title: Dissecting spatiotemporal biomass accumulation in barley under different water regimes using high-throughput image analysis.
abstract: Phenotyping large numbers of genotypes still represents the rate-limiting step in many plant genetic experiments and in breeding. To address this issue, novel automated phenotyping technologies have been developed. We investigated for a core set of barley cultivars if high-throughput image analysis can help to dissect vegetative biomass accumulation in response to two different watering regimes under semi-controlled greenhouse conditions. We found that experiments, treatments, genotypes and genotype by environment interaction (G × E) can be characterized at any time point by certain digital traits. Biomass accumulation under control and stress conditions was highly heritable. Growth model-derived maximum vegetative biomass (K max), inflection point (I) and regrowth rate (k) were identified as promising candidate traits for genome-wide association studies. Drought stress symptoms can be visualized, dissected and modelled. Especially the highly heritable regrowth rate, which had the biggest influence on biomass accumulation in stress treatment, seems promising for future studies to improve drought tolerance in different crop species. A proof of concept study revealed potential correlations between digital traits obtained from pot experiments under greenhouse conditions and agronomic traits from field experiments. Overall, non-invasive, imaging-based phenotyping platforms under greenhouse conditions offer excellent possibilities for trait discovery, trait development and industrial applications.
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
authors.forename: Kerstin
authors.initials: K
authors.lastname: Neumann
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
authors.forename: Christian
authors.initials: C
authors.lastname: Klukas
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.|BASF SE, Limburgerhof, Germany.
authors.forename: Swetlana
authors.initials: S
authors.lastname: Friedel
authors.affiliation: Technische Universität München (TUM), Freising-Weihenstephan, Germany.
authors.forename: Pablo
authors.initials: P
authors.lastname: Rischbeck
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
authors.forename: Dijun
authors.initials: D
authors.lastname: Chen
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Entzian
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
authors.forename: Nils
authors.initials: N
authors.lastname: Stein
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Graner
authors.affiliation: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.|Innovation Center, BCS R&D, Bayer CropScience NV, Gent, Belgium.
authors.forename: Benjamin
authors.identifier: http://orcid.org/0000-0002-9145-6980
authors.initials: B
authors.lastname: Kilian
mesh_terms: D018533:Biomass; D055864:Droughts; D059647:Gene-Environment Interaction; D001467:Hordeum / Q000033:anatomy & histology / Q000235:genetics / Q000254:growth & development* / Q000502:physiology; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D010641:Phenotype; D013312:Stress, Physiological; D014867:Water / Q000502:physiology
chemical_list: D014867:Water
keywords: drought; modelling; non-invasive phenotyping