Use of spectral reflectance for indirect selection of yield potential and stability in Pacific Northwest winter wheat

The use of canopy spectral reflectance as a high throughput selection method has been recommended to augment genetic gain from yield based selection in highly variable environments. The objectives of this study were to estimate genotypic correlations between grain yield and spectral reflectance indices (SRIs), and estimate heritability, expected response to selection, relative efficiency of indirect selection, and accuracy of yield predictive models in Pacific Northwest winter wheat (Triticum aestivum L.) under a range of moisture regimes. A diversity panel of 402 winter wheat genotypes (87 hard and 315 soft) was grown in rain-fed and irrigated conditions across the eastern Washington in 2012 and 2013. Canopy spectral reflectance measured at heading, milk, soft dough, and hard dough stages were used to derive several SRIs which generally had higher broad sense heritability (H-2) than yield per se. Grain yield and SRIs showed generally high genetic variability and response to selection in moist-cool rain-fed condition. Efficiency of indirect selection for yield using SRIs was high in drought environment and exceeded efficiency of yield based selection in the soft winter subgroup. Normalized water band index (NWI) showed consistent response to selection across environments, higher genetic correlation with yield (0.51-0.80, p<0.001), and highest indirect selection efficiency (up to 143%). A yield predictive model with one or more SRIs explained 41-82% of total variation in grain yield (p<0.001). The repeatability of genotypic performance between years increased when selection was conducted based on both SRIs and grain yield compared to selection based on yield or SRI alone. The generally high heritability of SRIs and their significant genotypic correlation with grain yield highlight the possibility to improve yield and yield stability in winter wheat through remotely sensed phenotyping approaches. (C) 2016 The Author(s). Published by Elsevier B.V.