UMR1213 Herbivores

This data article contains annotation data characterizing Multi Criteria Assessment (MCA) Methods proposed in the agri-food sector by researchers from INRA, Europe's largest agricultural research institute (INRA, http://institut.inra.fr/en). MCA can be used to assess and compare agricultural and food systems, and support multi-actor decision making and design of innovative systems for crop production, animal production and processing of agricultural products. These data are stored in a public repository managed by INRA (https://data.inra.fr/;

Ce projet consiste en une experimentation "systeme" pluridisciplinaire : nous avons mis a l’epreuve du reel, pour les evaluer sur differents criteres, deux systemes herbagers ovins biologiques, productifs et autonomes, dont l’un propose le fractionnement des periodes de mises-bas comme element de securisation face aux aleas. L’hypothese initiale, formulee par simulation ex-ante, n’a pas ete validee. Le systeme fractionne a permis une meilleure productivite animale, mais les couts de production, la charge de travail et sa complexite y ont ete plus eleves que dans le systeme autonome. A signaler notamment une moindre recolte de stocks fourragers dans ce systeme, notamment en 2011 (printemps sec), due a une plus grande difficulte de gestion du pâturage.

There is an increasing societal concern for the welfare of farm animals. The European project Welfare Quality® aims at developing a standard for the assessment of and information about animal welfare. Welfare is composed of several dimensions (health, behaviour, absence of stress...). Hence, its overall evaluation is based on a set of complementary measures. The objective of this PhD thesis is to develop a model for the overall assessment of the welfare of dairy cows, which respects the multidimensionality of the welfare concept. Our model follows a multicriterion approach. It follows a sequential evaluation process where several criteria are constructed and aggregated into an overall assessment. After identifying the constraints imposed on the construction of an evaluation model of overall welfare, we define a set of 4 criteria (Good feeding, Good housing, Good health and Appropriate behaviour ) and 12 subcriteria. To construct the subcriteria from the 44 measures observed on farms...

Meat quality includes intrinsic qualities (the characteristics of the product itself) and extrinsic qualities (e.g. animal health and welfare, environmental impacts, price). There is still a high level of variability in beef palatability, which induces consumer dissatisfaction. We also observe a general trend towards an increasing importance of healthiness and safety (intrinsic) and environmental issues and animal welfare (extrinsic). Most grading systems describe carcasses using only animal traits (e.g. weight, conformation, fatness, animal age and sex). In North American and Asian countries, emphasis has been put on maturity and marbling. The European system is mainly based on yield estimation. The Meat Standards Australia grading scheme, which predicts beef palatability for each cut, proved to be effective in predicting beef palatability in many other countries. Some genetic markers are available to improve beef quality. In addition, gene and protein expression profiling of the b...

The Welfare Quality multi-criteria evaluation (WQ-ME) model aggregates scores of single welfare measures into an overall assessment for the level of animal welfare in dairy herds. It assigns herds to 4 welfare classes: unacceptable, acceptable, enhanced, or excellent. The aim of this study was to demonstrate the relative importance of single welfare measures for WQ-ME classification of a selected sample of Dutch dairy herds. Seven trained observers quantified 63 welfare measures of the Welfare Quality protocol in 183 loose housed-and 13 tethered Dutch dairy herds (herd size: 10 to 211 cows). First, values of welfare measures were compared among the 4 welfare classes, using Kruskal-Wallis and Chisquared tests. Second, observed values of single welfare measures were replaced with a fictitious value, which was the median value of herds classified in the next highest class, to see if improvement of a single measure would enable a herd to reach a higher class. Sixteen herds were classified as unacceptable, 85 as acceptable, 78 as enhanced, and none as excellent. Classification could not be calculated for 17 herds because data were missing (15 herds) or data were deemed invalid because the stockperson disturbed behavioral observations (2 herds). Herds classified as unacceptable showed significantly more very lean cows, more severely lame cows, and more often an insufficient number of drinkers than herds classified as acceptable. Herds classified as acceptable showed significantly more cows with high somatic cell count, with lesions, that could not be approached closer than 1 m, colliding with components of the stall while lying down, and lying outside the lying area, and showed fewer cows with diarrhea, more often had an insufficient number of drinkers, and scored lower for the descriptors "relaxed" and "happy" than herds classified as enhanced. Increasing the number of drinkers and reducing the percentage of cows colliding with components of the stall while lying down were the changes most effective in allowing herds classified as unacceptable and acceptable, respectively, to reach a higher class. The WQ-ME model was not very sensitive to improving single measures of good health. We concluded that a limited number of welfare measures had a strong influence on classification of dairy herds. Classification of herds based on the WQ-ME model in its current form might lead to a focus on improving these specific measures and divert attention from improving other welfare measures. The role of expert opinion and the type of algorithmic operator used in this model should be reconsidered.

