Abstract
BackgroundRecent advances in genome sequencing technologies have shifted the research bottleneck in plant sciences from genotyping to phenotyping. This shift has driven the development of phenomics, high-throughput non-invasive phenotyping technologies.ResultsWe describe an automated high-throughput phenotyping platform, the Phenovator, capable of screening 1440 Arabidopsis plants multiple times per day for photosynthesis, growth and spectral reflectance at eight wavelengths. Using this unprecedented phenotyping capacity, we have been able to detect significant genetic differences between Arabidopsis accessions for all traits measured, across both temporal and environmental scales. The high frequency of measurement allowed us to observe that heritability was not only trait specific, but for some traits was also time specific.ConclusionsSuch continuous real-time non-destructive phenotyping will allow detailed genetic and physiological investigations of the kinetics of plant homeostasis and development. The success and ultimate outcome of a breeding program will depend greatly on the genetic variance which is sampled. Our observation of temporal fluctuations in trait heritability shows that the moment of measurement can have lasting consequences. Ultimately such phenomic level technologies will provide more dynamic insights into plant physiology, and the necessary data for the omics revolution to reach its full potential.Electronic supplementary materialThe online version of this article (doi:10.1186/s13007-016-0113-y) contains supplementary material, which is available to authorized users.
Highlights
Recent advances in genome sequencing technologies have shifted the research bottleneck in plant sciences from genotyping to phenotyping
System uniformity The uniformity and reproducibility of the system were assessed by estimating the magnitude of several design factors using a mixed model, which included random effects for genotype, experiment, basin, and table position (Additional file 3: Appendix S2; Additional file 4: Data S1, Additional file 5: Data S2)
Genotypic means were calculated as the best linear unbiased estimators (BLUEs) for genotype
Summary
Recent advances in genome sequencing technologies have shifted the research bottleneck in plant sciences from genotyping to phenotyping. One prominent class of photosynthetic organisms are plants, which are responsible for the vast majority of the energy and biomass influx in the terrestrial biosphere. They are the basis of our economy, Flood et al Plant Methods (2016) 12:14. The detail and extent of phenotypic data compares poorly with the increasingly complete genotype data available [13, 22, 37] This is due to the recent advances in genomics and due to the complex multidimensional nature of phenotypes [21]. This was recognised by Houle et al [22] leading them to propose that phenomics may be understood as the “acquisition of high dimensional phenotypic data on an organism wide scale”
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