A comparison of alternative nucleus breeding systems and a sire referencing scheme for sheep improvement

1996 ◽  
Vol 62 (2) ◽  
pp. 265-270 ◽  
Author(s):  
J. A. Roden
Keyword(s):  
Selection Response ◽  
Best Linear Unbiased Prediction ◽  
Breeding Systems ◽  
Linear Unbiased Prediction ◽  
Sequential Selection ◽  
Best Linear Unbiased ◽  
The Mean ◽  
Nucleus Breeding ◽  
Open Nucleus ◽  
Selection Of

AbstractStochastic simulation was used to compare selection response and rate of inbreeding in four nucleus breeding systems and a sire referencing scheme for sheep: an open nucleus system (ONS), an open nucleus system with sequential selection of the nucleus (ONS-S), a sire referencing scheme (SRS) and a dispersed open nucleus system (DONS). Selection was based on best linear unbiased prediction of breeding values for a single trait measurable on all individuals prior to selection. Selection in a population of 1200 ewes equally divided into 10 flocks was simulated over a 15-year period. The mean rate of genetic gain was proportionately about 0-15 higher in ONS-S and DONS compared with ONS and SRS. The rate of inbreeding in SRS was considerably lower and in ONS-S, considerably higher, than in the other systems. The level of prolificacy in the population did not influence the relative ranking of the breeding systems but may have implications for their optimal structure.

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.

A comparison of the rate of genetic gain and inbreeding in open nucleus and closed flock breeding systems for sheep.

1993 ◽  
Vol 1993 ◽  
pp. 34-34
Author(s):  
Janet A. Roden
Keyword(s):  
Breeding Population ◽  
Best Linear Unbiased Prediction ◽  
Breeding Systems ◽  
Optimum Structure ◽  
Linear Unbiased Prediction ◽  
Sheep Breeding ◽  
Group Breeding ◽  
Breeding Schemes ◽  
Best Linear Unbiased ◽  
Open Nucleus

Open nucleus systems (ONS) have been used in sheep breeding for a number of years, usually in group breeding schemes. In the simplest form the population is divided into two tiers, the nucleus flock composed of elite individuals, while the base, which forms the majority of the population, is usually sub-divided into a number of individual flocks. Animals born in the nucleus may be selected as replacements in the base, while superior animals born in the base may become part of the breeding population of the nucleus. The optimum structure and genetic benefits of using an ONS under Australasian conditions have been extensively studied using deterministic predictions (James, 1977; Mueller and James, 1983). However, subsequent advances in genetic evaluation (e.g. the application of Best Linear Unbiased Prediction (BLUP)) and the smaller flock sizes typical in Europe, are likely to impact on the outcome and optimum structure of such systems.

Combined selection of progeny in crop breeding using best linear unbiased prediction

2012 ◽  
Vol 92 (3) ◽  
pp. 553-562 ◽  
Author(s):  
José Marcelo Soriano Viana ◽  
Vinícius Ribeiro Faria ◽  
Fabyano Fonseca e Silva ◽  
Marcos Deon Vilela de Resende
Keyword(s):  
Least Squares ◽  
Best Linear Unbiased Prediction ◽  
Pedigree Information ◽  
Crop Breeding ◽  
Additive Variance ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Combined Selection ◽  
Selection Of ◽  
Unbiased Prediction

Viana, J. M. S., Faria, V. R., Fonseca e Silva, F. and Vilela de Resende, M. D. 2012. Combined selection of progeny in crop breeding using best linear unbiased prediction. Can. J. Plant Sci. 92: 553–562. Combined selection is an important strategy in crop breeding. As the classical index does not consider pedigree information, the objective of this study was to evaluate the efficiency of the best linear unbiased prediction (BLUP) methodology for combined selection of progeny. We analyzed expansion volume (EV) and grain yield of parents and inbred and non-inbred progeny from the popcorn population Viçosa. The BLUP analyses, single-trait and of the same character measured in parents and progeny (combined parent-family) were performed using the ASReml software. Because the experiments were balanced, the estimates of the additive variance from the BLUP and least squares analyses were generally equivalent. The accuracies of the BLUP analyses do not clearly establish the superior technique. The accuracy of the classical index tended to be higher than that obtained from BLUP analyses. There was equivalence between BLUP and least squares analyses relative to half-sib and inbred progeny selection, and superiority of the combined parent-family BLUP index for full-sib selection. The BLUP analyses also differed from the least squares analysis on the coincidence of selected parents. The populations obtained by selection based on BLUP of breeding values presented a lower effective size.

