Genetic parameter estimates for scrotal circumference and semen characteristics of Line 1 Hereford bulls1

2006 ◽  
Vol 84 (2) ◽  
pp. 283-290 ◽  
Author(s):  
C. G. Kealey ◽  
M. D. MacNeil ◽  
M. W. Tess ◽  
T. W. Geary ◽  
R. A. Bellows
Keyword(s):  
Genetic Parameter ◽  
Parameter Estimates ◽  
Scrotal Circumference ◽  
Semen Characteristics

PSIII-8 Genetic Parameter Estimates for Bull Prolificacy and Its Relationship with Scrotal Circumference in a Commercial Beef Cattle Population

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 158-159
Author(s):  
Chad A Russell ◽  
E J Pollak ◽  
Matthew L Spangler
Keyword(s):  
Beef Cattle ◽  
Breeding Season ◽  
Random Effects ◽  
Fixed Effects ◽  
Genetic Parameter ◽  
Additive Genetic Effect ◽  
Parameter Estimates ◽  
Contemporary Group ◽  
Scrotal Circumference ◽  
Heritability Estimates

Abstract The commercial beef cattle industry relies heavily on the use of natural service sires. Either due to the size of breeding herds or to safe-guard against injury during the breeding season, multiple-sire breeding pastures are utilized. Although each bull might be given an equal opportunity to produce offspring, evidence suggest that there is substantial variation in the number of calves sired by each bull in a breeding pasture. DNA-based paternity assignment enables correct assignment of calves to their respective sires in multi-sire pastures and presents an opportunity to investigate the degree to which this trait complex is under genetic control. Field data from a large commercial ranch were used to estimate genetic parameters for calf count (CC; n=623) and yearling scrotal circumference (SC; n=1962) using univariate and bivariate animal models. Average CC and SC were 12.1±11.1 calves and 35.4±2.30 cm, respectively. Average number breeding seasons per bull and bulls per contemporary group were 1.40 and 24.9, respectively. The model for CC included fixed effects of age during the breeding season (in years) and contemporary group (concatenation of breeding pasture and year). Random effects included additive genetic and permanent environmental effects, and a residual. The model for SC included fixed effects of age (in days) and contemporary group (concatenation of month and year of measurement). Random effects included an additive genetic effect and a residual. Univariate model heritability estimates for CC and SC were 0.237±0.156 and 0.456±0.072, respectively. Similarly, the bivariate model resulted in heritability estimates for CC and SC of 0.240±0.155 and 0.461±0.072, respectively. Repeatability estimates for CC from univariate and bivariate models were 0.517±0.054 and 0.518±0.053, respectively. The estimate of genetic correlation between CC and SC was 0.270±0.220. Parameter estimates suggest that both CC and SC would respond favorably to selection and that CC is moderately repeatable.

scholarly journals Genetic parameter estimates of conformation and performance traits in station-tested Limousin bulls

1994 ◽  
Vol 74 (2) ◽  
pp. 379-381 ◽  
Author(s):  
Filippo Miglior ◽  
E. B. Burnside ◽  
R. A. Kemp
Keyword(s):  
Genetic Parameter ◽  
Average Daily Gain ◽  
Parameter Estimates ◽  
Multiple Trait ◽  
Muscular Development ◽  
Scrotal Circumference ◽  
Performance Traits ◽  
Type Traits ◽  
And Performance ◽  
Highly Correlated

Genetic and residual parameters were computed for conformation and performance traits of Limousin bulls in Ontario central test stations. Following editing, data were available on 456 bulls tested in 1990. Genetic parameters for performance traits were similar to those reported in the literature. Heritability of bone score (1 — light to 9 — heavy) was 0.22 ± 0.23. Heritability of a composite muscular development score was 0.51 ± 0.14. Muscular development was positively correlated genetically with all traits studied, including average daily gain (140 d), height, scrotal circumference and bone, and very highly correlated genetically with backfat thickness and weight at end of test. Selection for muscular development using a linear scoring system is feasible, but consideration should be given to correlated responses in other economically important traits. Key words: Multiple-trait analysis, growth and type traits correlations, station-tested beef bulls

scholarly journals Genetic parameter estimates for bull prolificacy and its relationship with scrotal circumference in a commercial beef cattle population

