Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program

Wheat ( L.) cultivars must possess suitable end-use quality for release and consumer acceptability. However, breeding for quality traits is often considered a secondary target relative to yield largely because of amount of seed needed and expense. Without testing and selection, many undesirable mate...

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Main Authors: Sarah D. Battenfield, Carlos Guzmán, R. Chris Gaynor, Ravi P. Singh, Roberto J. Peña, Susanne Dreisigacker, Allan K. Fritz, Jesse A. Poland
Format: Article
Language:English
Published: Wiley 2016-07-01
Series:The Plant Genome
Online Access:https://dl.sciencesocieties.org/publications/tpg/articles/9/2/plantgenome2016.01.0005
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author Sarah D. Battenfield
Carlos Guzmán
R. Chris Gaynor
Ravi P. Singh
Roberto J. Peña
Susanne Dreisigacker
Allan K. Fritz
Jesse A. Poland
author_facet Sarah D. Battenfield
Carlos Guzmán
R. Chris Gaynor
Ravi P. Singh
Roberto J. Peña
Susanne Dreisigacker
Allan K. Fritz
Jesse A. Poland
author_sort Sarah D. Battenfield
collection DOAJ
description Wheat ( L.) cultivars must possess suitable end-use quality for release and consumer acceptability. However, breeding for quality traits is often considered a secondary target relative to yield largely because of amount of seed needed and expense. Without testing and selection, many undesirable materials are advanced, expending additional resources. Here, we develop and validate whole-genome prediction models for end-use quality phenotypes in the CIMMYT bread wheat breeding program. Model accuracy was tested using forward prediction on breeding lines ( = 5520) tested in unbalanced yield trials from 2009 to 2015 at Ciudad Obregon, Sonora, Mexico. Quality parameters included test weight, 1000-kernel weight, hardness, grain and flour protein, flour yield, sodium dodecyl sulfate sedimentation, Mixograph and Alveograph performance, and loaf volume. In general, prediction accuracy substantially increased over time as more data was available to train the model. Reflecting practical implementation of genomic selection (GS) in the breeding program, forward prediction accuracies () for quality parameters were assessed in 2015 and ranged from 0.32 (grain hardness) to 0.62 (mixing time). Increased selection intensity was possible with GS since more entries can be genotyped than phenotyped and expected genetic gain was 1.4 to 2.7 times higher across all traits than phenotypic selection. Given the limitations in measuring many lines for quality, we conclude that GS is a powerful tool to facilitate early generation selection for end-use quality in wheat, leaving larger populations for selection on yield during advanced testing and leading to better gain for both quality and yield in bread wheat breeding programs.
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spelling doaj.art-bfaf008e380f4b9f9fe085087656f3222022-12-21T23:44:09ZengWileyThe Plant Genome1940-33722016-07-019210.3835/plantgenome2016.01.0005plantgenome2016.01.0005Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding ProgramSarah D. BattenfieldCarlos GuzmánR. Chris GaynorRavi P. SinghRoberto J. PeñaSusanne DreisigackerAllan K. FritzJesse A. PolandWheat ( L.) cultivars must possess suitable end-use quality for release and consumer acceptability. However, breeding for quality traits is often considered a secondary target relative to yield largely because of amount of seed needed and expense. Without testing and selection, many undesirable materials are advanced, expending additional resources. Here, we develop and validate whole-genome prediction models for end-use quality phenotypes in the CIMMYT bread wheat breeding program. Model accuracy was tested using forward prediction on breeding lines ( = 5520) tested in unbalanced yield trials from 2009 to 2015 at Ciudad Obregon, Sonora, Mexico. Quality parameters included test weight, 1000-kernel weight, hardness, grain and flour protein, flour yield, sodium dodecyl sulfate sedimentation, Mixograph and Alveograph performance, and loaf volume. In general, prediction accuracy substantially increased over time as more data was available to train the model. Reflecting practical implementation of genomic selection (GS) in the breeding program, forward prediction accuracies () for quality parameters were assessed in 2015 and ranged from 0.32 (grain hardness) to 0.62 (mixing time). Increased selection intensity was possible with GS since more entries can be genotyped than phenotyped and expected genetic gain was 1.4 to 2.7 times higher across all traits than phenotypic selection. Given the limitations in measuring many lines for quality, we conclude that GS is a powerful tool to facilitate early generation selection for end-use quality in wheat, leaving larger populations for selection on yield during advanced testing and leading to better gain for both quality and yield in bread wheat breeding programs.https://dl.sciencesocieties.org/publications/tpg/articles/9/2/plantgenome2016.01.0005
spellingShingle Sarah D. Battenfield
Carlos Guzmán
R. Chris Gaynor
Ravi P. Singh
Roberto J. Peña
Susanne Dreisigacker
Allan K. Fritz
Jesse A. Poland
Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program
The Plant Genome
title Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program
title_full Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program
title_fullStr Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program
title_full_unstemmed Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program
title_short Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program
title_sort genomic selection for processing and end use quality traits in the cimmyt spring bread wheat breeding program
url https://dl.sciencesocieties.org/publications/tpg/articles/9/2/plantgenome2016.01.0005
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