Publications by authors named "P Duenk"

Heat stress in broilers is a pressing issue in the changing climate. Data on broiler behavior might be useful for early detection of heat stress and subsequent intervention, and may provide potential indicators for heat tolerance that can be used in broiler breeding programs. Here, we used bird location data collected in a previous study during which broilers were inadvertently exposed to high ambient temperatures due to a local heat wave.

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The purebred-crossbred genetic correlation (r) is a key parameter to determine whether the optimal selection of purebred animals to improve crossbred performance should rely on crossbred phenotypes, purebred phenotypes, or both. We reviewed published estimates of the r in poultry. In total, 19 studies were included, of which four were on broilers and 15 on laying hens, with 150 r estimates for nine different trait categories.

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Background: In genomic prediction, it is common to centre the genotypes of single nucleotide polymorphisms based on the allele frequencies in the current population, rather than those in the base generation. The mean breeding value of non-genotyped animals is conditional on the mean performance of genotyped relatives, but can be corrected by fitting the mean performance of genotyped individuals as a fixed regression. The associated covariate vector has been referred to as a 'J-factor', which if fitted as a fixed effect can improve the accuracy and dispersion bias of sire genomic estimated breeding values (GEBV).

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Article Synopsis
  • The study investigates how to estimate variance components that affect the genetic correlation between purebred (PB) and crossbred (CB) performances in pigs.
  • Two methods based on genomic estimated breeding values (GEBV) were compared to a third method using restricted maximum likelihood (REML) for more accurate variance estimation.
  • Results showed that the first two methods provided consistent bounds for the genetic correlation in most cases, while the third method had less accuracy in predicting these bounds.
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Breeding programs aiming to improve the performance of crossbreds may benefit from genomic prediction of crossbred (CB) performance for purebred (PB) selection candidates. In this review, we compared genomic prediction strategies that differed in 1) the genomic prediction model used or 2) the data used in the reference population. We found 27 unique studies, two of which used deterministic simulation, 11 used stochastic simulation, and 14 real data.

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