scholarly journals Genetic parameters of gestation length trait in dromedary camels (Camelus dromedarius)

2021 ◽  
Author(s):  
Szabolcs Bene ◽  
Ferenc Szabó ◽  
Péter J. Polgár ◽  
Judit Juhász ◽  
Péter Nagy
Keyword(s):  
United Arab Emirates ◽  
Genetic Parameters ◽  
Breeding Value ◽  
Dromedary Camel ◽  
Gestation Length ◽  
Dromedary Camels ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Species Specific ◽  
Maternal Heritability

Abstract Gestation length (GL) data of dromedary camels were analysed for the period from 2007 to 2018. The database of the largest dairy camel herds (Dubai, United Arab Emirates) was used in this study. The data of 4,084 camels included in the assessment were classified into six ecotypes (Emirati, Emirati cross, Black, Pakistani, Saudi-Sudanese and Saudi cross). The aim of the study was to describe the heritability of GL of camels and the breeding value (BV) of sires for this trait. The genetic parameters of GL were estimated by the General Linear Model method and two Best Linear Unbiased Prediction (BLUP) animal models as well. The mean (±SE) of GL of camels was 384.3 ± 0.2 days. The direct heritability of GL (0.26 ± 0.06–0.36 ± 0.08) was higher than the maternal heritability (0.00 ± 0.05–0.13 ± 0.06) obtained. The maternal permanent environmental effect (0.15 ± 0.05) was similar to the results estimated previously in dromedary camel, but higher than the data reported by relevant sources in other species. Based on the results of this study it can be concluded that the GL of dromedary camels is a species-specific value similar to that in cattle, which is less affected by the maternal influence. Considerable differences (16 days) exist among male dromedaries in their BV for the GL trait.

A method for reducing inbreeding with Best Linear Unbiased Prediction

1993 ◽  
Vol 1993 ◽  
pp. 33-33
Author(s):  
B Grundy ◽  
WG Hill
Keyword(s):  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Best Linear Unbiased Predictor ◽  
Linear Unbiased Prediction ◽  
Genetic Merit ◽  
Selection Decisions ◽  
Best Linear Unbiased ◽  
Estimated Breeding Value ◽  
Commercial Environment ◽  
Unbiased Prediction

An optimum way of selecting animals is through a prediction of their genetic merit (estimated breeding value, EBV), which can be achieved using a best linear unbiased predictor (BLUP) (Henderson, 1975). Selection decisions in a commercial environment, however, are rarely made solely on genetic merit but also on additional factors, an important example of which is to limit the accumulation of inbreeding. Comparison of rates of inbreeding under BLUP for a range of hentabilities highlights a trend of increasing inbreeding with decreasing heritability. It is therefore proposed that selection using a heritability which is artificially raised would yield lower rates of inbreeding than would otherwise be the case.

A simulation study of open nucleus and closed nucleus breeding systems in a sheep population

1995 ◽  
Vol 60 (1) ◽  
pp. 117-124 ◽  
Author(s):  
J. A. Roden
Keyword(s):  
Genetic Gain ◽  
Live Weight ◽  
Breeding Systems ◽  
Breeding Value ◽  
Linear Unbiased Prediction ◽  
Sheep Population ◽  
Best Linear Unbiased ◽  
Nucleus Breeding ◽  
Open Nucleus ◽  
Selection Of

AbstractStochastic simulation was used to compare the results of alternative breeding systems in a sheep population divided into 10 flocks of 120 ewes. The breeding systems compared were selection within closed flocks (CF), a closed nucleus system (CNS), an open nucleus system (ONS) and open nucleus systems with the selection of nucleus replacements being restricted to either nucleus born males (ONSRm) or nucleus born females (ONSRf). Selection was for a best linear unbiased prediction of breeding value for lamb live weight which had a heritability of 0·17. The open nucleus breeding systems (ONS, ONSRm, ONSRf) resulted in higher rates of genetic gain, more predictable selection responses and lower rates of inbreeding than either the closed nucleus system (CNS) or selection within closed flocks (CF). Initial genetic differences between flocks resulted in higher rates of genetic gain in the nucleus breeding systems due to the use of between flock genetic variance. In the ONS system up to 25% of nucleus sires and approximately 50% of nucleus dams were born in base flocks. Nevertheless if selection of either nucleus sires or dams was restricted to nucleus born animals there was very little change in genetic gain or rate of inbreeding.

scholarly journals Weaning results of beef Hungarian Fleckvieh calves 2. Genetic parameters, breeding values

2010 ◽  
Vol 53 (1) ◽  
pp. 26-36 ◽  
Author(s):  
S. Bene ◽  
I. Füller ◽  
A. Fördős ◽  
F. Szabó
Keyword(s):  
Genetic Parameters ◽  
Correlation Coefficients ◽  
Breeding Value ◽  
Phenotypic Variance ◽  
Weaning Weight ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Genetic Value ◽  
Maternal Heritability ◽  
Daily Gain

Abstract. Weaning weight, preweaning daily gain and 205-day weight of Hungarian Fleckvieh calves (n=8 929, bulls =4 539, heifers =4 390) born from 232 sires between 1980 and 2003 were examined. Variance, covariance components and heritability values and correlation coefficients were estimated. The effect of the maternal permanent environment on genetic parameters and breeding values were examined. Two animal models were used for breeding value estimation. The direct heritability (hd2) of weaning weight, preweaning daily gain and 205-day weight was between 0.37 and 0.42. The maternal heritability (hm2) of these traits was 0.06 and 0.07. The direct-maternal correlations (rdm) were medium and negative −0.52 and −0.74. Contribution of the maternal heritability and maternal permanent environment to phenotype is smaller than that of direct heritabilities (hm2+c2< hd2). The ratio of the variance of maternal permanent environment in the phenotypic variance (c2) changed from 3 to 6 %. Estimated breeding values changed whether the permanent environmental effect of dam wasn’t taken into consideration but the rank of the animals was not modified. The genetic value for weaning results of Hungarian Fleckvieh population has increased since 1997.

