimination to images of faces of different individuals. Our results suggest that sheep can perceive the emotional valence displayed on faces of conspecifics and that this valence affects learning processes.

Les préoccupations actuelles liées aux rejets dans l’environnement d’éléments liés aux activités d’élevage, soulèvent la question de la précision de leur prévision. C’est en particulier le cas des rejets d’azote fécal (Nfec) et urinaire (Nur) par les ruminants. Le projet INRA Systali de rénovation des systèmes d’unités alimentaires des ruminants se distingue des précédents par le fait qu’il prend mieux en compte, et de façon quantitative, les phénomènes biologiques majeurs liés à la digestion des aliments et à la métabolisation des nutriments. Il a donc semblé opportun de chercher à tirer profit de la meilleure « mécanisticité » du modèle Systali pour prévoir plus précisément à l’échelle d’un animal moyen, les niveaux des rejets azotés fécaux et urinaires et en tirer un moyen de diagnostic affiné sur le terrain. Un sous-modèle spécifique de prévision des rejets Nfec et Nur a été mis en en place au sein des calculs des rations, des besoins des animaux et de leurs réponses aux pratiques alimentaires. Pour les rejets Nfec le calcul utilise directement certains paramètres digestifs du système PDI: les protéines alimentaires non dégradées dans le rumen (PIA), les protéines microbiennes (PIM) et la fraction NDF non digestible de la ration. Pour les rejets d’Nur, une approche factorielle permet de quantifier de façon séparée l’ensemble des facteurs impliqués. En particulier, il est possible de prédire les deux principales origines digestive et métabolique de Nur. L’origine digestive principale est liée au niveau de gâchis d’N dans le rumen, elle est quantifiée par le nouveau paramètre BalProRu qui correspond au bilan protéique du rumen. L’origine métabolique est appréhendée à travers l’efficacité des PDI qui peut largement varier (moins de 50% à plus de 80%), tout en présentant la même valeur pour l’ensemble des fonctions de protéosynthèse de l’organisme (Sauvant et al., 2015). Ces variations d’efficacité des PDI permettent d’en déduire celles de leur inefficacité qui est à l’origine de Nur d’origine métabolique. Cette approche factorielle de Nur permet non seulement d’obtenir une prédiction fiable (ETR = 0,02 et 0,05 gNur/kgPV pour les vaches et chèvres respectivement) de son niveau mais également d’avoir une idée du poids relatif des différentes origines digestive ou métabolique pour en déduire un diagnostic de ration., Current concerns related to environmental releases of elements related to livestock productions, raise the question of the accuracy of their predictions. This is particularly the case for nitrogen losses in feces (Nfec) and in urine (Nur) by ruminants. The INRA Systali project of updating the feed unit systems for ruminants differs from the previous one because it better takes into account, and quantitatively, the major biological phenomena related to feed digestion and nutrient metabolism. It therefore seemed appropriate to seek to benefit from the improved "mechanisticity" of the systali model to more accurately predict the Nfec and Nur losses and make a precise diagnosis on the field. A specific sub-model of Nfec and Nur losses was set up in the processes of calculations of rations, requirements of animals and their responses to dietary practices. For Nfec losses the calculation directly uses the digestive parameters of the PDI system: dietary protein not degraded in the rumen (PIA), microbial proteins (PIM) and non digestible NDF fraction of the ration. For losses of Nur, a factorial approach quantifies separately all the factors involved. In particular, it is possible to predict the two main digestive and metabolic origins of Nur. The main digestive origin is related to the level of N excess in the rumen, it is predicted by the new "BalProRu" parameter (protein balance in the rumen). The metabolic origin is tackled through the PDI efficiency which may vary widely (from less than 50% to over 80%), while having the same value for all of the body's protein synthesis functions (Sauvant al., 2015). These PDI efficiency variations allow inferring those of their inefficiency which is the major cause of metabolic origin of Nur losses. This factorial approach of Nur not only provides a reliable prediction of its level, but also gives an idea of the relative weight of the different origins, digestive or metabolic, of Nur to deduce a diagnosis of ration.

A meta-analysis on the influence of dietary lipid or fatty acid (FA) contents on beef FA composition was conductedusing the “ω3Meat” database. This database contains bibliographic data posterior to year 2000 related to the impact ofcattle farming system parameters on beef FA composition. The results of the meta-analysis pointed that 1) Theproportion of C18:3 n-3 present in cattle muscle is directly proportional to its percentage in the diet and to the fatcontent of the diet, 2) Diet lipid content seems to be the most important factor of variation of n-6 PUFA and trans FApresent in cattle muscle. Thus, meta-analysis is a useful tool to assess and summarize the knowledge to accuratelypredict FA composition of ruminant meat even in rearing conditions.

National audience; Objectifs. Les systèmes d’expression des besoins et de la valeur des aliments pour les ruminants (UF pour l’énergie, PDI pour les protéines, et UE pour l’ingestion) ont fait leurs preuves, mais ils présentaient des limites qu’il convenait de lever pour répondre à la multiplicité des enjeux en matière de nutrition des ruminants, et pour élargir leurs zones d’influence au niveau européen et international. Le projet Systali, initié en 2010, avait pour objectif d’aboutir à une révision des systèmes d’alimentation pour Ruminants. Ces nouveaux systèmes seront plus précis, dynamiques et évolutifs, tenant mieux compte des interactions digestives et métaboliques. Ils seront applicables à une plus grande diversité de contextes y compris en zone tropicale, pour piloter la production et l’efficacité. L’objectif était également d’adosser à ces systèmes rénovés 3 modules : un module de prévision de la réponse moyenne à l’alimentation de la composition des produits (taux protéique du lait, teneur en matières grasses et qualité de la matière grasse des produits lait et viande) ; un module d’évaluation des risques d’acidose et des recommandations permettant de limiter ce risque ; et un module de prévision des rejets (CH4, N urinaire et fécal).Méthodes. De larges bases de données comprenant des centaines de résultats de mesures de la digestion, de bilans métaboliques et des performances animales, représentatives des pratiques alimentaires courantes, ont été construites et interprétées par des approches statistiques homogènes et bien tracées, permettant de dissocier la variabilité intra vs inter expérience. Les équations empiriques issues des différentes méta-analyses ont été intégrées dans des modèles mécanistes pour assurer leur cohérence interne ; ces modèles ont ensuite été couplés en conservant un principe de construction « apports vs besoins », dans un outil de simulation dédié, permettant un contrôle de la cohérence globale de l'ensemble des nouveaux systèmes, pour une large gamme de pratiques alimentaires et de caractéristiques animales.