2021 ◽  
Author(s):  
C A Russell ◽  
E J Pollak ◽  
M L Spangler
Keyword(s):  
Beef Cattle ◽  
Breeding Season ◽  
Random Effects ◽  
Fixed Effects ◽  
Genetic Parameter ◽  
Additive Genetic Effect ◽  
Parameter Estimates ◽  
Contemporary Group ◽  
Scrotal Circumference ◽  
Heritability Estimates

Abstract The commercial beef cattle industry relies heavily on the use of natural service sires. When artificial insemination is deemed difficult to implement, multi-sire breeding pastures are used to increase reproductive rates in large breeding herds or to safe-guard against bull injury during the breeding season. Although each bull might be given an equal opportunity to produce offspring, evidence suggest that there is substantial variation in the number of calves sired by each bull in a breeding pasture. With the use of DNA-based paternity testing, correctly assigning calves to their respective sires in multi-sire pastures is possible and presents an opportunity to investigate the degree to which this trait complex is under genetic control. Field data from a large commercial ranch was used to estimate genetic parameters for calf count (CC; 574 records from 443 sires) and yearling scrotal circumference (SC; n=1961) using univariate and bivariate animal models. Calf counts averaged 12.2±10.7 and SC averaged 35.4±2.30 cm. Bulls had an average of 1.30 records and there were 23.9±11.1 bulls per contemporary group. The model for CC included fixed effects of age during the breeding season (in years) and contemporary group (concatenation of breeding pasture and year). Random effects included additive genetic and permanent environmental effects, and a residual. The model for SC included fixed effects of age (in days) and contemporary group (concatenation of month and year of measurement). Random effects included an additive genetic effect and a residual. Univariate model heritability estimates for CC and SC were 0.178±0.142 and 0.455±0.072, respectively. Similarly, the bivariate model resulted in heritability estimates for CC and SC of 0.184±0.142 and 0.457±0.072, respectively. Repeatability estimates for CC from univariate and bivariate models were 0.315±0.080 and 0.317±0.080, respectively. The estimate of genetic correlation between CC and SC was 0.268±0.274. Heritability estimates suggest that both CC and SC would respond favorably to selection. Moreover, CC is lowly repeatable and although favorably correlated, SC appears to be weakly associated with CC.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

Genetic and phenotypic parameter estimates for scrotal circumference and semen traits in young beef bulls

1987 ◽  
Vol 28 (5) ◽  
pp. 547-555 ◽  
Author(s):  
T.A. Gipson ◽  
D.W. Vogt ◽  
M.R. Ellersieck ◽  
J.W. Massey
Keyword(s):  
Parameter Estimates ◽  
Scrotal Circumference ◽  
Phenotypic Parameter ◽  
Beef Bulls

Genetic parameter estimates for female proportion in tongue sole (Cynoglossus semilaevis)

Aquaculture ◽  
2021 ◽  
pp. 737652
Author(s):  
Yangzhen Li ◽  
Yuanri Hu ◽  
Yingming Yang ◽  
Jiayu Cheng ◽  
Xiangming Cheng ◽  
...  
Keyword(s):  
Genetic Parameter ◽  
Cynoglossus Semilaevis ◽  
Parameter Estimates ◽  
Tongue Sole

Genetic parameter estimates for feeding pattern and production traits in pigs

1997 ◽  
Vol 1997 ◽  
pp. 31-31
Author(s):  
A.D. Hall ◽  
W.G. Hill ◽  
P.R. Bampton ◽  
A.J. Webb
Keyword(s):  
Feed Intake ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Feeding Pattern ◽  
Parameter Estimates ◽  
Group Housing ◽  
Production Traits ◽  
Production Environment ◽  
Feeding Patterns ◽  
Potential Benefits

Until recently, to enable accurate recording of feed intake, pigs were kept in individual pens. The advent of electronic feeders has allowed accurate records of feed intake and feeding patterns in group housing which is more similar to that found in the production environment. The objectives of this study were to estimate genetic parameters for these feeding pattern traits and their correlations with production traits to show potential benefits in selection.

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