Improvement of the Welfare Quality scoring model for dairy cows to fit experts' opinion.

After several years of implementation, the original Welfare Quality scoring model for dairy cows appears to be highly sensitive to the number and cleanliness of drinkers and not enough to the prevalence of diseases, and as a consequence may not fit the opinion of some animal welfare experts. The present paper aims to improve the Welfare Quality calculations for the criteria 'Absence of prolonged thirst' and 'Absence of disease' in dairy cows, so that the results are more sensitive to input data and better fit experts' opinion. First, we modified the calculation of 'Absence of prolonged thirst' by linearising the calculation for drinkers' availability to avoid threshold effects. Second, we modified the calculation of 'Absence of disease' by applying a Choquet integral on the three lowest spline-based scores for each health disorder to limit compensation between health disorders. Third, we performed a global sensitivity analysis of the original and the alternative scoring models. Fourth, we compared the results obtained with the original and the alternative models with eight experts' opinions on two subsets composed of 44 and 60 farms, respectively, inspected using the Welfare Quality protocol and on which experts gave their opinion on the overall level of animal welfare. Results show that the alternative model significantly reduced the 'threshold effects' related to the number of drinkers and the compensation between health disorders. On the first subset, the alternative model fits the experts' opinion slightly better than the original model (P = 0.061). On the second subset, the models performed equally. In conclusion, the proposed refinements for calculating scores are validated since they significantly reduced 'threshold effects' and the influence of measures related to drinkers. It also reduced the compensation between health disorders by considering only the three lowest scores and thus increasing the influence of measures related to health disorders, and slightly improve at overall score level the accordance with experts' opinion.

Co-construction of a method for evaluating the intrinsic quality of bovine milk in relation to its fate.

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 semi-skimmed 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.

Knowledge, attitudes, practices about HIV and implications in risk and stigma prevention among French Guianese and Brazilian border inhabitants : Beliefs about HIV among border inhabitants.

BACKGROUND: The border area between French Guiana and Brazil is an active HIV-transmission zone. The aim of the present study was to describe HIV knowledge, risk and the level of stigma among inhabitants of this border area. METHODS: A cross-sectional study was conducted among 621 inhabitants over 18 years of age in the border cities of Saint-Georges-de-l'Oyapock in French Guiana and Oiapoque in Brazil. It was conducted between October 2017 and February 2018. An anonymous standardized questionnaire was filled out by culturally-trained mediators, then analyzed using STATA 12. RESULTS: Almost half (45.9%) of the individuals had a low education level. Participants whose native language was Portuguese or French demonstrated better HIV knowledge than other populations, notably native Amerindian and creole-speaking people. HIV risk behavior was more frequent in men and in younger age groups. People with good HIV knowledge reported having performed more HIV tests in the last year than participants with poor knowledge. The stigma level was high and reported in 74.8% of respondents. CONCLUSIONS: These results illustrate the need for initiatives to improve HIV prevention among autochthonous populations on both sides of this border area. Cross-border collaboration on health policies could produce common key messages adapted to the education level and multi-linguistic populations who live in this area.

Towards an agroecological assessment of dairy systems: proposal for a set of criteria suited to mountain farming.

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 ensure agroecological production. We present how such agroecological criteria were identified and organized to form the architecture of an evaluation model. As a basis for this work, we used five agroecological principles already proposed for animal production systems. A group of five experts of mountain production systems and of their multicriteria evaluation was selected, with a second round of consultation with five additional experts. They first split up each principle into three to four generic sub-principles. For each principle, they listed three to eight categories of state variables on which the fulfilment of the principle should have a positive impact (e.g. main health disorders for the integrated health management principle). State variables are specific for a given production, for example, dairy farms. Crossing principles with state variables enabled experts to build five matrices, with 75 cells relevant for dairy systems. In each cell, criteria are specific to the local context, for example, mountain dairy systems in this study. Finally, we discuss the opportunities offered by our methodology, and the steps remaining for the construction of the evaluation model.

Evaluating results of the Welfare Quality multi-criteria evaluation model for classification of dairy cattle welfare at the herd level.

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 Chi-squared 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 1m, 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.

Aggregation of measures to produce an overall assessment of animal welfare. Part 1: a review of existing methods.

Several systems have been proposed for the overall assessment of animal welfare at the farm level for the purpose of advising farmers or assisting public decision-making. They are generally based on several measures compounded into a single evaluation, using different rules to assemble the information. Here we discuss the different methods used to aggregate welfare measures and their applicability to certification schemes involving welfare. Data obtained on a farm can be (i) analysed by an expert who draws an overall conclusion; (ii) compared with minimal requirements set for each measure; (iii) converted into ranks, which are then summed; or (iv) converted into values or scores compounded in a weighted sum (e.g. TGI35L) or using ad hoc rules. Existing methods used at present (at least when used exclusively) may be insufficiently sensitive or not routinely applicable, or may not reflect the multidimensional nature of welfare and the relative importance of various welfare measures. It is concluded that different methods may be used at different stages of the construction of an overall assessment of animal welfare, depending on the constraints imposed on the aggregation process.

Aggregation of measures to produce an overall assessment of animal welfare. Part 2: analysis of constraints.

The overall assessment of animal welfare is a multicriterion evaluation problem that needs a constructive strategy to compound information produced by many measures. The construction depends on specific features such as the concept of welfare, the measures used and the way data are collected. Welfare is multidimensional and one dimension probably cannot fully compensate for another one (e.g. good health cannot fully compensate for behavioural deprivation). Welfare measures may vary in precision, relevance and their relative contribution to an overall welfare assessment. The data collected are often expressed on ordinal scales, which limits the use of weighted sums to aggregate them. A sequential aggregation is proposed in the Welfare Quality® project, first from measures to welfare criteria (corresponding to dimensions with pre-set objectives) and then to an overall welfare assessment, using rules determined at each level depending on the nature and number of variables to be considered and the level of compensation to be permitted. Scientific evidence and expert opinion are used to refine the model, and stakeholders' approval of general principles is sought. This approach could potentially be extended to other problems in agriculture such as the overall assessment of the sustainability of production systems.