International audience; Chronic stress is considered detrimental for an individual as it is a long-lasting negative emotional state, without or with a limited habituation. The reactivity and sensitivity of animals to stressors depend on the animal's organismic characteristics such as sex. In poultry, the studies dealing with chronic stress were mainly performed on females. Our study then focused on male quail and aimed at assessing the effect of unpredictable and repeated negative stimuli (URNS) on their general activity, tonic immobility, emotional reactivity to a human, a novel object, novel foods or when restrained in a crush cage, as well as on their plasma corticosterone concentrations. Quail were then left undisturbed or submitted to URNS during 6 weeks (n = 12 in each group). The results indicated that disturbed males spent a greater proportion of time far from the human than control ones (on the 1st test, 44.23 ± 5.28 vs 21.80 ± 6.12%, P = 0.01), probably to avoid the human. Disturbed males pecked at the novel object latter (P = 0.03) and less (P = 0.05) than controls. When restrained in a crush cage, disturbed quail were more often motionless than controls (13.49 ± 4.57 vs 4.76 ± 2.11%, P = 0.05). Disturbed quail ate a greater cumulative amount of mealworms (P = 0.05) or ate red maggots with a shorter latency compared to controls (P < 0.05 for the 2nd and 3rd red maggots, on the 2nd test). Concerning the general activity, disturbed males only showed less stereotypic behaviour than control ones after 14 days with URNS (1.4 ± 0.4 vs 4.9 ± 1.2% respectively, P = 0.03), but this difference disappeared after 34 days with URNS (P > 0.1). More importantly, stereotypic behaviours represented less than 5% of the time budget of both groups. URNS had however no effect on tonic immobility, general activity and corticosterone concentrations. This study demonstrated that URNS induced an increase of male quail's emotional reactivity to a human (when tested for the 1st time), to a novel object and when restrained in a crush cage. URNS also altered male quail's feeding behaviour. Disturbed quail were more interested by the novel foods than control quail presumably because they considered them as positive rewards after repeated exposures and they used them as a way to compensate their negative emotional state. All in all, our results demonstrated that URNS induced a chronic stress state in male quail that can have negative consequences on their welfare.

National audience; Un travail de méta-analyse a été engagé pour revoir le calcul des valeurs d’acides aminés digestibles dans l’intestin (AADI) dans le projet INRA Systali de révision des systèmes d’alimentation des ruminants. Le calcul des valeurs AADI dépend des calculs des flux de protéines digestibles dans l’intestin d’origine microbienne (PDIM) et alimentaire (PDIA), or ces valeurs ont été modifiées dans Systali. Une nouvelle base de données contenant des essais mesurant les flux d’acides aminés (AA) dans le duodénum a été constituée. La même démarche de calculs que celle choisie par Rulquin et al. (1998, 2001) a été appliquée. La première étape de la démarche a consisté en un calcul théorique des concentrations en AA dans le duodénum basé sur une approche factorielle des flux de PI d’origine microbienne (PIM), alimentaire (PIA) et endogène (PIendo) et de leurs compositions (%) respectives en AA. Ce calcul théorique a alors été confronté aux concentrations mesurées dans le duodénum par la méta-analyse. Des facteurs de correction ont été estimés à partir d’une analyse de covariance avec un effet essai fixe et un modèle linéaire. Les nouveaux modèles ont permis d’améliorer la prédiction des concentrations d’AA mesurées avec des erreurs de prédiction des modèles plus faibles que les modèles passés pour les 16 AA considérés dans le système AADI. De plus, les nouvelles estimations des PI appliquées à la nouvelle base de données ont permis de réduire les biais entre les concentrations calculées et mesurées et d’appliquer des facteurs de correction moins importants. Au final, 15 équations sur 16 (à l’exception de la Phe) présentaient des ordonnées à l’origine plus proche de zéro et des pentes plus proches de 1 que les modèles passés. Les 16 nouvelles équations de correction (incluant celle de la Phe) sont utilisées dans le calcul des 16 valeurs AADI de Systali.

Programme Pour et Sur le Développement Régional 4; La France est le premier producteur de lait de chèvre en Europe. Le Grand Ouest représente 54% de cette production nationale et près de la moitié de l’effectif de chèvres.Cependant, les systèmes caprins peuvent être fragilisés par leur relative faible autonomie alimentaire. Le projet Flèche vise à renforcer la durabilité des filières caprines laitières du Grand Ouest par une plus grande utilisation de l’herbe dans les élevages.Flèche est basé sur un partenariat fort entre acteurs du territoire, interprofession caprine, unités de recherches, organismes de développement et établissements d’enseignement secondaire et supérieur.

The evolution of feeding systems for ruminants towards evaluation of diets in terms of multiple responses requires the updating of the calculation of nutrient supply to the animals to make it more accurate on aggregated units (feed unit, or UF, for energy and protein digestible in the intestine, or PDI, for metabolizable protein) and to allow prediction of absorbed nutrients. The present update of the French system is based on the building and interpretation through meta-analysis of large databases on digestion and nutrition of ruminants. Equations involved in the calculation of UF and PDI have been updated, allowing: (1) prediction of the out flow rate of particles and liquid depending on the level of intake and the proportion of concentrate, and the use of this in the calculation of ruminal digestion of protein and starch from in situ data; (2) the system to take into account the effects of the main factors of digestive interactions (level of intake, proportion of concentrate, rumen protein balance) on organic matter digestibility, energy losses in methane and in urine; (3) more accurate calculation of the energy available in the rumen and the efficiency of its use for the microbial protein synthesis. In this renewed model UF and PDI values of feedstuffs vary depending on diet composition, and intake level. Consequently, standard feed table values can be considered as being only indicative. It is thus possible to predict the nutrient supply on a wider range of diets more accurately and in particular to better integrate energy x protein interactions occurring in the gut.

Some dairy farmers opt to omit one milking, either incidentally or weekly, without changing other milking times. This practice entails an extended milking interval of 24 h (24h-MI), which is associated with a decrease in milk yield. This decrease varies among cows and could be partly due to factors such as stage of lactation and milk yield level. The aim of this study was to describe the average and individual responses in terms of loss and carryover effects of a 24h-MI on milk yield. The influence of factors such as parity, stage of lactation, and milk yield potential were investigated, together with response repeatability. Our trial used 292 Holstein-Friesian cows, and consisted of 3 successive periods: 1 wk of twice-daily milking (TDM) as a control, one 24h-MI, and then 13 d of TDM. The number of observations per cow ranged from 1 to 9, with no more than three 24h-MI per lactation. The 24h-MI reduced milk yield by 23% (7.8 kg on average) and milk lactose content by 2.6 g/kg on the 24h-MI day. Milk fat and protein content, and somatic cell score increased by 3.0 g/kg, 0.5 g/kg, and 0.4 units, respectively. No significant carryover effect was found of a 24h-MI on milk yield or milk composition 2 wk after resumption of TDM. Milk yield loss and recovery varied widely (coefficient of variation 62%), and the relationship between milk loss and milk recovery showed substantial variation (residual standard deviation 2.1 kg/d). Cows with a greater milk potential level lost more milk yield but recovered more milk, with no influence on recovery:loss ratio. Cows in early lactation recovered the lost milk yield faster. Repeatability of the responses to a 24h-MI was 44% for milk yield loss (kg/d), 57% for relative milk yield loss (%), 33% for milk yield recovery (kg/d), and 0% for milk recovery:loss ratio (%), suggesting a genetically determined ability to limit loss when one milking is omitted. To conclude, a 24h-MI caused higher milk yield losses than reported in previous studies. Stage of lactation, estimated potential milk yield level, and parity explained the cows' response to the 24h-MI, but did not account for all the individual variability.

