Genomic prediction of yield and root development in wheat under changing water availability

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Genomic prediction of yield and root development in wheat under changing water availability. / Guo, Xiangyu; Svane, Simon F.; Fuchtbauer, Winnie S.; Andersen, Jeppe R.; Jensen, Just; Thorup-Kristensen, Kristian.

In: Plant Methods, Vol. 16, No. 1, 90, 2020.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Guo, X, Svane, SF, Fuchtbauer, WS, Andersen, JR, Jensen, J & Thorup-Kristensen, K 2020, 'Genomic prediction of yield and root development in wheat under changing water availability', Plant Methods, vol. 16, no. 1, 90. https://doi.org/10.1186/s13007-020-00634-0

APA

Guo, X., Svane, S. F., Fuchtbauer, W. S., Andersen, J. R., Jensen, J., & Thorup-Kristensen, K. (2020). Genomic prediction of yield and root development in wheat under changing water availability. Plant Methods, 16(1), [90]. https://doi.org/10.1186/s13007-020-00634-0

Vancouver

Guo X, Svane SF, Fuchtbauer WS, Andersen JR, Jensen J, Thorup-Kristensen K. Genomic prediction of yield and root development in wheat under changing water availability. Plant Methods. 2020;16(1). 90. https://doi.org/10.1186/s13007-020-00634-0

Author

Guo, Xiangyu ; Svane, Simon F. ; Fuchtbauer, Winnie S. ; Andersen, Jeppe R. ; Jensen, Just ; Thorup-Kristensen, Kristian. / Genomic prediction of yield and root development in wheat under changing water availability. In: Plant Methods. 2020 ; Vol. 16, No. 1.

Bibtex

@article{2887e72c80e649a2ab160ec484d5f925,
title = "Genomic prediction of yield and root development in wheat under changing water availability",
abstract = "Background Deeper roots help plants take up available resources in deep soil ensuring better growth and higher yields under conditions of drought. A large-scale semi-field root phenotyping facility was developed to allow a water availability gradient and detect potential interaction of genotype by water availability gradient. Genotyped winter wheat lines were grown as rows in four beds of this facility, where indirect genetic effects from neighbors could be important to trait variation. The objective was to explore the possibility of genomic prediction for grain-related traits and deep root traits collected via images taken in a minirhizotron tube under each row of winter wheat measured. Results The analysis comprised four grain-related traits: grain yield, thousand-kernel weight, protein concentration, and total nitrogen content measured on each half row that were harvested separately. Two root traits, total root length between 1.2 and 2 m depth and root length in four intervals on each tube were also analyzed. Two sets of models with or without the effects of neighbors from both sides of each row were applied. No interaction between genotypes and changing water availability were detected for any trait. Estimated genomic heritabilities ranged from 0.263 to 0.680 for grain-related traits and from 0.030 to 0.055 for root traits. The coefficients of genetic variation were similar for grain-related and root traits. The prediction accuracy of breeding values ranged from 0.440 to 0.598 for grain-related traits and from 0.264 to 0.334 for root traits. Including neighbor effects in the model generally increased the estimated genomic heritabilities and accuracy of predicted breeding values for grain yield and nitrogen content. Conclusions Similar relative amounts of additive genetic variance were found for both yield traits and root traits but no interaction between genotypes and water availability were detected. It is possible to obtain accurate genomic prediction of breeding values for grain-related traits and reasonably accurate predicted breeding values for deep root traits using records from the semi-field facility. Including neighbor effects increased the estimated additive genetic variance of grain-related traits and accuracy of predicting breeding values. High prediction accuracy can be obtained although heritability is low.",
keywords = "Genomic prediction, Wheat, Semi-field, Grain-related yield, Deep root, NITROGEN-USE EFFICIENCY, GRAIN-YIELD, MULTILEVEL SELECTION, POPULATION-STRUCTURE, ASSISTED SELECTION, INHERITANCE, CULTIVARS, ACCURACY, TRAITS, PLAINS",
author = "Xiangyu Guo and Svane, {Simon F.} and Fuchtbauer, {Winnie S.} and Andersen, {Jeppe R.} and Just Jensen and Kristian Thorup-Kristensen",
year = "2020",
doi = "10.1186/s13007-020-00634-0",
language = "English",
volume = "16",
journal = "Plant Methods",
issn = "1746-4811",
publisher = "BioMed Central",
number = "1",

}

RIS

TY - JOUR

T1 - Genomic prediction of yield and root development in wheat under changing water availability

AU - Guo, Xiangyu

AU - Svane, Simon F.