scholarly journals Selection of forage oat genotypes through GGE Biplot and BLUP

2020 ◽  
Author(s):  
Franklin Santos ◽  
y Félix Marza
Keyword(s):  
Statistical Methods ◽  
Dry Matter ◽  
Best Linear Unbiased Prediction ◽  
Dry Matter Yield ◽  
Gge Biplot ◽  
Average Yield ◽  
Phenotypic Stability ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Selection Of

AbstractIn Bolivia, there is a low predominance of forage oat productivity. Therefore, it was proposed to select more productive and stable genotypes through statistical methods of GGE Biplot and BLUP. The research was conducted in three environments in Bolivia and six commercial varieties of forage oats were evaluated; three of them correspond to INIA Peru and the rest of Bolivia. Data were analyzed through GGE Biplot and BLUP (Best Linear Unbiased Prediction) and an average yield of 10.29 ±3.51 t ha−1 of dry matter was obtained. BLUP accumulated greater variance than GGE Biplot in the first two components. In terms of productivity and stability values, both models have the same selection trend. Thus, Tayco and Texas were selected for their outstanding characteristic in dry matter yield and phenotypic stability.

scholarly journals Genetic Variation in Drought-Tolerance Traits and Their Relationships to Growth in Pinus radiata D. Don Under Water Stress

2022 ◽  
Vol 12 ◽  
Author(s):  
Ahmed Ismael ◽  
Jianming Xue ◽  
Dean Francis Meason ◽  
Jaroslav Klápště ◽  
Marta Gallart ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Water Stress ◽  
Genetic Correlations ◽  
Best Linear Unbiased Prediction ◽  
Linear Unbiased Prediction ◽  
Breeding Programs ◽  
Water Stress Tolerance ◽  
Drought Tolerant ◽  
Best Linear Unbiased ◽  
Selection Of

The selection of drought-tolerant genotypes is globally recognized as an effective strategy to maintain the growth and survival of commercial tree species exposed to future drought periods. New genomic selection tools that reduce the time of progeny trials are required to substitute traditional tree breeding programs. We investigated the genetic variation of water stress tolerance in New Zealand-grown Pinus radiata D. Don using 622 commercially-used genotypes from 63 families. We used quantitative pedigree-based (Genomic Best Linear Unbiased Prediction or ABLUP) and genomic-based (Genomic Best Linear Unbiased Prediction or GBLUP) approaches to examine the heritability estimates associated with water stress tolerance in P. radiata. Tree seedling growth traits, foliar carbon isotope composition (δ13C), and dark-adapted chlorophyll fluorescence (Y) were monitored before, during and after 10 months of water stress. Height growth showed a constant and moderate heritability level, while the heritability estimate for diameter growth and δ13C decreased with water stress. In contrast, chlorophyll fluorescence exhibited low heritability after 5 and 10 months of water stress. The GBLUP approach provided less breeding value accuracy than ABLUP, however, the relative selection efficiency of GBLUP was greater compared with ABLUP selection techniques. Although there was no significant relationship directly between δ13C and Y, the genetic correlations were significant and stronger for GBLUP. The positive genetic correlations between δ13C and tree biomass traits under water stress indicated that intraspecific variation in δ13C was likely driven by differences in the genotype’s photosynthetic capacity. The results show that foliar δ13C can predict P. radiata genotype tolerance to water stress using ABLUP and GBLUP approaches and that such approaches can provide a faster screening and selection of drought-tolerant genotypes for forestry breeding programs.

scholarly journals ESTIMATES OF GENETIC PARAMETERS USING RELM/BLUP FOR INTRA-POPULATIONAL GENETIC BREEDING OF Platonia insignis Mart.