The aim of this study was to gain a better understanding of the variability in shape and features of all progesterone profiles during estrus cycles in cows and to create templates for cycle shapes and features as a base for further research. Milk progesterone data from 1418 estrus cycles, coming from 1009 lactations, was obtained from the Danish Cattle Research Centre in Foulum, Denmark. Milk samples were analyzed daily using a Ridgeway ELISA-kit. Estrus cycles with less than 10 data points or shorter than 4 days were discarded, after which 1006 cycles remained in the analysis. A median kernel of three data points was used to smooth the progesterone time series. The time between start of progesterone rise and end of progesterone decline was identified by fitting a simple model consisting of base length and a quadratic curve to progesterone data, and this luteal-like phase (LLP) was used for further analysis. The data set of 1006 LLP's was divided into five quantiles based on length. Within quantiles, a cluster analysis was performed on the basis of shape distance. Height, upward and downward slope, and progesterone level on Day 5 were compared between quantiles. Also, the ratio of typical versus atypical shapes was described, using a reference curve on the basis of data in Q1–Q4. The main results of this article were that (1) most of the progesterone profiles showed a typical profile, including the ones that exceeded the optimum cycle length of 24 days; (2) cycles in Q2 and Q3 had steeper slopes and higher peak progesterone levels than cycles in Q1 and Q4 but, when normalized, had a similar shape. Results were used to define differences between quantiles that can be used as templates. Compared to Q1, LLP's in Q2 had a shape that is 1.068 times steeper and 1.048 times higher. Luteal-like phases in Q3 were 1.053 times steeper and 1.018 times higher. Luteal-like phases in Q4 were 0.977 times steeper and 0.973 times higher than LLP's in Q1. This article adds to our knowledge about the variability of progesterone profiles and their shape differences. The profile clustering procedure described in this article can be used as a means to classify progesterone profiles without recourse to an a priori set of rules, which arbitrarily segment the natural variability in these profiles. Using data-derived profile shapes may allow a more accurate assessment of the effects of, e.g., nutritional management or breeding system on progesterone profiles.

Dans le cadre de la révision des systèmes d’unités d’alimentation des ruminants (projet INRA « Systali »), on a revisité les valeurs des besoins énergétiques d’entretien et d’efficacité de l’utilisation de l’énergie métabolisable (EM) par les femelles laitières, vaches et chèvres essentiellement. Les résultats de la base de mesures calorimétriques « Rumener » ont été utilisées pour ces analyses. L’actualisation du calcul de l’EM a été publiée auparavant (Sauvant et Nozière, 2013). Les besoins d’entretien sont accrus par rapport aux références antérieures : 145 vs 117 kcal EM/kg PV0,75 et 94,3 vs 70 kcal ENetteLait/kg PV0,75 pour les vaches laitières et 110 vs 109 kcal EM/kg PV0,75et 71,5 vs 65,3 kcal ENL/kg PV0,75pour les chèvres laitières. Pour l’efficacité k de la transformation de l’EM en ENL les résultats montrent que les valeurs relatives aux vaches et aux chèvres sont identiques. Pour les animaux en bilan d’énergie positif, l’efficacité kls spécifique de l’EM en EN lait est inférieure à celle de l’EM pour la rétention d’énergie kg. On a en moyenne kls = 0,65 et kg = 0,80. En outre, d’après les données, kg n’est pas différent de kt, l’efficacité de l’utilisation des réserves énergétiques en lait. On les a donc regroupées en un seul coefficient commun kgt lié à kls : kgt = kls + 0,15.D’autre part, le traitement des données a fait apparaitre une différence dans la prévision des valeurs de kls en fonction de q=EM/EB par rapport à l’équation utilisée auparavant : kls = 0,65 + 0,247 (q – 0,63). L’application de cette équation à l’orge de référence, utilisée depuis 1987, aboutit à un léger accroissement de la valeur UFL de référence 1760 Kcal lait/kg brut (vs 1700). Pour les valeurs UFV, l’application des relations Systali et des coefficients kmf précédents aboutit aussi à la valeur de 1760 kcal. Ces dernières modifications présentent un impact mineur sur la valeur UFL du lait de référence à 750 kcal : 0,43 vs 0,44 UFL., As part of the revision of the ruminant feed unit systems (INRA project "Systali"), it was decided to revisit the energy requirements and efficiency of the metabolisable energy (ME) used in dairy females, especially cows and goats. For this we used the "Rumener" database for calorimetric records. The new calculation of ME from Gross Energy (GE) has been proposed previously (Nozière and Sauvant, 2013). Maintenance requirements have increased compared to previous values: 145 vs 117 kcal ME/kg LW0,75 and 94.3 vs 70 kcal NEL/kg LW0,75 for dairy cows and 110 vs 109 kcal ME/kg LW0,75 and 71.5 vs 65.3 kcal NEL/kg LW 0,75 for dairy goats. For the efficiency of transformation of ME to NE, k, the data show the same values for cows and goats. For animals with a positive energy balance, the kls values, the specific efficiency of ME into milk energy, were lower than those of energy retention, kg. Mean values are kls = 0.65 and kg = 0.80. Moreover, according to the data, kg was not different from the efficiency of body energy mobilization, kt, into milk energy. Therefore they were pooled into a common value ktg linked with kls: kgt = kls + 0.15. On the contrary, the equation of prevision of kls as a function of q = ME/GE was found to be different from the previous one: kls = 0.65 + 0.247 (q – 0.63). The application of this equation to the reference barely used since 1987 led to a small increase of the energy equivalent of one UFL: 1760 milk kcal (vs 1700). For the feed unit for meat (UFV), the application of the Systali equations to the previous kmf coefficient also provided a mean value of 1760 kcal for one UFV. These last modifications have only a small impact on the UFL value of the reference milk of 750 kcal: 0.43 vs 0.44 UFL.

Etude de la variabilité inter-laboratoire de la dégradation de l'azote mesurée in sacco. 22. Rencontres autour des Recherches sur les Ruminants

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International audience; Resilience is the ability of an animal to cope with environmental disturbances, such as pathogens or negative energy balance. To improve resilience through breeding, we need resilience indicators. Functional longevity might be a good indicator of a dairy goat's lifetime resilience as it results from the ability to cope with and recover from all the challenges faced throughout its life-time. The aim of this study was to validate the use of functional longevity as an indicator of resilience for selection. To address this question, we created 2 genetic lines of Alpine goats using hyperselected artificial insemination bucks with the most extreme estimated breeding values for functional longevity arid the same milk yield performance. A total of 440 goats, 228 in the high longevity (high_LGV) and 221 in the low longevity (low_LGV) lines, were bred and monitored for 4 yr. Health treatments, serum IgG concentration as a proxy of passive immune transfer in early life, kidding, age, and reason of culling were systematically noted. Weight and body morphology were monitored. Weight arid growth during the first year of life were similar in both goat lines. In contrast, the low_LGV goats had a lower weight during the beginning of first lactation than high_LGV goats. The milk fat-to-protein ratio was also significantly higher in low_LGV goats during first lactation. A multivariable Cox regression was fitted to the data to decipher survival at different stages of life in the 2 lines. The overall survival of high_LGV goats was significantly better than low_LGV goats (hazard ratio = 0.63, confidence interval = 0.47; 0.86) even after we included treatment, growth, serum IgG concentration at birth, and year effects in the model. The line effect was riot constant over time; no significant effect was found during the first year, and the difference was observed after first kidding. This result suggested that survival at an early stage of life and during later productive life are under different genetic regulation. Altogether, this monitoring of the goat lines indicated that functional longevity-based selection helps to improve resilience by improving survival and mitigating some indicators of fat mobilization during early lactation.

