Genetic Architecture of Phenomic-Enabled Canopy Coverage in Glycine max
| Autor: | Keith A. Cherkauer, Anthony A. Hearst, Katy M. Rainey, Benjamin Hall, Alencar Xavier |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0106 biological sciences
0301 basic medicine Canopy Quantitative Trait Loci Quantitative trait locus Biology Investigations Breeding 01 natural sciences Genetic correlation Chromosomes Plant 03 medical and health sciences Phenomics Yield (wine) Genetics GWAS Genetics of Complex Traits canopy Phenology food and beverages Chromosome Mapping phenomics SoyNAM Genetic architecture 030104 developmental biology Phenotype Agronomy Trait Soybeans 010606 plant biology & botany |
| Zdroj: | Genetics |
| ISSN: | 1943-2631 0016-6731 |
| Popis: | Digital imagery can help to quantify seasonal changes in desirable crop phenotypes that can be treated as quantitative traits. Because limitations in precise and functional phenotyping restrain genetic improvement in the postgenomic era, imagery-based phenomics could become the next breakthrough to accelerate genetic gains in field crops. Whereas many phenomic studies focus on exploratory analysis of spectral data without obvious interpretative value, we used field images to directly measure soybean canopy development from phenological stage V2 to R5. Over 3 years, we collected imagery using ground and aerial platforms of a large and diverse nested association panel comprising 5555 lines. Genome-wide association analysis of canopy coverage across sampling dates detected a large quantitative trait locus (QTL) on soybean (Glycine max, L. Merr.) chromosome 19. This QTL provided an increase in yield of 47.3 kg ha−1. Variance component analysis indicated that a parameter, described as average canopy coverage, is a highly heritable trait (h2 = 0.77) with a promising genetic correlation with grain yield (0.87), enabling indirect selection of yield via canopy development parameters. Our findings indicate that fast canopy coverage is an early season trait that is inexpensive to measure and has great potential for application in breeding programs focused on yield improvement. We recommend using the average canopy coverage in multiple trait schemes, especially for the early stages of the breeding pipeline (including progeny rows and preliminary yield trials), in which the large number of field plots makes collection of grain yield data challenging. |
| Databáze: | OpenAIRE |
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