title: Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis.
abstract: 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.
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, P.R. China.
authors.forename: Dijun
authors.initials: D
authors.lastname: Chen
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany.
authors.forename: Kerstin
authors.initials: K
authors.lastname: Neumann
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany.
authors.forename: Swetlana
authors.initials: S
authors.lastname: Friedel
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Kilian
authors.affiliation: Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, P.R. China.
authors.forename: Ming
authors.initials: M
authors.lastname: Chen
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany.
authors.forename: Thomas
authors.initials: T
authors.lastname: Altmann
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany klukas@ipk-gatersleben.de.
authors.forename: Christian
authors.initials: C
authors.lastname: Klukas
mesh_terms: D016000:Cluster Analysis; D018556:Crops, Agricultural / Q000033:anatomy & histology / Q000254:growth & development* / Q000378:metabolism; D055864:Droughts; D056726:Genetic Association Studies; D001467:Hordeum / Q000033:anatomy & histology / Q000254:growth & development* / Q000378:metabolism; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D010641:Phenotype; D013312:Stress, Physiological; D014867:Water / Q000378:metabolism*
chemical_list: D014867:Water