Market driven initiatives can improve broiler welfare - a comparison across five European countries based on the Benchmark method.

Two kinds of initiatives exist to ensure welfare in broiler production: welfare legislation, where all broiler production in a country or region must comply with legally defined welfare standards; and market driven initiatives, where part of the production must meet specific welfare standards and is sold with a particular label, typically at a price premium, or as part of minimum welfare standards defined by a retailer, a fast-food chain or the like. While the effects of national legislation may be undermined by price competition from lower welfare imported products, the effects of market driven initiatives may be limited by lack of willingness from consumers to pay the extra cost. To investigate how this works out in practice, we compared broiler welfare requirements in 5 European countries, Denmark, Germany, United Kingdom, the Netherlands, and Sweden, in 2018, by means of the Benchmark method. A number of welfare dimensions, covering the input features typically modified in broiler welfare initiatives, were defined. A total of 27 academic welfare experts (response rate 75%) valued the different levels within each dimension on a 0 to 10 scale, and then weighted the relative contribution of each dimension to overall welfare on a 1 to 5 scale. By combining these values and weights with an inventory of existing welfare initiatives, the additional welfare generated by each initiative was calculated. Together with information on national coverage of each initiative, the Benchmark score for each country's production and consumption of chicken meat was calculated. Sweden achieved a much higher Benchmark for national production due to higher legal standards than any of the four other countries. The Netherlands, on the other hand, achieved a Benchmark for national consumption of chicken at the same level as that found in Sweden, because market driven initiatives complemented more welfare-limited Dutch legislation. So, despite some uncertainties in the Benchmark method, it appears that market driven initiatives can have a strong impact on improving broiler welfare, building on those standards achieved by animal welfare legislation.

Genetic parameters and signatures of selection in two divergent laying hen lines selected for feather pecking behaviour.

BACKGROUND: Feather pecking (FP) in laying hens is a well-known and multi-factorial behaviour with a genetic background. In a selection experiment, two lines were developed for 11 generations for high (HFP) and low (LFP) feather pecking, respectively. Starting with the second generation of selection, there was a constant difference in mean number of FP bouts between both lines. We used the data from this experiment to perform a quantitative genetic analysis and to map selection signatures. METHODS: Pedigree and phenotypic data were available for the last six generations of both lines. Univariate quantitative genetic analyses were conducted using mixed linear and generalized mixed linear models assuming a Poisson distribution. Selection signatures were mapped using 33,228 single nucleotide polymorphisms (SNPs) genotyped on 41 HFP and 34 LFP individuals of generation 11. For each SNP, we estimated Wright's fixation index (FST). We tested the null hypothesis that FST is driven purely by genetic drift against the alternative hypothesis that it is driven by genetic drift and selection. RESULTS: The mixed linear model failed to analyze the LFP data because of the large number of 0s in the observation vector. The Poisson model fitted the data well and revealed a small but continuous genetic trend in both lines. Most of the 17 genome-wide significant SNPs were located on chromosomes 3 and 4. Thirteen clusters with at least two significant SNPs within an interval of 3 Mb maximum were identified. Two clusters were mapped on chromosomes 3, 4, 8 and 19. Of the 17 genome-wide significant SNPs, 12 were located within the identified clusters. This indicates a non-random distribution of significant SNPs and points to the presence of selection sweeps. CONCLUSIONS: Data on FP should be analysed using generalised linear mixed models assuming a Poisson distribution, especially if the number of FP bouts is small and the distribution is heavily peaked at 0. The FST-based approach was suitable to map selection signatures that need to be confirmed by linkage or association mapping.