Balanced forest tree improvement can be enhanced by selecting among many parents but maintaining balance among grandparents

2008 ◽  
Vol 38 (11) ◽  
pp. 2797-2803 ◽  
Author(s):  
Dag Lindgren ◽  
Darius Danusevičius ◽  
Ola Rosvall
Keyword(s):  
Genetic Gain ◽  
Phenotypic Selection ◽  
Tree Breeding ◽  
Breeding Population ◽  
Forest Tree ◽  
Selection Strategy ◽  
Family Selection ◽  
Parent Selection ◽  
Tree Breeding Program ◽  
Balanced Tree

A model for a balanced tree breeding program that considers genetic gain and cost was used to assess the benefits of increasing the breeding population to allow for a component of among-parent selection while maintaining an equal contribution among grandparents, rather than relaying on within-family selection with an equal parental representation. The scenario used in this study had characteristics similar to those of the phenotypic selection strategy for Scots pine ( Pinus sylvestris L.) in Sweden. The results showed that investments in a greater number of parents and families to allow for among-parent selection resulted in a markedly higher genetic gain. The among-parent selection component increased the genetic gain by as much as 70% in a scenario with a high budget and no family creation costs and by as much as 20% in a scenario with a low budget and high family creation costs.

Genetic response to within-family selection using molecular markers in some radiata pine breeding schemes

2001 ◽  
Vol 31 (5) ◽  
pp. 779-785 ◽  
Author(s):  
Satish Kumar ◽  
D J Garrick
Keyword(s):  
Genetic Gain ◽  
Radiata Pine ◽  
Forest Tree ◽  
Clonal Forestry ◽  
Genetic Response ◽  
Forest Tree Breeding ◽  
Forward Selection ◽  
Family Selection ◽  
Marker Haplotype ◽  
Selection For

Marker-assisted selection (MAS) provides an opportunity to increase the efficiency of within-family selection in forest tree breeding. Within-family MAS involves selection decisions first made on conventional breeding values and quantitative trait loci (QTL) information used for within-family selection. In this study genetic response obtained by using MAS was compared with conventional methods for three options: "full-sib family forestry," "clonal forestry," and "forward selection for deployment." This comparison was undertaken using stochastic simulation for a locus that explained 10 or 20% of the genetic variance. In the full-sib family forestry scenario, markers were used to select genotypes (among juvenile individuals in a family) for vegetative propagation. Markers were used to preselect genotypes for clonal testing in clonal forestry option. In case of forward selection for deployment option, offspring that have favourable marker haplotype and a superior phenotype were selected from each family. The comparison between the MAS and the conventional strategy was evaluated in genetic terms based on comparison of the average genetic merit of the genotypes used for deployment in production plantations. The relative genetic gain (%) using MAS were found to be 4–8% and 2–3% higher compared with conventional strategy for full-sib family forestry and clonal forestry options, respectively. In case of forward selection for deployment option, MAS was generally found to be providing higher genetic gain only when the heritability is low.

scholarly journals Modeling Illustrates That Genomic Selection Provides New Opportunities for Intercrop Breeding

2021 ◽  
Vol 12 ◽  
Author(s):  
Jon Bančič ◽  
Christian R. Werner ◽  
R. Chris Gaynor ◽  
Gregor Gorjanc ◽  
Damaris A. Odeny ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genetic Correlation ◽  
Genomic Selection ◽  
Genetic Gain ◽  
Phenotypic Selection ◽  
Breeding Program ◽  
Weed Suppression ◽  
Selection Strategy ◽  
Agricultural Practice ◽  
Breeding Programs

Intercrop breeding programs using genomic selection can produce faster genetic gain than intercrop breeding programs using phenotypic selection. Intercropping is an agricultural practice in which two or more component crops are grown together. It can lead to enhanced soil structure and fertility, improved weed suppression, and better control of pests and diseases. Especially in subsistence agriculture, intercropping has great potential to optimize farming and increase profitability. However, breeding for intercrop varieties is complex as it requires simultaneous improvement of two or more component crops that combine well in the field. We hypothesize that genomic selection can significantly simplify and accelerate the process of breeding crops for intercropping. Therefore, we used stochastic simulation to compare four different intercrop breeding programs implementing genomic selection and an intercrop breeding program entirely based on phenotypic selection. We assumed three different levels of genetic correlation between monocrop grain yield and intercrop grain yield to investigate how the different breeding strategies are impacted by this factor. We found that all four simulated breeding programs using genomic selection produced significantly more intercrop genetic gain than the phenotypic selection program regardless of the genetic correlation with monocrop yield. We suggest a genomic selection strategy which combines monocrop and intercrop trait information to predict general intercropping ability to increase selection accuracy in the early stages of a breeding program and to minimize the generation interval.

