Data from: Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis

Significantly improved crop varieties are urgently needed to feed the
rapidly growing human population under changing climates. While genome
sequence information and excellent genomic tools are in place for major
crop species, the systematic quantification of phenotypic traits or
components thereof in a high-throughput fashion remains an enormous
challenge. In order to help bridge the genotype to phenotype gap, we
developed a comprehensive framework for high-throughput phenotype data
analysis in plants, which enables the extraction of an extensive list of
phenotypic traits from nondestructive plant imaging over time. As a proof
of concept, we investigated the phenotypic components of the drought
responses of 18 different barley (Hordeum vulgare) cultivars during
vegetative growth. We analyzed dynamic properties of trait expression over
growth time based on 54 representative phenotypic features. The data are
highly valuable to understand plant development and to further quantify
growth and crop performance features. We tested various growth models to
predict plant biomass accumulation and identified several relevant
parameters that support biological interpretation of plant growth and
stress tolerance. These image-based traits and model-derived parameters
are promising for subsequent genetic mapping to uncover the genetic basis
of complex agronomic traits. Taken together, we anticipate that the
analytical framework and analysis results presented here will be useful to
advance our views of phenotypic trait components underlying plant
development and their responses to environmental cues.