Simultaneous estimation of genetic parameters for production and reproduction traits in pigs using the REML method
2001
Peskovicova, D. | Groeneveld, E. | Hetenyi, L. (Vyskumny Ustav Zivocisnej Vyroby, Nitra (Slovak Republic))
Knowledge about the relationship between reproduction and production traits is needed in order to design selection criteria in pig breeding. Data from field test - average daily gain and backfat thickness (ADGFT, BFFT) and station test - average daily gain, valuable cuts and backfat thickness (ADGST, VC(%), BFST) together with number of piglets born alive in the first litter (NBA1) and number born alive in the second and further litters (NBA2+) as a trait with repeated measurements were used to estimate the complex covariance structure. The study was based on the two data sets from the performance test of pigs in Slovakia representing the data from Large White (BU) and White Meaty (BM) breeds, respectively. The restricted maximum likelihood methodology (REML) and quasi Newton iteration procedure with analytical gradient implemented in VCE package was used to estimate (co)variance parameters in 7-trait animal model. Heritability estimates agree very well with those calculated in separate analyses of production and reproduction traits. The genetic correlations between growth rate and litter size traits tended to be negative. The highest unfavourable genetic correlations were estimated between NBA1 and ADGST (-0.16 for BM breed) and between ADGST and NBA2+ (-0.28 for BM and -0.25 for BU breed). Lower (in absolute value), but also negative genetic correlations were found between field test traits and litter size traits. The leanness of pigs (measured by valuable cuts content in the station test) seem to be slightly positively correlated with litter size traits. The genetic correlations between NBA1 and VC% were 0.14 and 0.12 for BM breed and BU breed, respectively. At the same time, negative genetic correlations (-0.18 and -0.15) between backfat (BFST) and litter size (NBA1) were found for both breeds. The covariance matrices estimated in this study are used as input parameters in join genetic evaluation of the dam breeds of pigs in Slovakia
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