Meat quality is a complex concept and can be defined as the characteristics of meat which satisfy consumers and citizens. The quality concept can be divided into intrinsic quality traits (which are the characteristics of the product itself) and extrinsic quality traits (which are more or less associated to the product for instance the price, a major determinant of purchase, or any brand or quality label). Quality can also be generic for the mass market or specific for niche markets. The relative importance of the different quality traits varies with human culture and time with a general trend of an increasing contribution of healthiness, safety and extrinsic quality traits. This review underlines the need for the development of methods to interpret and aggregate measures under specific rules to be defined in order to produce an overall assessment of beef quality. Such methods can be inferred for example from genomic results or data related to muscle biochemistry to better predict te...

L’apparition de la notion de développement durable a conduit à un passage des évaluations orientées selon un seul critère vers des évaluations plus intégrées couvrant différentes dimensions de la performance des élevages : l’économie, le social, le sanitaire, le bien être, l’environnement. De nombreuses questions méthodologiques sont posées par la confrontation de ces différentes dimensions avec leurs échelles de mesure propres. Comment accompagner l’évolution des systèmes d’élevage avec une évaluation multicritère ? Comment bien définir les finalités de l’évaluation ? Comment gérer la multiplicité des informations ? Comment interpréter un ensemble d’indicateurs conjointement lorsqu’ils prennent des valeurs opposées ? Quels outils mobiliser ? Faut-il utiliser ou créer ses propres outils d’évaluation ? L’élevage avec ses enjeux multiples qui s’étagent entre les niveaux des ateliers, des filières et des territoires est particulièrement concerné par ces questions. La participation des ...

National audienceThe emergence of the notion of sustainable development has led to a shift from single-criterion-oriented evaluations to more integrated assessments covering the different dimensions of livestock performance: economics, social, health, welfare and the environment. Many methodological questions arise from the confrontation of these dimensions which have different measurement scales. How to support the evolution of livestock systems with a multicriteria assessment? How to well define the purposes of the evaluation? How to manage the multiplicity of information? How to interpret a set of indicators together when they take opposite values? Which tools to mobilize? Should we use or create our own assessment tools? Livestock farming with its multiple stakes at different scales herd, farm and territory, is particularly concerned with these issues. The participation of the actors in the evaluation process is also a question to be decided: are they co-designers of the method,...

Ruminant production systems have been facing the sustainability challenge, namely, how to maintain or even increase production while reducing their environmental footprint, and improving social acceptability. One currently discussed option is to encourage farmers to follow agroecological principles, that is, to take advantage of ecological processes to reduce inputs and farm wastes, while preserving natural resources, and using this diversity to increase system resilience. However, these principles need to be made more practical. Here, we present the procedure undertaken for the collaborative construction of an agroecological diagnostic grid for dairy systems with a focus on the mountain farming relying on the use of semi-natural grasslands. This diagnosis will necessarily rely on a multicriteria evaluation as agroecology is based on a series of complementary principles. It requires defining a set of criteria, based on practices to be recommended, that should be complied with to ens...

RESUME-Le bien-être est un concept multidimensionnel. Son évaluation globale repose sur la prise en compte de manière conjointe d'un ensemble d'indicateurs-d'état général, sanitaire, ou comportemental-, chacun lié à une facette du bien-être. L'évaluation en ferme peut avoir des objectifs divers. Dans une approche analytique, on observera des fermes selon un plan préétabli visant à comparer des fermes différant pour le (ou les) facteur(s) étudié(s). La liste des indicateurs ne sera pas forcément exhaustive mais devra permettre d'estimer correctement le facteur étudié. Des analyses statistiques (ex. analyse de variance, régressions multiples, statistiques multivariées) permettront de mettre en relation des variables supposées causales et des variables à expliquer et ainsi de décrire la population étudiée. Dans une logique de certification ou de conception de systèmes, on ne cherche plus à décrire un état préexistant mais à porter un jugement sur des situations observées. Les grilles d'observation devront alors être exhaustives et les données seront interprétées selon un modèle normatif d'évaluation multicritère. Ces grilles peuvent comprendre des observations sur l'environnement ou de préférence sur animaux (blessures, pathologies, expression des comportements…) L'évaluation globale du bien-être animal est soumise à différentes contraintes théoriques, en particulier elle doit respecter le fait que les dimensions du bien-être ne se compensent pas entre elles et que les experts suivent rarement un raisonnement linéaire lorsqu'ils jugent la gravité d'une situation. Le projet Welfare Quality® explore les méthodes mathématiques propres à l'évaluation multicritère afin de produire un outil d'évaluation globale du bienêtre, en particulier dans le cadre de certifications d'élevages : le choix, la construction, puis l'agrégation des critères de bienêtre sont décrits.