2016 ◽  
Vol 40 (3) ◽  
pp. 561-573 ◽  
Author(s):  
Maria Clideana Cabral Maia ◽  
Luciano Medina Macedo ◽  
Lúcio Flavo Lopes Vasconcelos ◽  
João Pedro Alves Aquino ◽  
Luís Cláudio Oliveira ◽  
...  
Keyword(s):  
Variance Components ◽  
Genetic Parameters ◽  
Recurrent Selection ◽  
Indirect Selection ◽  
Best Linear Unbiased Prediction ◽  
Selection Differential ◽  
Linear Unbiased Prediction ◽  
Genetic Breeding ◽  
Best Linear Unbiased ◽  
Selection Of

ABSTRACT The aim of this study was to estimate genetic parameters to support the selection of bacuri progenies for a first cycle of recurrent selection, using the REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure to estimate the variance components and genotypic values. Were evaluated twelve variables in a total of 210 fruits from 39 different seed trees, from a field trial with an experimental design of incomplete blocks with clonal replies among subplots. The three variables related with the fruit development (weight, diameter, length) showed strong correlation, and where fruit length showed higher heritability and potential to be used for indirect selection. Among the 39 progenies evaluated in this study, five present potential to compose the next cycle of recurrent selection, due they hold good selection differential either to agrotechnological variables as to development of bacuri fruit.

Genetic Parameters and Selection in Full-Sib Families of Tall Fescue Using Best Linear Unbiased Prediction (BLUP) Analysis of Animal Breeding and Genetic

2021 ◽  
Author(s):  
Fatemeh Pirnajmedin ◽  
Mohammad Mahdi Majidi ◽  
Mohammad Hadi Taleb ◽  
Davoud Rostami
Keyword(s):  
Ssr Markers ◽  
Tall Fescue ◽  
Genetic Parameters ◽  
Best Linear Unbiased Prediction ◽  
Forage Yield ◽  
Linear Unbiased Prediction ◽  
Breeding Programs ◽  
Sib Families ◽  
Best Linear Unbiased ◽  
Selection Of

Abstract Background: Better understanding of genetic structure of economic traits is crucial for identification and selection of superior genotypes in specific breeding programs. Best linear unbiased prediction (BLUP) is the most efficient method in this regards, which is poorly used in forage plant breeding. The present study aimed to assess genetic variation, estimate genetic parameters, and predict breeding values of five essential traits in full sib families (recognized by EST-SSR markers) of tall fescue using REML/BLUP procedure. Method: Forty-two full-sib families of tall fescue (included of 120 individual genotypes), recognized by EST-SSR markers’ along with twenty-one their corresponding parental genotypes were assessed for biomass production and agro-morphological traits at three harvests (spring, summer, and autumn) in the field during 4 years (2017-2020). Results: Considerable genotypic variability was observed for all traits. Low narrow-sense heritability (h2n) for dry forage yield (DFY) at three harvest indicates that non-additive gene actions may play an important role in the inheritance of this trait. Higher h2n of yield related traits and flowering time and also significant genetic correlation of these traits with forage yield, suggests that selection based on these traits via developing an index may lead to indirect genetic improvement of DFY. Conclusion: Our results showed the adequacy of REML/BLUP procedure for identification and selection of preferable parental genotypes and progenies with higher breeding values for future breeding programs such as variety development in tall fescue. Parental genotypes 21M, 1M, and 20L were identified as superior and stable genotypes and could also produce the best hybrid combinations when they were mostly used as maternal parent.

scholarly journals Prediction of genotypic values and estimation of genetic parameters in common bean

2008 ◽  
Vol 51 (3) ◽  
pp. 465-472 ◽  
Author(s):  
Alisson Fernando Chiorato ◽  
Sérgio Augusto Morais Carbonell ◽  
Luiz Antônio dos Santos Dias ◽  
Marcos Deon Vilela de Resende
Keyword(s):  
Common Bean ◽  
Genetic Parameters ◽  
High Accuracy ◽  
Best Linear Unbiased Prediction ◽  
Broad Sense Heritability ◽  
Phaseolus Vulgaris L ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Estimation Of Genetic Parameters ◽  
Selection Of

Eighteen common bean (Phaseolus vulgaris L.) genotypes were evaluated in 25 environments of the state of São Paulo in 2001 and 2002. The estimation of genetic parameters by the Restricted Maximum Likelihood (REML) and the prediction of genotypic values via Best Linear Unbiased Prediction (BLUP) were obtained by software Selegen-REML/BLUP. The estimate of the broad-sense heritability was low for the grain yield (0.03), since it took individual plots into consideration and was free of the effects of interaction with years, cultivation periods and site. Nevertheless, the heritability at the level of line means across the various environments was high (0.75), allowing a high accuracy (0.87) in the selection of lines for planting in the environment mean. Among the 18 genotypes, the predicted genotypic values of nine were higher than the general mean. The genetic gain predicted with the selection of the best line, in this case line Gen 96A31 of the IAC, was 16.25%.

Sign in / Sign up

Export Citation Format

Share Document