International audience; WAIT4: Welfare: Artificial Intelligence and new Technologies for Tracking key indicator Traits in animals facing challenges of the agroecological Transition Objectives of the WAIT4 project: 1/ Real-time analysis of AW indicators under different environments (indoor, outdoor, grazing, loose, organic farming) and climates (continental, harsh, tropical), in response to AE practices and 2/ Defining early alerts for deteriorated AW and evaluation of improved welfare

Fibrobacter succinogenesis a cellulolytic predominant bacterium that plays an essential role in the degradation of plant fibers in the rumen ecosystem. It converts cellulose polymers into intracellular glycogen and the fermentation metabolites succinate, acetate, and formate. We developed dynamic models ofF. succinogenesS85 metabolism on glucose, cellobiose, and cellulose on the basis of a network reconstruction done with the Automatic Reconstruction of metabolic models (AuReMe) workspace. The reconstruction was based on genome annotation, 5 templates-based orthology methods, gap-filling and manual curation. The metabolic network ofF. succinogenesS85 comprises 1565 reactions with 77% linked to 1317 genes, 1586 unique metabolites and 931 pathways. The network was reduced using the NetRed algorithm and analyzed for computation of Elementary Flux Modes (EFMs). A yield analysis was further performed to select a minimal set of macroscopic reactions for each substrate. The accuracy of the models was acceptable in simulatingF. succinogenescarbohydrate metabolism with an average coefficient of variation of the Root mean squared error of 19%. Resulting models are useful resources for investigating the metabolic capabilities ofF. succinogenesS85, including the dynamics of metabolite production. Such an approach is a key step towards the integration of omics microbial information into predictive models of the rumen metabolism.

The rumen ecosystem harbours a galaxy of microbes working in synthrophy to carry out a metabolic cascade of hydrolytic and fermentative reactions. This fermentation process allows ruminants to harvest nutrients from a wide range of feedstuff otherwise inaccessible to the host. The interconnection between the ruminant and its rumen microbiota shapes key animal phenotypes such as feed efficiency and methane emissions and suggests the potential of reducing methane emissions and enhancing feed conversion into animal products by manipulating the rumen microbiota. Whilst significant technological progress in omics techniques has increased our knowledge of the rumen microbiota and its genome (microbiome), translating omics knowledge into effective microbial manipulation strategies remains a great challenge. This challenge can be addressed by modelling approaches integrating causality principles and thus going beyond current correlation basis approaches applied to analyse rumen microbial genomic data. However, existing rumen models are not yet adapted to capitalise on microbial genomic information. This gap between the rumen microbiota available omics data and the way microbial metabolism is represented in the existing rumen models needs to be filled to enhance rumen understanding and produce better predictive models with capabilities for guiding nutritional strategies. To fill this gap, integration of computational biology tools and mathematical modelling frameworks is needed to translate the information of the metabolic potential of the rumen microbes (inferred from their genomes) into a mathematical object. In this review, we discuss computational biology tools to analyse the rumen microbiome and two modelling approaches for the integration of microbial genomic information into dynamic models. The first modelling approach explores the theory of state observers to integrate microbial time series data into rumen fermentation models. The second approach is based on the genome-scale network reconstructions of rumen microbes. For a given microorganism, the network reconstruction produces a stoichiometry matrix of the metabolism. This matrix is the core of the so-called genome-scale metabolic models which can be exploited by a plethora of methods comprised within the constraint-based reconstruction and analysis (COBRA) approaches. We will discuss how these methods can be used to produce the next generation models of the rumen microbiome.

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International audience; Nutritional strategies, including feed management measures, are promising methods for CH4 and overall GHG reduction. Evidence from literature is reviewed in this article in relation to the effects of forage quality (digestible organic matter, DOM) and forage type (grasses vs. legumes, and maize). The major determinants of forage quality are botanical composition and phenological stage, i.e., at advanced growth stages of plants, the fibre content increases while DOM decreases. Methane yield (g/kg DMI) decreases with increased digestibility of forages in both dairy cattle and sheep, and also CH4 intensity (g/kg milk) decreases with increased digestibility of forages for dairy cattle. Using forage legumes in ruminant feeding systems can reduce overall GHG emissions due to decreased N fertilizer use and related emissions. Recommended dietary mitigation measures are often related to a reduction in N excretion such as better matching of dietary protein to animal needs, shifting N excretion from urine to faeces (by tannin inclusion at low levels) and reducing the amount of excreted fermentable organic matter. Methane decreases with increasing intake of forage legumes rich in tannins and there is a shift of N partition from urinary N towards faecal N. Reduced CH4 emissions from ruminants fed on forage-based diets will decrease the carbon footprint of livestock and agriculture and improve the efficiency of productive ruminants in both developing and developed countries. Likewise, estimations of net CH4 output should account for enteric CH4 emissions and soil carbon (C) sequestration of land used for feed production (i.e., grasslands and croplands).

International audience; Feed efficiency (FE) is a complex phenotype made up of multiple traits for which there is potential for substantial genotype by environment interaction (G & times; E). The objective of this study is to evaluate the extent of G & times; E for FE traits with a simulation approach. We used a mechanistic model of the dairy cow that simulates trajectories of phenotypes throughout lifetime, depending on trajectories of resource acquisition and allocation, driven by 4 genetic scaling parameters, and depending on the nutritional environment (quantity and quality of feed resources). The cow model, calibrated for a grass-based farming system and seasonal calving, was combined with a genetic module. This simulated genetic variation in the 4 genetic scaling parameters related to resource acquisition and allocation, based on a simple balanced pedigree structure (200 paternal half-sib groups each of 100 daughters). The population of 20,000 cows generated was simulated in 4 nutritional environment scenarios, representing a gradient of feeding constraints. In each scenario, 6 traits derived from the model outputs were analyzed to obtain population genetic parameters. Genetic correlations between second-lactation production and FE were positive and high in all scenarios and increased as the nutritional environment became more constraining. A measure of lifetime FE was positively correlated with second -lactation production under a less constrained environment, but these correlations decreased as the environment became more constraining. The genetic correlation between body reserves at second calving, and lifetime FE was positive and low in the least constraining scenario and increased as the environment became more constraining. In addition to genetic parameters, we looked at the distributions of acquisition and allocation pa rameters among the best performing cows for lactation and life FE, in the 2 most contrasted scenarios. The 4 subpopulations of best cows had acquisition and allocation strategies different from the whole population. In conclusion, this simulation study identifies the potential underlying biological basis for important G & times; E in FE traits. This highlights the importance of having a balanced breeding goal when undertaking selection that should also be based on phenotypes relevant to the environment.

The rumen harbours countless bacteria, archaea, ciliated protozoa, fungi and viruses: various microorganisms that have established multiplicity of relationships to efficiently digest complex plant fibres and polysaccharides to produce volatile fatty acids (VFAs), microbial proteins and vitamins, essentials for the host’s health, growth and performances. Recent studies using omics-based techniques have revealed that changes in rumen microbiota are associated with changes in ruminants’ production and health parameters such as feed efficiency, methane yield, milk composition and ruminal acidity. However, traditionally, rumen microbes were unveiled using anaerobic culture-based techniques, which are at the origin of most of the basic concepts and understanding of the rumen functioning. Isolating and culturing microbes is frequently more difficult and time-consuming and requires more training than molecular techniques, which explains why culture seems to be abandoned in favour of sequencing. Microbial cultures enable the study of substrate preferences and product output, essential growth requirements, biocide production and susceptibilities; obtaining a pure culture also enables genome sequencing of these strains. We propose here, after a brief report of published rumen isolates, a comprehensive review of current advances in molecular methods to identify novel rumen microbes and discuss how culturing and mathematics could enhance our understanding of rumen microbiology.