Individual older than 7 months. In WelFur terms adult mink can be present in period 1, 2 and 3. Animal-based measurement: Measurement that is taken directly from the animal. Assessor: Person in charge of collecting data using the WelFur protocol on a farm in order to assess the welfare of animals. Dam: Adult female mink selected for breeding. Farm: In this protocol, "farm" is used to designate the animal unit, which means the whole or section of a farm that deals with mink. Farm manager: Person responsible for the farm. Fur-chewing: A behavioural disorder where mink chew their own fur or that of a cage mate. Habituation: The weakening of responses due to repeated exposure to stimulus. Juveniles: Young mink older than 10 weeks and less than 8 months. Thus juveniles are found on farms in the period between the time of separation and pelting or selection. In WelFur terms mink juveniles are present only in Period 3. Kits: Young mink from birth until separation/10 weeks of age. In WelFur terms, mink kits are only present in Period 2. Kits become juveniles at separation typically before or at 10 weeks of age, also if they are continuously housed with the mother. Management-based measurement: Measurement that refers to what the farm manager does on the farm and what management procedures are used or planned. Overall assessment of welfare: Synthesis of welfare information, which will be used to allocate a farm to a welfare category. Pelting: The killing of animals to harvest mature winter pelts. In the northern hemisphere this period would be early November to late December and defines the end of Period 3. Killing for harvesting fur can also take place in late March or early April after mating e.g. of males and unmated females. Resource-based measurement: Measurement that is taken regarding the environment in which the animals are kept. Section of cages: Battery type pens assembled as one unit, often 6 cages. Separation: When the kits are put out in pairs or groups after weaning. One or more kits may be housed with the female mother with or without weaning. Weaning: When the dam is removed from the litter or vice versa, terminating the lactation if it has not ceased already. Usually at 6-8 weeks after birth. Welfare category: Final categorisation given to a farm that indicates the overall welfare of animals in that particular farm. Welfare criterion: Represents a specific area of welfare concern that has to be addressed to satisfy good animal welfare. Welfare measurement: Measurement taken on a farm that is used to assess a welfare criterion. A welfare measurement may be animal, resource or managementbased. Welfare principle: Collection of criteria associated with: feeding, housing, health and behaviour. Welfare score: Score that indicates the welfare state under a criterion or principle. WelFur protocol: Description of the measurements that will be used to calculate the overall assessment of welfare. The protocol also specifies how the data will be collected. Welfare Assessment Protocol for Mink Photo : © Kopenhagen fur Welfare Assessment Protocol for Mink 13 18 Welfare Assessment Protocol for Mink 2.2 Basic principles 2.2.1 Defining welfare principles and criteria The WelFur project used the welfare principles and criteria defined in Welfare Quality® (Table 1). Welfare principles Criterion number Welfare criteria

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Face au développement en Europe de programmes de certification d’élevages mettant en avant le respect du bien-être animal, le projet Welfare Quality® a proposé à l’Union Européenne d’établir un modèle d’évaluation globale des exploitations (fermes ou abattoirs) au regard du bien-être des animaux. Ce modèle repose sur une évaluation multicritère dans laquelle 12 critères de bien-être, regroupés en 4 principes, ont été définis. Après avoir identifié les mesures nécessaires pour vérifier qu’une exploitation est conforme aux différents critères, le modèle a été progressivement construit. Il aboutit à un classement des exploitations en quatre catégories reflétant le niveau de bien-être (d’excellent à très faible). Pour ce faire, des méthodes multicritères ont été utilisées, évitant ainsi les écueils d’une agrégation naïve de l’information (comme les sommes pondérées qui autorisent les pleines compensations entre critères, ce qui n’est pas compatible avec le concept de bien-être). Différe...

