Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL.

Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL. Research Abstract Details 

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Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL. Abstract Text:

T A Schrag,A E Melchinger,A P Sørensen,M Frisch,

Prediction methods to identify single-cross hybrids with superior yield performance have the potential to greatly improve the efficiency of commercial maize (Zea mays L.) hybrid breeding programs. Our objectives were to (1) identify marker loci associated with quantitative trait loci for hybrid performance or specific combining ability (SCA) in maize, (2) compare hybrid performance prediction by genotypic value estimates with that based on general combining ability (GCA) estimates, and (3) investigate a newly proposed combination of the GCA model with SCA predictions from genotypic value estimates. A total of 270 hybrids was evaluated for grain yield and grain dry matter content in four Dent x Flint factorial mating experiments, their parental inbred lines were genotyped with 20 AFLP primer-enzyme combinations. Markers associated significantly with hybrid performance and SCA were identified, genotypic values and SCA effects were estimated, and four hybrid performance prediction approaches were evaluated. For grain yield, between 38 and 98 significant markers were identified for hybrid performance and between zero and five for SCA. Estimates of prediction efficiency (R (2)) ranged from 0.46 to 0.86 for grain yield and from 0.59 to 0.96 for grain dry matter content. Models enhancing the GCA approach with SCA estimates resulted in the highest prediction efficiency if the SCA to GCA ratio was high. We conclude that it is advantageous for prediction of single-cross hybrids to enhance a GCA-based model with SCA effects estimated from molecular marker data, if SCA variances are of similar or larger importance as GCA variances.

Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL. Publishing Authors By Initials

TA Schrag,AE Melchinger,AP Sørensen,M Frisch,

For similar plants: plant families and groups: angiosperms: poaceae: zea mays research abstracts see: plants: plant families and groups: angiosperms: poaceae: zea mays research

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Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: TAG. Theoretical and applied genetics. Theoretisch

VOLUME: 113

Page Numbers: 1037-47

Journal Abbreviation: Theor. Appl. Genet.

ISSN: 0040-5752

DAY: 3

MONTH: 08

YEAR: 2006

Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL. Information

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LANGUAGE: eng

NlmUniqueID: 145600

Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL. Keywords Mesh Terms:

KEYWORDS: Zea mays

MESH TERMS: growth & development

Chemical & Substance for Abstract: Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL. Information

Substance Name: Genetic Markers

Registry Number: 0

Grant and Affiliation Information for Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL.

AFFILIATION: Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, 70593 Stuttgart, Germany.

Country: Germany

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MEDLINETA: Theor Appl Genet

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