Yellow Dwarf Virus Resistance in Barley: Phenotyping, Remote Imagery, and Virus–Vector Characterization

Author:

Massman Chris1ORCID,Rivedal Hannah M.2,Dorman Seth J.2,Tanner K. Christy1,Fredrickson Chance3,Temple Todd N.2,Fisk Scott1,Helgerson Laura1,Hayes Patrick M.1ORCID

Affiliation:

1. Department of Crop and Soil Science, Oregon State University, Corvallis, OR 97331

2. U.S. Department of Agriculture-Agricultural Research Service, Forage Seed and Cereal Research Unit, Corvallis, OR 97331

3. Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331

Abstract

Yellow dwarf viruses (YDVs) spread by aphids are some of the most economically important barley ( Hordeum vulgare) virus–vector complexes worldwide. Detection and control of these viruses are critical components in the production of barley, wheat, and numerous other grasses of agricultural importance. Genetic control of plant diseases is often preferable to chemical control to reduce the environmental and economic cost of foliar insecticides. Accordingly, the objectives of this work were to (i) screen a barley population for resistance to YDVs under natural infection using phenotypic assessment of disease symptoms, (ii) implement drone imagery to further assess resistance and test its utility as a disease screening tool, (iii) identify the prevailing virus and vector types in the experimental environment, and (iv) perform a genome-wide association study to identify genomic regions associated with measured traits. Significant genetic differences were found in a population of 192 barley inbred lines regarding their YDV symptom severity, and symptoms were moderately to highly correlated with grain yield. The YDV severity measured with aerial imaging was highly correlated with on-the-ground estimates ( r = 0.65). Three aphid species vectoring three YDV species were identified with no apparent genotypic influence on their distribution. A quantitative trait locus impacting YDV resistance was detected on chromosome 2H, albeit undetected using aerial imaging. However, quantitative trait loci for canopy cover and mean normalized difference vegetation index were successfully mapped using the drone. This work provides a framework for utilizing drone imagery in future resistance breeding efforts for YDVs in cereals and grasses, as well as in other virus–vector disease complexes.

Funder

U.S. Department of Agriculture-Research, Education, and Economics-Agricultural Research Service

Publisher

Scientific Societies

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