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Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Whe...

Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Whe...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3169764521

Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

About this item

Full title

Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

Publisher

United States: Oxford University Press

Journal title

G3 : genes - genomes - genetics, 2019-04, Vol.9 (4), p.1231-1247

Language

English

Formats

Publication information

Publisher

United States: Oxford University Press

More information

Scope and Contents

Contents

Abstract
Hyperspectral reflectance phenotyping and genomic selection are two emerging technologies that have the potential to increase plant breeding efficiency by improving prediction accuracy for grain yield. Hyperspectral cameras quantify canopy reflectance across a wide range of wavelengths that are associated with numerous biophysical and b...

Alternative Titles

Full title

Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_3169764521

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3169764521

Other Identifiers

ISSN

2160-1836

E-ISSN

2160-1836

DOI

10.1534/g3.118.200856

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