Accuracy of First Lactation Versus All Lactation Sire Evaluations by Best Linear Unbiased Prediction

Ufford, G.R.; Henderson, Charles; Keown, Jeffrey F.; Vleck, L.D. Van

doi:10.3168/jds.s0022-0302(79)83296-8

Cited by 25 publications

(6 citation statements)

References 7 publications

(13 reference statements)

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“…Comparisons of sire evaluations based on first vs all lactation records have indicated that there is little change in sire ranking for some populations (Weller et al, 1984). However, use of all lactation records results in higher accuracy values, but may also result in additional bias due to including selected data (Ufford et al, 1979). Johansson ( 198 1) reported a genetic correlation of .41 between first and second parities for NBA and .2 for litter size at 3 wk from his 1979 work, but suggested further research in this area was needed.…”

Section: Model Developmentmentioning

confidence: 99%

Development of an animal model for across-herd genetic evaluation of number born alive in swine

Woodward

Mabry

See

et al. 1993

Journal of Animal Science

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An animal model and computer software were developed to conduct across-herd genetic evaluations using data from producers participating in the Sow Productivity Index program of the American Yorkshire Club. The final data set consisted of 61,596 litter records from 1986 to early 1990. The animal model included fixed contemporary group effects and random additive direct, service sire, permanent environmental, and residual effects. Additive genetic relationships among animals were included. A separate relationship matrix for service sires and their sires was also included. A data set similar to the Yorkshire field data was simulated to use in testing the animal model. The simulated data set consisted of 40 herds, each with 120 reproducing dams and either four or five sires. Six generations of simulated data were produced, resulting in 20,605 litter records. These records were then evaluated using the animal model for number of pigs born alive. Finally, correlations between the true breeding values from the simulation and the predicted breeding values were computed. The correlation between the 918 true and predicted sire breeding values was considerably lower for the animal model without a service sire effect than when it was included (.53 vs .74, respectively). However, the difference was cut in half (.66 vs .77) when only sires with greater than five daughter records were included. The high accuracy of the animal model with a random service sire effect indicates that the proposed model adequately accounts for the variation found in records for number of pigs born alive.

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Section: Model Developmentmentioning

confidence: 99%

Development of an animal model for across-herd genetic evaluation of number born alive in swine

Woodward

Mabry

See

et al. 1993

Journal of Animal Science

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“…Because of computational limitations, most applications of TD models consider only the first few lactations information. However, in genetic evaluation, use of records from subsequent lactations has been credited with increasing accuracy of evaluations (Ufford et al 1979) and providing more complete information on the lifetime performance of animals (Cassell & McDaniel 1983). The inclusion of later lactations information is especially important for a trait-like SCS, where the overall aim was to increase mastitis resistance throughout the productive life of cows.…”

Section: Introductionmentioning

confidence: 99%

Genetic evaluation of somatic cell score in dairy cattle considering first and later lactations as two different but correlated traits

Negussie

Koivula

Mäntysaari

et al. 2006

J Animal Breeding Genetics

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A test-day (TD) random regression model (RRM) was described for the genetic evaluation of somatic cell score (SCS) where first and later lactations were considered as two different but correlated traits. A two-step covariance function procedure was used to estimate variance-covariances and associated genetic parameters. Analysis of estimated breeding values (EBV), ranking of top bulls and cows and some computational aspects were used to compare RRM with TD repeatability model (RPM) and lactation average model (LAM). Residuals were analysed to assess the relative fit of TD models. Comparison between RRM and RPM showed that RRM has lower mean squared error and gave better fit to the data. For young bulls and cows, the standard deviation (SD) of EBVs was highest for RRM and lowest for LAM implying efficient utilization of information on SCS, in terms of revealing more genetic variation. A much lower correlation of EBVs ranging from 0.80 to 0.92 and significant re-ranking of top bulls and cows were observed between RRM and LAM. The lower across-lactation correlation between RRM and LAM indicated that LAM is directed to give more weight to first lactation breeding values. The RRM, where SCS in the first and later lactations was considered as two different but correlated traits was able to make effective use of available information on young bulls and cows, and could offer an opportunity to breeders to utilize EBVs for first and later lactations.

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“…Workers at Virginia Tech (23,24) in cooperation with the Holstein Association developed herdmate procedures for Holstein data. Even more recently the United States Department of Agriculture (USDA) (4,14) has adapted best linear unbiased prediction (BLUP) procedures (5,6,7,8,18,19,20) for Jersey, Guernsey, and Holstein records. A BLUP system was begun in Canada for Holsteins (16,17).…”

Section: Introductionmentioning

confidence: 99%

Sire Evaluation by Best Linear Unbiased Prediction for Categorically Scored Type Traits

Vleck

Karner

1980

Journal of Dairy Science

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Best linear unbiased prediction to predict category frequencies of future progeny of a sire for type traits scored in mutually exclusive categories is described. The method accounts for automatic covariances among categories and is comparable to prediction for multiple traits. The method does not require linearity of measurements and also allows nonlinear economic values to be assigned to each category after frequencies are predicted. Evaluations were for 12 descriptive type traits for 712 Brown Swiss bulls having daughters in more than one herd. Problems in obtaining solutions to the mixed-model equations for multiple traits are discussed.

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Accuracy of First Lactation Versus All Lactation Sire Evaluations by Best Linear Unbiased Prediction

Cited by 25 publications

References 7 publications

Development of an animal model for across-herd genetic evaluation of number born alive in swine

Development of an animal model for across-herd genetic evaluation of number born alive in swine

Genetic evaluation of somatic cell score in dairy cattle considering first and later lactations as two different but correlated traits

Sire Evaluation by Best Linear Unbiased Prediction for Categorically Scored Type Traits

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