In this study the effects of barren vs enriched housing conditions of pigs on their behavior during the lairage period (2-h holding period before slaughter), carcass characteristics, postmortem muscle metabolism, and meat quality were studied. The barren housing system was defined by common intensive housing conditions (i.e., with slatted floors and recommended space allowances), whereas the enriched environment incorporated extra space and straw for manipulation. Salivary cortisol concentrations were measured before transport and at the end of the lairage period. During the lairage period the percentage of time spent walking and fighting by the pigs was registered. Carcass characteristics such as weight, meat percentage, and backfat thickness were determined. At 5 min, 45 min, 4 h, and 24 h postmortem, pH, temperature, and lactate concentrations were determined in the longissimus lumborum (LL) and biceps femoris (BF) muscles. Capillarization of the muscle, mean muscle fiber area, and color and drip loss after 2 and 5 d of storage were determined for both muscle types. Pigs from the barren environment had a significantly higher increase in cortisol from farm to slaughter, but no differences in behavior were observed during the lairage period. Carcass characteristics did not differ between pigs from barren and those from enriched housing conditions. Postmortem lactate formation was significantly lower in LL muscles of enriched pigs at 4 and 24 h postmortem. Capillary density and mean muscle fiber area did not differ between the groups of pigs. The percentage of drip loss at 2 and 5 d after storage of LL muscle samples from enriched-housed pigs was significantly lower than that of the barren-housed pigs. Similar tendencies were found for the BF muscle from pigs kept in an enriched environment, but these were not statistically significant. The housing system did not affect meat color. It is concluded that on-farm improvement of animal welfare by environmental enrichment can also lead to beneficial economic effects after slaughter by improving the water-holding capacity of pork.

With the aim of increasing the accuracy of genomic estimated breeding values for dry matter intake (DMI) in Holstein-Friesian dairy cattle, data from 10 research herds in Europe, North America, and Australasia were combined. The DMI records were available on 10,701 parity 1 to 5 records from 6,953 cows, as well as on 1,784 growing heifers. Predicted DMI at 70 d in milk was used as the phenotype for the lactating animals, and the average DMI measured during a 60-to 70-d test period at approximately 200 d of age was used as the phenotype for the growing heifers. After editing, there were 583,375 genetic markers obtained from either actual high-density single nucleotide polymorphism (SNP) genotypes or imputed from 54,001 marker SNP genotypes. Genetic correlations between the populations were estimated using genomic REML. The accuracy of genomic prediction was evaluated for the following scenarios: (1) within-country only, by fixing the correlations among populations to zero, (2) using near-unity correlations among populations and assuming the same trait in each population, and (3) a sharing data scenario using estimated genetic correlations among populations. For these 3 scenarios, the data set was divided into 10 sub-populations stratified by progeny group of sires; 9 of these sub-populations were used (in turn) for the genomic prediction and the tenth was used for calculation of the accuracy (correlation adjusted for heritability). A fourth scenario to quantify the benefit for countries that do not record DMI was investigated (i.e., having an entire country as the validation population and excluding this country in the development of the genomic predictions). The optimal scenario, which was sharing data, resulted in a mean prediction accuracy of 0.44, ranging from 0.37 (Denmark) to 0.54 (the Netherlands). Assuming nearunity among-country genetic correlations, the mean accuracy of prediction dropped to 0.40, and the mean within-country accuracy was 0.30. If no records were available in a country, the accuracy based on the other populations ranged from 0.23 to 0.53 for the milking cows, but were only 0.03 and 0.19 for Australian and New Zealand heifers, respectively; the overall mean prediction accuracy was 0.37. Therefore, there is a benefit in collaboration, because phenotypic information for DMI from other countries can be used to augment the accuracy of genomic evaluations of individual countries.

Reliable breed assignment can be performed with SNP. Currently, high density SNP chips are available with large numbers of SNP from which the most informative SNP can be selected for breed assignment. Several methods have been published to select the most informative SNP to distinguish among breeds. In this study, we evaluated Delta, Wright's FST, and Weir and Cockerham's FST, and extended these methods by adding a rule to avoid selection of sets of SNP in high linkage disequilibrium (LD) providing the same information. The SNP that had a r2 value>0.3 with any of the SNP already selected were discarded. The different selection methods were evaluated for both the 50K SNP and 777K Bovine BeadChip. Animals from 4 cattle breeds (989 Holstein Friesian, 97 Groningen White headed, 137 Meuse-Rhine-Yssel, and 64 Dutch Friesian) were genotyped. After editing 30,447 and 452,525 SNP were available for the 50K and 777K SNP chip, respectively. All selection methods showed that only a small set of SNP is needed to differentiate among the 4 Dutch cattle breeds, whereas comparison of the selection methods showed only small differences. In general, the 777K performed marginally better than the 50K BeadChip, especially at higher confidence thresholds. The rule to avoid selection of SNP in high LD reduced the required number of SNP to achieve correct breed assignment. The Global Weir and Cockerham's FST performed marginally better than other selection methods. There was little overlap in the SNP selected from the 2 BeadChips, whereas the number of SNP selected was about the same.

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High quality pork is consumed as fresh meat, whereas other carcasses are used in the processing industry. Meat quality is determined measuring technical muscle variables. The objective of this research was to investigate the molecular regulatory mechanisms underlying meat quality differences of pork originating from genetically different Piétrain boars. Piétrain boars were approved for high meat quality using a DNA marker panel. Other Piétrain boars were indicated as average. Both groups produced litters in similar Piétrain sows. The LM were sampled from 9 carcasses produced by approved boars and 8 carcasses of average boars. Total RNA was isolated, and an equal portion of each sample was pooled to make a reference sample representing the mean of all samples. Each sample was hybridized on microarrays against the reference in duplicate using a dye swaps design. After normalization and subtraction of 2 times the background, only genes expressed in at least 5 carcasses were analyzed. For all analyses the mean of the M-values relative to the reference (i.e., fold change), were used. Sixteen genes showed significant linear or quadratic associations between gene expression and meat color (Minolta a* value, Minolta L* value, reflection, pH 24 h) after Bonferroni correction. All these genes had expression levels similar to the reference in all carcasses. Studying association between gene expression levels and meat quality using only genes with expression statistically differing from the reference in at least 5 carcasses revealed 29 more genes associating with the technological meat quality variables, again with meat color as a main trait. These associations were not significant after Bonferroni correction and explained less of the phenotypic variation in the traits. Bioinformatics analyses with The Database for Annotation, Visualization and Integrated Discovery (DAVID) using the list of genes with more than 2-fold changed expression level revealed that these genes were mainly found in muscle-specific processes, protein complexes, and oxygen transport, and located to muscle-specific cellular localizations. Pathway analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database revealed pathways related to protein metabolism, cellular proliferation, signaling, and adipose development differing between the 2 groups of carcasses. Approved meat carcasses showed less variation in gene expression. The results highlight biological molecular mechanisms underlying the differences between the high meat quality approved and average boars.

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