There are time-tested assessments for the environmental and economic aspects of sustainability. Its societal aspect has mainly been approached through the assessment of animal welfare. However, the intrinsic quality of milk is seldom taken into account. We developed a participatory construction method for the overall assessment of intrinsic milk quality in its different dimensions (sensory, technological, nutritional and health), according to the fate of the raw milk. Two assessment models were developed, for semiskimmed standardized ultra-high temperature (UHT) milk and for pressed uncooked non-standardized raw milk cheese. They were constructed by a participatory approach involving experts in the dairy sector with the aim to obtain a diagnostic tool that could be used in the field to help farmers to manage the quality of their milk (by prioritizing improvements on major problems). They were shaped from prerequisite specifications (limited costs and time of application, desire to obtain a transparent tool with all the steps kept visible) and current technical and scientific knowledge. They were based on indicators obtained from raw bulk tank milk analyses (30 for UHT milk and 50 for cheese assessments), which were then aggregated into criteria, principles, dimensions and overall intrinsic quality at farm level. The assessment models had parts in common, for example, same four dimensions, common indicators for health and nutritional dimensions. They also had process-specific features: units chosen, criteria, indicators and weightings in relation to the final product specifications. For instance, sensory and technological dimensions are more complex and preponderant in the cheese assessment (three principles for cheese vs one for UHT milk in both dimensions). Another example is the lack of microbial pathogens (as potential health risk for consumer) in the UHT milk assessment because of pasteurization. The assessment models then underwent a sensitivity analysis and an application in 30 farms in indoor and grazing periods to finally obtain overall UHT milk and cheese quality scores at a 1-year level. The tool was found to be applicable at farm level. However, we observed low overall quality scores with a narrow dispersion, characteristic of a severe evaluation. Even so, the assessment models showed up seasonal differences of the UHT milk and cheese quality at both overall and dimensional levels. In the light of new scientific knowledge and future quality objectives, these are adaptable to other dairy products allowing for their specific features.

Marbling score Meat Colour Fat colour and fat thickness Ossification score Eye muscle area Fat thickness Texture Meat brightness Texture Meat texture Hump height Fat luster Firmness Ribfat Ultimate pH Fat texture Lean maturity Kidney fat Fat firmness Perirenal fat Rib thickness Post chiller Ageing time Cooking method

One approach to reducing enteric production of greenhouse gases (GHG; i.e., nitrous oxide and methane) is to feed tanniniferous forage plants such as sainfoin. The objective of this study was to investigate, in vitro, effects of the content and structural characteristics of condensed tannins (CT) in the whole plant, leaves and stems of sainfoin (Onobrychis viciifolia) on the digestive process in the rumen. Sainfoin, studied during the first vegetation cycle at the end of flowering, and during the second vegetation cycle at the start of flowering, was incubated in serum bottles containing buffered rumen fluid for 3.5 and 24 h. To assess effects of CT, incubations were with and without added polyethylene glycol (PEG), to neutralise CT effects. Biological activity and prodelphinidin (PD) content were higher (P<0.001) in leaves than in stems, but cis value was lower (P<0.01). At 3.5 h of incubation, gas production was higher for stems than leaves (P<0.05), but at 24 h only tended to be higher for leaves than stems (P=0.096), at the end of flowering. The presence of PEG at both short and long fermentation times increased gas production of leaves, stems and whole plant (P<0.001). At 3.5 h, PEG addition resulted in higher CH 4 values for stems and leaves at two vegetation cycles (P<0.01). The CO 2 :CH 4 ratio was lower (P<0.01) at 3.5 h and higher at 24 h (P<0.01) with added PEG. No effect of PEG on whole plant CH 4 production, or the CO 2 :CH 4 ratio, at either 3.5 or 24 h of incubation. At both incubation periods, in vitro true organic matter digestibility (IVTOMD) was higher for leaves than stems (P<0.001), and decreased with added PEG at 24 h (P<0.001). For the whole plant, PEG had no effect on IVTOMD at either 3.5 or 24 h of incubation. At 3.5 h, PEG resulted in higher N disappearance (ND) at both vegetation cycles (P<0.01), whereas values were higher at the second one (P<0.001). Mean volatile fatty acid production was higher for leaves than stems (P<0.01) and increased with PEG (P<0.001) for both vegetation cycles at 3.5 and 24 h of incubation. For both incubation periods, PEG increased (P<0.001) NH 3 -N for leaves and stems in both vegetation cycles. For the whole plant, PEG resulted in higher NH 3 -N content (P<0.001) at both 3.5 and 24 h of incubation. Utilisation of sainfoin curbs CH 4 production without altering its organic matter digestibility and N value, but research on the nutritional impact of CT must not only be based on CT content in plant tissue, but include structure-activity considerations of CT.