International audience; The enzyme isocitrate dehydrogenase (EC 1.1.1.42; 1; NADP+ dependent) located in the mammary cell cytosol mediates the synthesis of the majority of reducing equivalents for the energetically demanding milk fat and cholesterol synthesis in mammary cell cytosol. The present article presents a novel fluoro-metric method for quantification of the activity of this enzyme (IDH) in ruminant milk without pretreat-ment of the sample. Further, 493 goat milk samples - harvested before, during and after a nutritional restriction - were analysed for IDH activity i) with addition of extra substrate (isocitrate), and ii) with the intrinsic isocitrate solely. The IDH activity ranged from 0.22 to 15.4 units [nano moles product/ (ml * min)] (un-supplemented) and from 0.22 to 45.6 units (isocitrate supplemented). The IDH activity increased considerably in milk during the nutritional restriction period concomitant with the increase in the metabolite isocitrate concentration and somatic cell count and returned to the initial level shortly after restriction period. The present 'high through-put' analytical method may be beneficial in future studies to phenotype modifications in mammary energy metabolism and milk fat synthesis, for which IDH activity may be a biomarker. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of The Animal Consortium. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

International audience; Quantitative description of individual animal performance is a key element of breeding. In addition to measurements of traits associated with productivity, dynamic-mechanistic models can be used for identifying diversity of complex traits like feed efficiency. The objective of this work was to use Bayesian inference to quantify differences in a model's 'genetic-scaling' parameters (related to resource acquisition and resource allocation) within-and between-breeds. We first describe the experimental data processing before calibration, the function used for the error calculation, and the Bayesian algorithm used for parameter inference. Two databases were used as case studies. The results showed that this approach allowed us to identify variations in the genetic-scaling parameters within-and between-breeds. This approach is a useful tool to quantify complex traits for future selection of efficient and resilient animals.

International audience; The objective of this study was to present a new methodology to predict selection response on resilience and feed efficiency (FE) in dairy cattle. This approach combines genetic and mechanistic modelling to describe the biological mechanisms underlying these traits. A dairy cattle breeding scheme was simulated considering a non-limiting nutritional environment and two different breeding goals focusing either on milk production or FE. Selection response was predicted within the non-limiting environment but also for a prospective low-input system (LS). Predictions obtained with conventional and mechanistic-based methods were consistent for milk production, body weight and FE within the non-limiting environment. However, genetic trends predicted for fertility were different. Selection response achieved on milk production was much smaller in the LS than in the breeding nucleus due to the increased nutritional constraint. The breeding goal with emphasis on FE enabled a better transfer of genetic gain to the LS environment.

High-producing ruminants need high-concentrate diets to satisfy their nutrient requirements and meet performance objectives. However, such diets induce sub-acute ruminal acidosis (SARA), which will adversely affect dry matter intake and lead to lower production performance. This work develops a novel modelling approach to quantify the capacity of dairy goats to adapt to a high-concentrate diet challenge at the individual level. The animal model used was dairy goats (from Saanen or Alpine breed), and rumen pH was used as the indicator of the response. A three-step modelling procedure was developed to quantify daily scores and produce a single global index for animals’ adaptive response to the new diet. The first step summarizes the post-prandial kinetics of rumen acid status using three synthetic variables. In the second step, the effect of time on the response of goats is described, in the short and long terms. In the last step, a metric based on phase trajectories ranks goats for their resilience capacity. This modelling procedure showed a high variability among the goats in response to the new diet, highlighting in particular their daily and general strategies to buffer the effect of the diet change. Two main categories of adaptive strategies were observed: (i) acid status increased, but the goats tried to minimize its variations, and (ii) acid status oscillated between increases and decreases. Such phenotyping, alongside other behavioral, digestive, and metabolic measures, can help to determine biomarkers of goats’ capacity to adapt to diets of higher nutritive value and to increase production performance without compromising their health status. Quantifying the capacity of goats to buffer the effect of highly fermentable diets helps to better adapt feed to animals in precision livestock farming. This procedure is generic and can be adapted to any indicator of animal health and performance. In particular, several indicators can be combined to assess multi-performance, which is of major interest in the context of selection for robust animals.

A dairy cow’s lifetime resilience and her ability to recalve gain importance on dairy farms, as they affect all aspects of the sustainability of the dairy industry. Many modern farms today have milk meters and activity sensors that accurately measure yield and activity at a high frequency for monitoring purposes. We hypothesized that these same sensors can be used for precision phenotyping of complex traits such as lifetime resilience or productive life span. The objective of this study was to investigate whether lifetime resilience and productive life span of dairy cows can be predicted using sensor-derived proxies of first-parity sensor data. We used a data set from 27 Belgian and British dairy farms with an automated milking system containing at least 5 yr of successive measurements. All of these farms had milk meter data available, and 13 of these farms were also equipped with activity sensors. This subset was used to investigate the added value of activity meters to improve the model’s prediction accuracy. To rank cows for lifetime resilience, a score was attributed to each cow based on her number of calvings, her 305-d milk yield, her age at first calving, her calving intervals, and the DIM at the moment of culling, taking her entire lifetime into account. Next, this lifetime resilience score was used to rank the cows within their herd, resulting in a lifetime resilience ranking. Based on this ranking, cows were classified in a low (last third), moderate (middle third), or high (first third) resilience category within farm. In total, 45 biologically sound sensor features were defined from the time series data, including measures of variability, lactation curve shape, milk yield perturbations, activity spikes indicating estrous events, and activity dynamics representing health events (e.g., drops in daily activity). These features, calculated on first-lactation data, were used to predict the lifetime resilience rank and, thus, to predict the classification within the herd (low, moderate, or high). Using a specific linear regression model progressively including features stepwise selected at farm level (cutoff P-value of 0.2), classification performances were between 35.9 and 70.0% (46.7 ± 8.0, mean ± SD) for milk yield features only, and between 46.7 and 84.0% (55.5 ± 12.1, mean ± SD) for lactation and activity features together. This is, respectively, 13.7 and 22.2% higher than what random classification would give. Moreover, using these individual farm models, only 3.5 and 2.3% of cows were classified high when they were actually low, or vice versa, whereas respectively 91.8 and 94.1% of wrongly classified animals were predicted in an adjacent category. The sensor features retained in the prediction equation of the individual farms differed across farms, which demonstrates the variability in culling and management strategies across farms and within farms over time. This lack of a common model structure across farms suggests the need to consider local (and evidence-based) culling management rules when developing decision support tools for dairy farms. With this study we showed the potential of precision phenotyping of complex traits based on biologically meaningful features derived from readily available sensor data. We conclude that first-lactation milk and activity sensor data have the potential to predict cows’ lifetime resilience rankings within farms but that consistency between farms is currently lacking. ispartof: JOURNAL OF DAIRY SCIENCE vol:103 issue:8 pages:7155-7171 ispartof: location:United States status: published

International audience; The objective of this review is to describe how dietary glucogenic precursors could stimulate ovarian activity in post-partum dairy cows and improve reproductive success. Although the nutrient requirements for the early resumption of ovarian cycles, and for follicle and embryo development are quantitatively small, reproductive success is deteriorated by post-partum negative energy balance. Since very little glucose is absorbed directly from the digestive tract of ruminants one of the targets for nutritional manipulation could be the glucogenic potential of the diet. This could be achieved by giving rumen-resistant starch or mono-propylene glycol. Both these adaptations increase glucose, insulin and insulin-like growth factor-1 plasma concentrations and stimulate ovarian follicle growth.