Comparing gain and optimum test size from progeny testing and phenotypic selection in Pinus sylvestris

2007 ◽  
Vol 37 (7) ◽  
pp. 1227-1235 ◽  
Author(s):  
Björn Hannrup ◽  
Gunnar Jansson ◽  
Öje Danell
Keyword(s):  
Pinus Sylvestris ◽  
Genetic Parameters ◽  
Phenotypic Selection ◽  
Tree Breeding ◽  
Optimum Number ◽  
Progeny Testing ◽  
Southern Sweden ◽  
Family Selection ◽  
Investment Level ◽  
Optimum Balance

The profit from tree breeding is dependent on the amount of money invested and how these resources are spent, particularly in the testing of selection candidates. Simulations of within-family selection were used to find the optimum balance among the number of candidates, progenies per candidate, and test sites for a given investment level and to compare the profit from progeny testing and phenotypic selection. The simulations were based on genetic parameters estimated from 66 Pinus sylvestris L. progeny trials in southern Sweden and on compilations of breeding costs. For progeny testing the optimum number of candidates and test sites increased with increasing investment level, whereas the number of progenies per candidate and site decreased and stabilized at ca. 10 individuals. The maximum annual profit for the phenotypic selection was higher and occurred at a lower investment level than for progeny testing. Among the two alternatives of progeny testing studied, the intensive alternative with practices to stimulate early flowering showed a higher maximum annual profit than the base alternative.

Tissue Culture in Forestry: Economic and Genetic Potential

1986 ◽  
Vol 62 (4) ◽  
pp. 219-225 ◽  
Author(s):  
Sadiq Hasnain ◽  
William Cheliak
Keyword(s):  
Tissue Culture ◽  
Genetic Gain ◽  
Vegetative Propagation ◽  
Tree Breeding ◽  
Forest Tree ◽  
Tree Improvement ◽  
Forest Tree Breeding ◽  
Culture Methods ◽  
Breeding Programs ◽  
Genetic Potential

Vegetative propagation of Canadian conifers by tissue culture methods will allow the exploitation of the maximum genetic gain achieved in forest tree breeding programs. Tissue culture could provide a much more rapid means for delivering the genetic gain achieved to the commercial forests. Key Words: Forestry, biotechnology, plant tissue culutre, genetics, tree improvement.

Genetic gain with desired status number in breeding programs: a study on selection effects

1998 ◽  
Vol 28 (12) ◽  
pp. 1861-1869 ◽  
Author(s):  
R -P Wei ◽  
C R Hansen ◽  
N K Dhir ◽  
F C Yeh
Keyword(s):  
Genetic Gain ◽  
Breeding Population ◽  
Breeding Value ◽  
Index Selection ◽  
Selection Methods ◽  
Family Selection ◽  
Breeding Populations ◽  
High Heritability ◽  
Status Number ◽  
Restricted Selection

Genetic gain and average coancestry or status number was investigated for five selection methods: penalty index selection (PIS), family index selection (FIS), combined between-family and within-family selection (CBW), restricted individual selection (RIS), and combined index selection (RCS). PIS was a function of an individual's breeding value and family contributions, modelled as a stepwise procedure to select superior individuals one by one. A penalty would indicate the need to have low average coancestry or large status number. Breeding populations of unrelated families were investigated by Monte Carlo simulation to examine the genetic response of the five selection methods at a restricted selection intensity and average coancestry. PIS attained the greatest genetic gain, except at the selection limits of maximum genetic gain and minimum average coancestry where PIS might be identical to the other selection methods. FIS and RCS well approximated PIS at high average coancestry. RIS was similar to RCS when the heritability was high, particularly at low average coancestry. CBW attained the least genetic gain among the selection methods. For all selections, high heritability would contribute to a greater genetic gain and status number or low average coancestry. PIS was applied to a practical breeding program in Alberta that included several subpopulations. The results suggested that the selection efficiency for balancing genetic gain and average coancestry would increase when deploying a subpopulation strategy for breeding population management.

scholarly journals Modelling illustrates that genomic selection provides new opportunities for intercrop breeding

2020 ◽  
Author(s):  
Jon Bančič ◽  
Christian Werner ◽  
Chris Gaynor ◽  
Gregor Gorjanc ◽  
Damaris Odeny ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genetic Correlation ◽  
Genomic Selection ◽  
Genetic Gain ◽  
Phenotypic Selection ◽  
Breeding Program ◽  
Weed Suppression ◽  
Selection Strategy ◽  
Agricultural Practice ◽  
Breeding Programs