AU - Fuchtbauer, Winnie S.

AU - Andersen, Jeppe R.

AU - Jensen, Just

AU - Thorup-Kristensen, Kristian

PY - 2020

Y1 - 2020

N2 - Background Deeper roots help plants take up available resources in deep soil ensuring better growth and higher yields under conditions of drought. A large-scale semi-field root phenotyping facility was developed to allow a water availability gradient and detect potential interaction of genotype by water availability gradient. Genotyped winter wheat lines were grown as rows in four beds of this facility, where indirect genetic effects from neighbors could be important to trait variation. The objective was to explore the possibility of genomic prediction for grain-related traits and deep root traits collected via images taken in a minirhizotron tube under each row of winter wheat measured. Results The analysis comprised four grain-related traits: grain yield, thousand-kernel weight, protein concentration, and total nitrogen content measured on each half row that were harvested separately. Two root traits, total root length between 1.2 and 2 m depth and root length in four intervals on each tube were also analyzed. Two sets of models with or without the effects of neighbors from both sides of each row were applied. No interaction between genotypes and changing water availability were detected for any trait. Estimated genomic heritabilities ranged from 0.263 to 0.680 for grain-related traits and from 0.030 to 0.055 for root traits. The coefficients of genetic variation were similar for grain-related and root traits. The prediction accuracy of breeding values ranged from 0.440 to 0.598 for grain-related traits and from 0.264 to 0.334 for root traits. Including neighbor effects in the model generally increased the estimated genomic heritabilities and accuracy of predicted breeding values for grain yield and nitrogen content. Conclusions Similar relative amounts of additive genetic variance were found for both yield traits and root traits but no interaction between genotypes and water availability were detected. It is possible to obtain accurate genomic prediction of breeding values for grain-related traits and reasonably accurate predicted breeding values for deep root traits using records from the semi-field facility. Including neighbor effects increased the estimated additive genetic variance of grain-related traits and accuracy of predicting breeding values. High prediction accuracy can be obtained although heritability is low.

AB - Background Deeper roots help plants take up available resources in deep soil ensuring better growth and higher yields under conditions of drought. A large-scale semi-field root phenotyping facility was developed to allow a water availability gradient and detect potential interaction of genotype by water availability gradient. Genotyped winter wheat lines were grown as rows in four beds of this facility, where indirect genetic effects from neighbors could be important to trait variation. The objective was to explore the possibility of genomic prediction for grain-related traits and deep root traits collected via images taken in a minirhizotron tube under each row of winter wheat measured. Results The analysis comprised four grain-related traits: grain yield, thousand-kernel weight, protein concentration, and total nitrogen content measured on each half row that were harvested separately. Two root traits, total root length between 1.2 and 2 m depth and root length in four intervals on each tube were also analyzed. Two sets of models with or without the effects of neighbors from both sides of each row were applied. No interaction between genotypes and changing water availability were detected for any trait. Estimated genomic heritabilities ranged from 0.263 to 0.680 for grain-related traits and from 0.030 to 0.055 for root traits. The coefficients of genetic variation were similar for grain-related and root traits. The prediction accuracy of breeding values ranged from 0.440 to 0.598 for grain-related traits and from 0.264 to 0.334 for root traits. Including neighbor effects in the model generally increased the estimated genomic heritabilities and accuracy of predicted breeding values for grain yield and nitrogen content. Conclusions Similar relative amounts of additive genetic variance were found for both yield traits and root traits but no interaction between genotypes and water availability were detected. It is possible to obtain accurate genomic prediction of breeding values for grain-related traits and reasonably accurate predicted breeding values for deep root traits using records from the semi-field facility. Including neighbor effects increased the estimated additive genetic variance of grain-related traits and accuracy of predicting breeding values. High prediction accuracy can be obtained although heritability is low.

KW - Genomic prediction

KW - Wheat

KW - Semi-field

KW - Grain-related yield

KW - Deep root

KW - NITROGEN-USE EFFICIENCY

KW - GRAIN-YIELD

KW - MULTILEVEL SELECTION

KW - POPULATION-STRUCTURE

KW - ASSISTED SELECTION

KW - INHERITANCE

KW - CULTIVARS

KW - ACCURACY

KW - TRAITS

KW - PLAINS

U2 - 10.1186/s13007-020-00634-0

DO - 10.1186/s13007-020-00634-0

M3 - Journal article

C2 - 32625241

VL - 16

JO - Plant Methods

JF - Plant Methods

SN - 1746-4811

IS - 1

M1 - 90

ER -

ID: 249533703