One of challenges of the French dairy goat sector is to develop, promote and support the development of sustainable farming systems. French dairy goat farms are strong users of grass, used mainly in hay, butthe feeding self-sufficiency of these farms remains relatively low (on average 61%). Greater use of herb is a technical solution to respond this societal demand, reduce feeding costs and the environmental footprint. On the 2015-2020 period, a strong mobilization of Research and Development stakeholders in the PSDR4 Flèche to understand the grass use place and level in dairy goat farming systems, to determine its technical and sociological pros and obstacles, and to provide scientific and technicalknowledge. This project has made it possible to acquire new knowledge on the use of multi-species grasslands by dairy goats, their use level and the nutritional qualities of milks and cheeses. Associatedwith agricultural education, the agroecological transition of goat farms can take place to make them more sustainable, more competitive and more resilient to hazards, especially in a context of climate change; Un des enjeux de la filière caprine française est de mettre au point, promouvoir et accompagner le développement de systèmes de production plus durables. Cependant, malgré une forte utilisation del’herbe, principalement sous forme de foin, l’autonomie alimentaire des exploitations caprines françaises techniques pour répondre aux exigences sociétales en matière d’élevage, mais également pour réduirele coût alimentaire et l’empreinte environnementale. Sur la période 2015-2020, les acteurs de la recherche, du développement et de la formation se sont mobilisés dans le projet PSDR4 Flèche pourcomprendre la place et le niveau de valorisation de l’herbe dans les systèmes caprins, d’en déterminer les avantages et les freins techniques et sociologiques, et d’apporter des références scientifiques ettechniques sur son utilisation. Ce projet a ainsi permis d’acquérir de nouvelles connaissances sur l’utilisation des prairies multi-espèces par les chèvres, leur niveau de valorisation et les qualitésnutritionnelles des laits et des fromages des systèmes herbagers. Associé à l’enseignement agricole, la transition agro-écologique des élevages caprins peut s’opérer pour les rendre plus durables, compétitifset résilients aux aléas, tout particulièrement dans un contexte de changement climatique.

International audience; Most intake models for dairy cows have been developed to make predictions under normal conditions, in which animals can meet their nutritional requirements. To estimate intake under constraining conditions, i.e. when intake is defined by the environment and not by the animal's requirements, it is necessary to develop models that take into account environmentally driven effects. The aim of this work was to develop a framework to represent the links between environmental variables (food quality and quantity, as well as ambient temperature, season, and farm type) and intake. The framework integrates time as the major constraint on intake and proposes the environmentally attainable intake (EAI) as the product of the Eating Rate (ER) and the Eating Time (ET). ER is the maximum sustainable rate (gr DM/min) at which animals bite the food, and ET is the daily time (min/d) that animals have to eat. The architecture of the framework is easily extensible to add constraints such as predation pressure, reproductive costs, competition, parasitism, or diseases. Data from grazing and indoor dairy farms were used to test the usability of the framework. The results show that a time use-based framework is a reliable approach to estimate intake considering environmental variables with minimum use of animals' characteristics. In conclusion, a high-level framework of feeding behaviour, that captures the main underlying mechanisms of intake in constrained environments, can be used to predict the EAI and the effects of the environment on animal performance.

BackgroundResilience can be defined as the capacity of animals to cope with short-term perturbations in their environment and return rapidly to their pre-challenge status. In a perspective of precision livestock farming, it is key to create informative indicators for general resilience and therefore incorporate this concept in breeding goals. In the modern swine breeding industry, new technologies such as automatic feeding system are increasingly common and can be used to capture useful data to monitor animal phenotypes such as feed efficiency. This automatic and longitudinal data collection integrated with mathematical modelling has a great potential to determine accurate resilience indicators, for example by measuring the deviation from expected production levels over a period of time.ResultsThis work aimed at developing a modelling approach for facilitating the quantification of pig resilience during the fattening period, from approximately 34 kg to 105 kg of body weight. A total of 13 093 pigs, belonging to three different genetic lines were monitored (Pietrain, Pietrain NN and Duroc) since 2015, and body weight measures registered (approximately 11.1 million of weightings) with automatic feeding systems. We used the Gompertz model and linear interpolation on body weight data to quantify individual deviations from expected production, thereby creating a resilience index (ABC). The estimated heritabilities of ABC are low but not zero from 0.03 to 0.04 (± 0.01) depending on the breed.ConclusionsOur model-based approach can be useful to quantify pig responses to perturbations using exclusively the growth curves and should contribute to the genetic improvement of resilience of fattening pigs by providing a resilience index.

International audience; Cattle are the world’s largest consumers of plant biomass. Digestion of this biomass by ruminants generates high methane emissions that affect global warming. In the last decades, the specialisation of cattle breeds and livestock systems towards either milk or meat has increased the milk production of dairy cows and the carcass weight of slaughtered cattle. At the animal level and farm level, improved animal performance decreases feed use and greenhouse gas emissions per kg of milk or carcass weight, mainly through a dilution of maintenance requirements per unit of product. However, increasing milk production per dairy cow reduces meat production from the dairy sector, as there are fewer dairy cows. More beef cows are then required if one wants to maintain the same meat production level at country scale. Meat produced from the dairy herd has a better feed efficiency (less feed required per kg of carcass weight) and emits less methane than the meat produced by the cow-calf systems, because the intake of lactating cows is largely for milk production and marginally for meat, whereas the intake of beef cows is entirely for meat. Consequently, the benefits of breed specialisation assessed at the animal level and farm level may not hold when milk and meat productions are considered together. Any change in the milk-to-meat production ratio at the country level affects the numbers of beef cows required to produce meat. At the world scale, a broad diversity in feed efficiencies of cattle products is observed. Where both productions of milk per dairy cow and meat per head of cattle are low, the relationship between milk and meat efficiencies is positive. Improved management practices (feed, reproduction, health) increase the feed efficiency of both products. Where milk and meat productivities are high, a trade-off between feed efficiencies of milk and meat can be observed in relation to the share of meat produced in either the dairy sector or the beef sector. As a result, in developing countries, increasing productivities of both dairy and beef cattle herds will increase milk and meat efficiencies, reduce land use and decrease methane emissions. In other regions of the world, increasing meat production from young animals produced by dairy cows is probably a better option to reduce feed use for an unchanged milk-to-meat production ratio.

Climate change, with its increasing frequency of environmental disturbances puts pressures on the livestock sector. To deal with these pressures, more complex traits such as resilience must be considered in our management strategies and in our breeding programs. Resilient animals respond well to environmental challenges, and have a decreased probability of needing assistance to overcome them. This paper discusses the need for operational measures of resilience that can be deployed at large scale across different farm types and livestock species. Such measures are needed to provide more precise phenotypes of resilience for use in farm management, but also for use in animal breeding. Any measure of response and recovery reflects both the animals resilience and the perceived size of the environmental disturbance, which can vary over time, depending on multiple animal and farm-related contexts. Therefore, and because universal definitions of resilience are too broad to be operational, we argue that resilience should be seen as a latent construct that cannot be directly measured and selected for. This leads to the following two points: (1) any postulated operational measure of resilience to a disturbance should be constructed from a sufficient number of indicators that each individually capture different facets of the resilience, such that when combined they better reflect the full resilience response; and (2) any postulated operational measure of resilience will have to be validated against reference measures that are the accumulated consequences of good resilience (e.g. productive lifespan or ability to re-calve). In a dairy cow case study, a practical resilience definition for dairy cattle was proposed and tested based on a scoring system containing several categories. In general terms and within a given parity, a cow receives plus points for each calving, and for a shorter calving interval, fewer inseminations and a higher milk production compared to her herd peers. She will receive minus points in case the number of inseminations increases, for each curative treatment day, and if her milk production is lower compared to her herd peers. By using readily available farm data, we were able to assess a practical lifetime resilience score, based on which cows can then be ranked within the herd. Cows that reach a next parity were shown to have a higher rank than cows that are culled before the next parity. To examine the usefulness of such a score, this resilience ranking was linked to two precision livestock technology-derived measures, related to milk yield deviations and accelerometer-derived deviations. Higher resilience ranking cows had fewer drops in milk yield and a more stable activity pattern during the lactation. This case study, taking the operational approach to quantifying and defining resilience, shows the promise of a data-driven approach for identifying resilience measures when applied within a biologically logical framework. ispartof: Peer Community Journal vol:2 status: published

