Practical application of genomic selection in a doubled-haploid winter wheat breeding program

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F17%3A73938" target="_blank" >RIV/60460709:41320/17:73938 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s11032-017-0715-8" target="_blank" >http://dx.doi.org/10.1007/s11032-017-0715-8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11032-017-0715-8" target="_blank" >10.1007/s11032-017-0715-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Practical application of genomic selection in a doubled-haploid winter wheat breeding program

Popis výsledku v původním jazyce

Crop improvement is a long-term, expensive institutional endeavor. Genomic selection (GS), which uses single nucleotide polymorphism (SNP) information to estimate genomic breeding values, has proven efficient to increasing genetic gain by accelerating the breeding process in animal breeding programs. As for crop improvement, with few exceptions, GS applicability remains in the evaluation of algorithm performance. In this study, we examined factors related to GS applicability in line development stage for grain yield using a hard red winter wheat (Triticum aestivum L.) doubled-haploid population. The performance of GS was evaluated in two consecutive years to predict grain yield. In general, the semi-parametric reproducing kernel Hilbert space prediction algorithm outperformed parametric genomic best linear unbiased prediction. For both parametric and semi-parametric algorithms, an upward bias in predictability was apparent in within-year cross-validation, suggesting the prerequisite of cross-year val

Název v anglickém jazyce

Practical application of genomic selection in a doubled-haploid winter wheat breeding program

Popis výsledku anglicky

Crop improvement is a long-term, expensive institutional endeavor. Genomic selection (GS), which uses single nucleotide polymorphism (SNP) information to estimate genomic breeding values, has proven efficient to increasing genetic gain by accelerating the breeding process in animal breeding programs. As for crop improvement, with few exceptions, GS applicability remains in the evaluation of algorithm performance. In this study, we examined factors related to GS applicability in line development stage for grain yield using a hard red winter wheat (Triticum aestivum L.) doubled-haploid population. The performance of GS was evaluated in two consecutive years to predict grain yield. In general, the semi-parametric reproducing kernel Hilbert space prediction algorithm outperformed parametric genomic best linear unbiased prediction. For both parametric and semi-parametric algorithms, an upward bias in predictability was apparent in within-year cross-validation, suggesting the prerequisite of cross-year val

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40106 - Agronomy, plant breeding and plant protection; (Agricultural biotechnology to be 4.4)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MOLECULAR BREEDING

ISSN

1380-3743

e-ISSN

—

Svazek periodika

37

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

15

Strana od-do

1-15

Kód UT WoS článku

000411138800002

EID výsledku v databázi Scopus

2-s2.0-85028637119