An efficient computing strategy for prediction in mixed linear models

Gilmour, A.; Cullis, Brian R; Welham, S. J.; Gogel, Beverley J.; Thompson, R.

doi:10.1016/s0167-9473(02)00258-x

Cited by 516 publications

(655 citation statements)

References 9 publications

(18 reference statements)

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“…Gilt treatment was only significant for WT110, SWPF and SHORT, but not condition (fatness) traits or APBW. Random effect models were developed and parameter estimates were obtained using ASReml (Gilmour et al, 2005), which estimates variance components under a linear mixed model by residual maximum likelihood procedures. Univariate analyses were used to obtain initial estimates of genetic parameters under an animal (continuous traits) or sire (binary traits) model, including the common litter as an additional effect if significant.…”

Section: Methodsmentioning

confidence: 99%

Body development in sows, feed intake and maternal capacity. Part 2: gilt body condition before and after lactation, reproductive performance and correlations with lactation feed intake

Lewis

Bunter

2011

Animal

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Data on sow body weight (BW) and fatness (n 5 ,2250 pregnant sows) and reproductive data (including historical: n 5 ,18 000) were used to examine the genetic and phenotypic associations between body condition before and after farrowing, gestational outcomes, lactation feed intake and the gilts' ability to survive unculled to farrow in the second parity. Within-trait genetic correlations were very high between weight (0.77 6 0.06) and fat depth (0.91 6 0.04) recorded before farrowing and at weaning. Litter size traits were generally uncorrelated genetically with aspects of sow BW and body condition. However, genetic correlations indicated that sows producing heavier piglets at birth had litters with increased gain (0.36 6 0.16), and were characterised by greater weight (20.72 6 0.08) and fat change (20.19 6 0.15) during lactation, reflected to a lesser extent by lower weight (20.12 6 0.11) and fatness (20.17 6 0.10) at weaning. Genetic correlations (r a ) between reproductive traits and lactation feed intake were generally low, but favourable. However, lactation intake was positively correlated with measures of sow size (r a 5 ,0.55), such that selection for lactation feed intake would likely be accompanied by increased mature sow size. Phenotypic correlations (r p ) showed that sow survival to the second parity (FAR12) was positively influenced by litter size and fat depth at weaning, supporting attributes of increased fatness before farrowing, less weight loss during lactation and an increased lactation intake.

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Section: Methodsmentioning

confidence: 99%

Body development in sows, feed intake and maternal capacity. Part 2: gilt body condition before and after lactation, reproductive performance and correlations with lactation feed intake

Lewis

Bunter

2011

Animal

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“…Variance and covariance components for the studied traits were estimated using univariate and bivariate animal models in ASREML (Gilmour et al, 2009). Fixed effects considered in the analyses were the same as described previously, and the random effects were the additive genetic effect and the residual term.…”

Section: Statistical Analysesmentioning

confidence: 99%

Genetic parameters for milk mineral content and acidity predicted by mid-infrared spectroscopy in Holstein–Friesian cows

Toffanin

Penasa

McParland

et al. 2015

Animal

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The aim of the present study was to estimate genetic parameters for calcium (Ca), phosphorus (P) and titratable acidity (TA) in bovine milk predicted by mid-IR spectroscopy (MIRS). Data consisted of 2458 Italian Holstein − Friesian cows sampled once in 220 farms. Information per sample on protein and fat percentage, pH and somatic cell count, as well as test-day milk yield, was also available. (Co)variance components were estimated using univariate and bivariate animal linear mixed models. Fixed effects considered in the analyses were herd of sampling, parity, lactation stage and a two-way interaction between parity and lactation stage; an additive genetic and residual term were included in the models as random effects. Estimates of heritability for Ca, P and TA were 0.10, 0.12 and 0.26, respectively. Positive moderate to strong phenotypic correlations (0.33 to 0.82) existed between Ca, P and TA, whereas phenotypic weak to moderate correlations (0.00 to 0.45) existed between these traits with both milk quality and yield. Moderate to strong genetic correlations (0.28 to 0.92) existed between Ca, P and TA, and between these predicted traits with both fat and protein percentage (0.35 to 0.91). The existence of heritable genetic variation for Ca, P and TA, coupled with the potential to predict these components for routine cow milk testing, imply that genetic gain in these traits is indeed possible.

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“…The effects of sires and of dams nested within sires were assumed random. Analyses were undertaken by restricted maximum likelihood (REML) within each mating group using the ASREML package [6], such that residual variances could be estimated separately for each sire family.…”

Section: Basic Analysismentioning

confidence: 99%

Genetic heterogeneity of residual variance in broiler chickens

et al. 2006

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-Aims were to estimate the extent of genetic heterogeneity in environmental variance. Data comprised 99 535 records of 35-day body weights from broiler chickens reared in a controlled environment. Residual variance within dam families was estimated using ASREML, after fitting fixed effects such as genetic groups and hatches, for each of 377 genetically contemporary sires with a large number of progeny (>100 males or females each). Residual variance was computed separately for male and female offspring, and after correction for sampling, strong evidence for heterogeneity was found, the standard deviation between sires in within variance amounting to 15-18% of its mean. Reanalysis using log-transformed data gave similar results, and elimination of 2-3% of outlier data reduced the heterogeneity but it was still over 10%. The correlation between estimates for males and females was low, however. The correlation between sire effects on progeny mean and residual variance for body weight was small and negative (−0.1). Using a data set bigger than any yet presented and on a trait measurable in both sexes, this study has shown evidence for heterogeneity in the residual variance, which could not be explained by segregation of major genes unless very few determined the trait.broiler chickens / body weight / genetic variance / environmental variance / heterogeneity of variance

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An efficient computing strategy for prediction in mixed linear models

Cited by 516 publications

References 9 publications

Body development in sows, feed intake and maternal capacity. Part 2: gilt body condition before and after lactation, reproductive performance and correlations with lactation feed intake

Body development in sows, feed intake and maternal capacity. Part 2: gilt body condition before and after lactation, reproductive performance and correlations with lactation feed intake

Genetic parameters for milk mineral content and acidity predicted by mid-infrared spectroscopy in Holstein–Friesian cows

Genetic heterogeneity of residual variance in broiler chickens

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