International audience; The objectives of this study were to investigate the possibility of characterising animalrobustness by using indicators based on the dynamics of energy allocation of the animal andto determine their genetic parameters. A total of 2 140 pigs, from the Piétrain NN Françaisline, were raised at the AXIOM boar testing station. This farm was equipped with automaticfeeding system, recording individual weight and feed intake at each visit. We used a dynamiclinear regression model to characterize the evolution of the allocation factor ( αt) betweencumulative net energy available, estimated from feed intake, and cumulative weight gainduring fattening period. The variance of α t, that could be interpreted as an indicator of theresponse of the animal to perturbations/stress, showed moderate heritability (0.27 ±0.08). Ourperspective is to further decompose the allocation factor into components to bettercharacterise the robustness phenotyp

International audience; In the long term, resilient animals are able to maintain their normal biological processes when confronted with environmental perturbations, reducing their risk of being culled. Therefore, longevity can be proposed as an indicator of long-term resilience. Decisions to remove a given dairy cow from the herd are mainly related to low milk production (i.e., voluntary culling) or to reasons other than production (i.e., involuntary culling). The aptitude of animals to delay any culling is defined as true longevity (TL), whereas functional longevity (FL) is the ability to avoid involuntary culling. The aim of the study was to investigate the influence of production, reproduction, morphology, and health traits on TL and FL, to identify risk factors for culling. Data included 278,217 lactations from 122,461 Holstein Friesian cows reared in 640 herds. The length of productive life, calculated as the time between first calving and culling, or censoring, was used as the measure of longevity. Survival analysis was performed using proportional hazards models assuming a piecewise Weibull distribution of the baseline hazard function, with or without adjustment for milk production to evaluate FL and TL. Insemination status, calving ease, mastitis, somatic cell count, displaced abomasum, and udder depth had significant relationships with TL and FL. Differences in estimates of relative risk between TL and FL showed that milk production often influenced culling decisions: farmers are more prone to cull animals with low production even when they had good other characteristics. The culling risk factors identified in the present study can be used to study resilience in dairy cattle and to improve genetic evaluations of functional or total longevity.

International audience; The production of methane by the rumen microbiota is a complex biological process. When tackling the modelling of methane production, the modeller decides what complexity is needed to answer the scientific question for which the model is intended. Such a choice results in a diversity of possible models spanning both empirical and mechanistic approaches. Within the framework of precision livestock farming, simple dynamic models offer great advantages for integrating online data (e.g., feed intake) to predict individual methane emissions from cattle. Accordingly, we previously developed, with satisfactory results, a simple dynamic model that uses DM intake kinetics as a single predictor of methane emissions from finishing beef steers. The objective of the present work was to assess the capability of the previously developed model to predict the dynamic pattern of methane production from dairy cows fed a diet containing either wheat grain or corn grain. We showed that the simple dynamic model in its original form enables a description of the dynamics of individual methane emissions from dairy cows with an average determination coefficient (r2) of 0.65 and an average concordance correlation coefficient of 0.81 and RMSE of 16% and 26% for the corn-based and wheat-based diets, respectively. Additionally, we performed a principal component analysis associating the parameters of the methane model with variables characterising the feeding behaviour of the cows. The results showed the effect of the diet type on the feeding behaviour of the animals. This impact was propagated on the dynamics of methane emissions. Interestingly, our model enabled us to determine that the differences in patterns of methane emissions between the diets result simply from the dependency of the methane yield and rate constant of methane eructation on the grain type.

International audience; In ruminants, feeding behaviour variables are parameters involved in feed efficiency that show variation among individuals. This study aimed to evaluate during the first two production cycles in ruminants the repeatability of feed intake pattern, which is an important aspect of feeding behaviour. Thirty-five dairy goats from Alpine or Saanen breeds were housed in individual pens at four periods (end of first gestation, middle of first and second lactations and middle of second gestation which is also the end of first lactation) and fed a total mixed ration (TMR) ad libitum. Individual cumulative dry matter intake (DMI) was automatically measured every 2 min during the last 4 days of each period. Feed intake pattern was characterized by several measures related to the quantity of feed eaten or to the rate of intake during the 15 h following the afternoon feed delivery. Two main methods were used: modelling cumulative DMI evolution by an exponential model or by a segmentation-clustering method. The goat ability to sort against dietary fibre was also evaluated. There was a very good repeatability of the aggregate measures between days within a period for a given goat estimated by the day effect within breed and goat, tested on the residual variance (P > 0.95). The correlations between periods were the highest between the second and either the third or fourth periods. With increasing age, goats sorted more against the fibrous part of the TMR and increased their initial rate of intake. Alpine goats ate more slowly than Saanen goats but ate during a longer duration. Principal component analysis (PCA) was performed on all the aggregate measures of feed intake patterns. The factor score plots generated by the PCA highlighted the opposition between the different measures of feed intake patterns and the sorting behaviour. The projection of the animals on the scoring plots showed a breed effect and that there was a continuum for the feed intake pattern of goats. In conclusion, this study showed that the feed intake pattern was highly repeatable for an animal in a given period and between periods. This means that phenotyping goats in a younger age might be of interest, either to select them on feeding behaviour and choose preferentially the slow eaters or to adapt the quantity offered and restrict feed delivery to the fast eaters in order to increase feed efficiency and welfare by limiting the occurrence of acidosis, for example.

Heat and water stress are rampant challenges in animal production as a result of climate change. Sixteen lactating goats of the Alpine and Saanen breeds were subjected to water restriction for 16 h on two consecutive days followed by rehydration, along with naturally rising temperature that culminated by the end of an experimental period of one week. Data were collected from the animals on four separate days representing their status under control conditions when temperature was still within their comfort zone, on the second day of the water restriction treatment, 24 h after rehydration and finally on the day when ambient temperature was above the normal average. Animals showed an increase in rectal temperature with time as ambient temperature increased. The heat stress was reflected by the decrease in pCO2 and HCO3 concentrations consistent with the onset of panting, while milk production was maintained but the concentration of major milk components decreased. Water stress, on the other hand, led to hemoconcentration with increased osmolality, Na+, urea, glucose and albumin concentrations and an increase in milk lactose. The changes in blood parameters were reversed 24 h after rehydration but were slightly lower than normal, indicating the need for more than 24 h to re-adjust water balance in these lactating animals. Finally, the latency between first feeding and the following drinking event after return from milking showed that the shortest latency was under the water restriction treatment indicating thirst, in addition, a trend for shorter latency before drinking over the experimental period was observed in response to the rise in temperature. This experiment showed the capacity of these highly productive breeds to withstand mild water and heat stress. However, subtle changes in physiology and milk composition warrant further research into their effect on milk quality and animal welfare.