scholarly journals Estimation of genetic parameters and (co)variance components for weaning traits of Charolais population in Hungary

2007 ◽  
Vol 50 (5) ◽  
pp. 447-454
Author(s):  
F. Szabó ◽  
Z. Lengyel ◽  
Z. Domokos ◽  
S. Bene
Keyword(s):  
Variance Components ◽  
Genetic Parameters ◽  
Mean Value ◽  
Breeding Value ◽  
Direct Effects ◽  
Birth Season ◽  
Progeny Tests ◽  
Maternal Heritability ◽  
Daily Gain ◽  
Estimation Of Genetic Parameters

Abstract. Weaning performance of 10 808 purebred offsprings (4991 male and 5817 female) of 80 sires in 13 farms were analised using animal model. Heritability, breeding value, (co)variance components for weaning weight (WW), preweaning daily gain (PDG), 205-day weight (CWW) were calculated. Farm, parity, year of birth, season of birth, sex were treated as fixed, and the maternal permanent environment was treated as random effects. In case of WW and PDG, the age of the calves at weaning was fitted as a covariant. Data were analyzed with MTDFREML (Boldman et al. 1993) program. The overall mean value and standard deviation of WW, PDG and CWW were 221±47 kg, 1,111±0.21 kg/day and 226±42 kg, respectively. The age of the calves at weaning was 202 days. The direct heritability (h2d) of WW and PDG were 0.57±0.08, 0.49±0.07 and CWW was 0.44±0.06, respectively. The maternal heritability (h2m) of these traits were 0.32±0.09, 0.33±0.10 and 0.33±0.09, respectively. The direct-maternal correlations (rdm) were strong and negative. The medium heritability estimates for direct effects suggest that progeny tests should be used in this population to increase genetic improvement.

scholarly journals Prediction of Rates of Inbreeding in Populations Selected on Best Linear Unbiased Prediction of Breeding Value

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 361-373
Author(s):  
Piter Bijma ◽  
John A Woolliams
Keyword(s):  
Linear Model ◽  
Goodness Of Fit ◽  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Quadratic Model ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Wide Range ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Abstract Predictions for the rate of inbreeding (ΔF) in populations with discrete generations undergoing selection on best linear unbiased prediction (BLUP) of breeding value were developed. Predictions were based on the concept of long-term genetic contributions using a recently established relationship between expected contributions and rates of inbreeding and a known procedure for predicting expected contributions. Expected contributions of individuals were predicted using a linear model, μi(x) = α βsi, where si denotes the selective advantage as a deviation from the contemporaries, which was the sum of the breeding values of the individual and the breeding values of its mates. The accuracy of predictions was evaluated for a wide range of population and genetic parameters. Accurate predictions were obtained for populations of 5–20 sires. For 20–80 sires, systematic underprediction of on average 11% was found, which was shown to be related to the goodness of fit of the linear model. Using simulation, it was shown that a quadratic model would give accurate predictions for those schemes. Furthermore, it was shown that, contrary to random selection, ΔF less than halved when the number of parents was doubled and that in specific cases ΔF may increase with the number of dams.

scholarly journals The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

Animals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 569
Author(s):  
Chen Wei ◽  
Hanpeng Luo ◽  
Bingru Zhao ◽  
Kechuan Tian ◽  
Xixia Huang ◽  
...  
Keyword(s):  
Rank Correlation ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Breeding Value ◽  
Genomic Information ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Merino Sheep ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992–2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h2 values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

Use of the REML/BLUP methodology for the selection of sweet orange genotypes

2021 ◽  
Vol 56 ◽  
Author(s):  
Márcia da Costa Capistrano ◽  
Romeu de Carvalho Andrade Neto ◽  
Vanderley Borges dos Santos ◽  
Lauro Saraiva Lessa ◽  
Marcos Deon Vilela de Resende ◽  
...  
Keyword(s):  
Genetic Parameters ◽  
Sweet Orange ◽  
Superior Performance ◽  
Yield Potential ◽  
Components Of Variance ◽  
Linear Unbiased Prediction ◽  
Character Set ◽  
Best Linear Unbiased ◽  
Fruit Mass ◽  
Selection Of

Abstract: The objective of this work was to select superior sweet orange (Citrus sinensis) genotypes with higher yield potential based on data from eight harvests, using the residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology. The experiment was carried out from 2002 to 2008 and in 2010 in the municipality of Rio Branco, in the state of Acre, Brazil. Analyzes of deviance were performed to test the significance of the components of variance according to the random effects of the used model, and parameters were estimated from individual genotypic and phenotypic variances. A selection intensity of 20% was adopted regarding genotypic selection, i.e., only the best 11 of the 55 genotypes tested were selected. The estimates of the genetic parameters show the existence of genetic variability and the selection potential of the studied sweet orange genotypes. The genotypic correlation between harvests is of low magnitude, except for the variable average fruit mass, and, as a reflex, there is a change in the ordering of the genotypes. Genotypes 5, 48, 19, 14, and 47 stand out as being the most productive, and, therefore, are the most suitable for selection purposes. Genotypes 14 and 47 show superior performance for the character set evaluated.

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