Genomic Prediction and Indirect Selection for Grain Yield in US Pacific Northwest Winter Wheat Using Spectral Reflectance Indices from High-Throughput Phenotyping.

Dennis N Lozada,Jayfred V Godoy,Arron H Carter,Brian P Ward

doi:10.3390/ijms21010165

Abstract

Secondary traits from high-throughput phenotyping could be used to select for complex target traits to accelerate plant breeding and increase genetic gains. This study aimed to evaluate the potential of using spectral reflectance indices (SRI) for indirect selection of winter-wheat lines with high yield potential and to assess the effects of including secondary traits on the prediction accuracy for yield. A total of five SRIs were measured in a diversity panel, and F5 and doubled haploid wheat breeding populations planted between 2015 and 2018 in Lind and Pullman, WA. The winter-wheat panels were genotyped with 11,089 genotyping-by-sequencing derived markers. Spectral traits showed moderate to high phenotypic and genetic correlations, indicating their potential for indirect selection of lines with high yield potential. Inclusion of correlated spectral traits in genomic prediction models resulted in significant (p < 0.001) improvement in prediction accuracy for yield. Relatedness between training and test populations and heritability were among the principal factors affecting accuracy. Our results demonstrate the potential of using spectral indices as proxy measurements for selecting lines with increased yield potential and for improving prediction accuracy to increase genetic gains for complex traits in US Pacific Northwest winter wheat.

Highlights

Trait phenotyping is a major constraint in plant breeding due to the number of lines that need to be evaluated in multiple environments and trials
Significant (p < 0.001) phenotypic correlations of spectral reflectance indices (SRI) with grain yield were observed across different developmental stages (Table 1) for the winter-wheat diversity panel (DP)
The present study showed the potential of indirect selection of high-yielding winter-wheat lines, using SRI collected from High-throughput phenotyping (HTP)

Summary

Introduction

Trait phenotyping is a major constraint in plant breeding due to the number of lines that need to be evaluated in multiple environments and trials. Secondary traits that are generally more heritable and are correlated with grain yield such as spectral reflectance indices (SRI) from HTP have been utilized for indirect selection of wheat lines with high yield potential [6,7]. SRIs utilizing only near-infrared (NIR) wavelengths include the Normalized Water Index (NWI), whereas those including wavelengths in both the visible and NIR regions of the electromagnetic spectrum include the Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR) [7]. The Normalized Difference Red Edge (NDRE) index utilizes wavelengths from the red-edge region of the electromagnetic spectrum [9,10] These values can be used to evaluate correlated traits associated with crop yield and productivity such as biomass, vegetation and water status, greenness, and the degree of senescence of plant canopies [11,12,13,14]

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