International audience; Precision farming allows automatic and massive data collection aiming at improving animal productivity and welfare among many goals. Animal models are needed to interpret these data and individual variability in order to better adjust management strategies (i.e. feeding strategies). The GARUNS model of dairy cow lifetime performance initially proposed by Martin and Sauvant has evolved through the last ten years, including a reproductive module, able to take into account individual reproductive management, and more recently a ‘feed plan’ module, taking into account the composition of the ration distributed to the cow during its life. The first objective of this study was to quantify the effect of this ‘feed plan’ module on the fitting accuracy of production variables. The second objective was to evaluate the fitting quality of the second lactation when the fitting was done on first lactation data only. The new model, with the ‘feed plan’ module, was fitted with a step-by-step procedure on the first lactation data of 16 Holstein cows. These data were collected during an experimental trial on extended lactation conducted from 2012 to 2015 at the Danish Cattle Centre in Aarhus University (Denmark). Data used concerned production (dry matter intake, milk yield, body weight, body condition score, milk components) and reproduction (insemination and parturition time) data as well as rations’ composition. Preliminary results indicated that the adjustment with the new model was more accurate for the three production variables studied (dry matter intake, milk yield and body weight) during the first lactation than the one with the model without ‘feed plan’ module. Based on the first lactation fitting, the new model was also able to fit the second lactation data to a certain extend. To conclude, this first approach indicated the relevance of the feed module to improve the model fitting. It could therefore serve as management tool and help predicting the individual productivity of the next lactation. Further work should include perturbations (i.e. health incidents) in the model to obtain more accurate predictions.

International audience; We propose a non-invasive proxy based on milk natural abundance of stable isotopes to assess body mobilization in dairy cow, and test whether this proxy can reflect between-animal variation in feed efficiency.

International audience; To optimize the use of dietary P by pigs, 5 feeding strategies were studied in a 3-phase feeding trial on 240 pigs (initial bodyweight (BW) of 31 kg): 1) C-C-C providing 100% of digestible phosphorus (Pdig, 4.3 g/kg STTD) and calcium (Ca, 9.7 g/kg) requirement to maximize bone mineralization, 2) L-L-L 60% of the Pdig and Ca requirements of C-C-C, 3) Phyt-Phyt-Phyt (phosphate-free, with phytase, 750, 686, 390 FTU/kg), providing 60% of Pdig and Ca requirements in phase 1, then 100%, 4) and 5) C in phases 1 and 3, and 60% of the need for Pdig in phase 2, associated with 65% of the requirements for Ca (N) or 80% (H), namely C-N-C and C-H-C. The BW and bone mineral content (BMC) were measured at the beginning and end of each phase. The BMC gain (gBMC), average daily gain (ADG) and average daily feed intake (ADFI) were calculated by phase. In phase 1, ADG was lower in the Phyt group than the C group (1.05 vs 1.10 kg/d, P < 0.01) and the BMC of group C and gBMC were higher than those of the Phyt and B groups (P < 0.05). In phase 2, C-C and Phyt-Phyt groups had similar BMC due to higher gBMC in the Phyt-Phyt (27.1 vs 18.4 g/d, P < 0.01). At the end of phases 2 and 3, C-C-C, C-N-C and C-H-C groups had similar BMC. The Phyt and B groups showed an increased phosphorus-use efficiency during phases 1 and 2 (+20% vs C). Phosphorus retention was also higher in the C-N-C and C-H-C groups, during the depletion in phase 2 (+24% vs C, P< 0.05). These results showed the potential of a depletion-repletion strategy including free phosphate diet to reduce phosphorus intake and excretion without affecting final growth performance and bone mineralization because of increased minerals utilization efficacies.

International audience; Few studies have investigated how meal patterns of ruminants are affected by diet fibre content. Dairy goats (N = 32) in late lactation and early gestation were housed in eight groups of four goats, with all combinations of breed (Alpine and Saanen) and lactation number (1 and 2) represented in each group. Each goat had access to its own individual feed trough placed on a weigh scale with data logged automatically. All goats were fed the same total mixed ration (TMR; 30% concentrate and 44.6% NDF in DM) ad libitum for a control period of 22 days. Using the same feed ingredients, half of the groups were then offered a High fibre diet (20% concentrate; 47.3% NDF), and the other half a Low fibre diet (40% concentrate; 41.5% NDF) for a treatment period of 16 days. Daily meal patterns (meal frequency, duration and size, feeding rate, daily feed intake and daily feeding time) were computed for each animal using a meal criterion of 8 min. The last 10 days for each period (control and treatment) were used to calculate individual period means and individual differences between the two periods. During the control period, the goats ate on average 12.1 +/- 0.49 meals/day, consuming 4.2 +/- 0.10 kg fresh TMR daily. When the ration changed, all measures of feeding behaviour except meal size changed asymmetrically for the goats on the two diets. Goats fed the High fibre diet reduced their meal frequency by 10%, and the first meal after feed distribution lasted 11% longer, leading to a 9% reduction in feeding rate and no significant changes in daily feed intake and daily feeding time. Goats on the Low fibre diet did not significantly change their meal frequency or meal size, but the combined changes nevertheless led to a 9% increase in daily feed intake. On the Low fibre diet, goats were able to increase their feeding rate by a third, leading to a reduction in meal durations, thus reducing daily feeding time by 13%. Goats adapt their feeding behaviour to the fibre proportion of the offered diet, with more changes when fibre content is lowered, which needs to be taken into account when comparing phenotypes and adaptability of small ruminants to different diets.

It has been over 20 years since the first scientific papers on rat tickling were published (1, 2). Rats were found to emit ultrasonic vocalizations in the 50-kHz range (hereafter referred to as USVs) when a human performed rapid manual stimulation on their dorsoventral region. Such tickling of rats by a human hand is trying to imitate the rough-and-tumble play seen in young rats of both sexes (3, 4). Emission of USVs by the rat indicates that it enjoys being tickled (5–7), as USVs have been linked with positive emotions (8, 9), are emitted in anticipation of, and during, social play (10, 11), and have been suggested to be homologous to human laughter (12). To date, more than 70 scientific articles on rat tickling have been published1, and the consensus is that tickling induces positive emotions in rats. Indeed, in a systematic review, LaFollette et al. (13) found that tickling increased USVs and human hand approach behavior, and decreased measures of anxiety in rats. In this Opinion paper, we consider whether current methods of tickling overemphasize the use of pinning (Figure 1) to which there may be a wider response variation than commonly acknowledged. We do not dispute that tickling can be a positive way to handle juvenile rats, but tickling may not always be perceived as a positive interaction by the rat, and we raise the possibility that tickling methods need to be revised. In particular, we suggest incorporating more aspects of play during tickling (increased diversity) and adapting the method to individual rats' responses (increased flexibility) to achieve positive emotions and increased welfare across a wider cohort of rats. Open in a separate window Figure 1 (A) Pinning is a component of social play in rats, where one rat has its dorsal surface pinned to the ground, while the other rat is in a dominant posture above. (B,C) Pinning has become the main component of the methodology used when tickling rats, as it elicits 50-kHz ultrasonic vocalizations (USVs). Pinning has been used in the past as a means to quantify rough-and-tumble play between rats (14). However, rough-and-tumble play is much more than just pinning, and USVs during pinning are frequent when being tickled by a human (1), but less so when being pinned during play (10, 15). Drawings are by Tayla J. Hammond.

Graphical abstract, The COVID-19 pandemic has resulted in many changes in the way research is conducted. Some specific groups (e.g. women) and activities (e.g. teaching) may have been disproportionally affected. Our aim was to assess the impact of the COVID-19 pandemic on animal behaviour and welfare researchers’ work experience and productivity, focussing on gender, care role, career stage and teaching load. An online survey asked researchers about childcare, research and teaching load and associated changes due to the pandemic, among others, and included the Perceived Stress Scale (PSS) and the Inventory of Socially Supportive Behaviours (ISSB). From June-July 2020, 117 completed responses were received from 28 countries. Time available for writing papers and grants either increased (36%), decreased (31%) or these tasks were halted completely (12%). Perceived productivity was significantly lower for caregivers (P