AbstractIntercrop breeding programs using genomic selection can produce faster genetic gain than intercrop breeding programs using phenotypic selection. Intercropping is an agricultural practice in which two or more component crops are grown together. It can lead to enhanced soil structure and fertility, improved weed suppression, and better control of pests and diseases. Especially in subsistence agriculture, intercropping has great potential to optimise farming and increase profitability. However, breeding for intercrop varieties is complex as it requires simultaneous improvement of two or more component crops that combine well in the field. We hypothesize that genomic selection can significantly simplify and accelerate the process of breeding crops for intercropping. Therefore, we used stochastic simulation to compare four different intercrop breeding programs implementing genomic selection and an intercrop breeding program entirely based on phenotypic selection. We assumed three different levels of genetic correlation between monocrop grain yield and intercrop grain yield to investigate how the different breeding strategies are impacted by this factor. We found that all four simulated breeding programs using genomic selection produced significantly more intercrop genetic gain than the phenotypic selection program regardless of the genetic correlation with monocrop yield. We suggest a genomic selection strategy which combines monocrop and intercrop trait information to predict general intercropping ability to increase selection accuracy in early stages of a breeding program and to minimize the generation interval.

scholarly journals Increasing selection gain and accuracy of harvest prediction models in Jatropha through genome-wide selection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Adriano dos Santos ◽  
Erina Vitório Rodrigues ◽  
Bruno Galvêas Laviola ◽  
Larissa Pereira Ribeiro Teodoro ◽  
Paulo Eduardo Teodoro ◽  
...  
Keyword(s):  
Prediction Models ◽  
Block Design ◽  
Phenotypic Selection ◽  
Breeding Population ◽  
Breeding Cycle ◽  
Selection Cycle ◽  
Genome Wide ◽  
Random Block ◽  
Random Block Design ◽  
Number Of Individuals

AbstractGenome-wide selection (GWS) has been becoming an essential tool in the genetic breeding of long-life species, as it increases the gain per time unit. This study had a hypothesis that GWS is a tool that can decrease the breeding cycle in Jatropha. Our objective was to compare GWS with phenotypic selection in terms of accuracy and efficiency over three harvests. Models were developed throughout the harvests to evaluate their applicability in predicting genetic values in later harvests. For this purpose, 386 individuals of the breeding population obtained from crossings between 42 parents were evaluated. The population was evaluated in random block design, with six replicates over three harvests. The genetic effects of markers were predicted in the population using 811 SNP's markers with call rate = 95% and minor allele frequency (MAF) > 4%. GWS enables gains of 108 to 346% over the phenotypic selection, with a 50% reduction in the selection cycle. This technique has potential for the Jatropha breeding since it allows the accurate obtaining of GEBV and higher efficiency compared to the phenotypic selection by reducing the time necessary to complete the selection cycle. In order to apply GWS in the first harvests, a large number of individuals in the breeding population are needed. In the case of few individuals in the population, it is recommended to perform a larger number of harvests.

scholarly journals Genomics and breeding innovations for enhancing genetic gain for climate resilience and nutrition traits

2021 ◽  
Author(s):  
Pallavi Sinha ◽  
Vikas K. Singh ◽  
Abhishek Bohra ◽  
Arvind Kumar ◽  
Jochen C. Reif ◽  
...  
Keyword(s):  
Statistical Methods ◽  
Genetic Gain ◽  
Crop Improvement ◽  
Breeding Population ◽  
Breeding Cycle ◽  
Climate Resilience ◽  
Heritability Estimation ◽  
Improvement Programs ◽  
Statistical Designs ◽  
Novel Alleles

Abstract Key message Integrating genomics technologies and breeding methods to tweak core parameters of the breeder’s equation could accelerate delivery of climate-resilient and nutrient rich crops for future food security. Abstract Accelerating genetic gain in crop improvement programs with respect to climate resilience and nutrition traits, and the realization of the improved gain in farmers’ fields require integration of several approaches. This article focuses on innovative approaches to address core components of the breeder’s equation. A prerequisite to enhancing genetic variance (σ2g) is the identification or creation of favorable alleles/haplotypes and their deployment for improving key traits. Novel alleles for new and existing target traits need to be accessed and added to the breeding population while maintaining genetic diversity. Selection intensity (i) in the breeding program can be improved by testing a larger population size, enabled by the statistical designs with minimal replications and high-throughput phenotyping. Selection priorities and criteria to select appropriate portion of the population too assume an important role. The most important component of breeder′s equation is heritability (h2). Heritability estimates depend on several factors including the size and the type of population and the statistical methods. The present article starts with a brief discussion on the potential ways to enhance σ2g in the population. We highlight statistical methods and experimental designs that could improve trait heritability estimation. We also offer a perspective on reducing the breeding cycle time (t), which could be achieved through the selection of appropriate parents, optimizing the breeding scheme, rapid fixation of target alleles, and combining speed breeding with breeding programs to optimize trials for release. Finally, we summarize knowledge from multiple disciplines for enhancing genetic gains for climate resilience and nutritional traits.

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