title: Non-destructive Phenotypic Analysis of Early Stage Tree Seedling Growth Using an Automated Stereovision Imaging Method.
abstract: A plant phenotyping approach was applied to evaluate growth rate of containerized tree seedlings during the precultivation phase following seed germination. A simple and affordable stereo optical system was used to collect stereoscopic red-green-blue (RGB) images of seedlings at regular intervals of time. Comparative analysis of these images by means of a newly developed software enabled us to calculate (a) the increments of seedlings height and (b) the percentage greenness of seedling leaves. Comparison of these parameters with destructive biomass measurements showed that the height traits can be used to estimate seedling growth for needle-leaved plant species whereas the greenness trait can be used for broad-leaved plant species. Despite the need to adjust for plant type, growth stage and light conditions this new, cheap, rapid, and sustainable phenotyping approach can be used to study large-scale phenome variations due to genome variability and interaction with environmental factors.
authors.affiliation: Laboratory of Environmental and Applied Botany, Department of Biotechnology and Life Science, University of Insubria Varese, Italy.
authors.forename: Antonio
authors.initials: A
authors.lastname: Montagnoli
authors.affiliation: Laboratory of Environmental and Applied Botany, Department of Biotechnology and Life Science, University of Insubria Varese, Italy.
authors.forename: Mattia
authors.initials: M
authors.lastname: Terzaghi
authors.affiliation: Laboratory of Environmental and Applied Botany, Department of Biotechnology and Life Science, University of Insubria Varese, Italy.
authors.forename: Nicoletta
authors.initials: N
authors.lastname: Fulgaro
authors.affiliation: Sensor Systems Department, Acreo Swedish ICT Gothenburg, Sweden.
authors.forename: Borys
authors.initials: B
authors.lastname: Stoew
authors.affiliation: Sensor Systems Department, Acreo Swedish ICT Gothenburg, Sweden.
authors.forename: Jan
authors.initials: J
authors.lastname: Wipenmyr
authors.affiliation: Sensor Systems Department, Acreo Swedish ICT Gothenburg, Sweden.
authors.forename: Dag
authors.initials: D
authors.lastname: Ilver
authors.affiliation: Sensor Systems Department, Acreo Swedish ICT Gothenburg, Sweden.
authors.forename: Cristina
authors.initials: C
authors.lastname: Rusu
authors.affiliation: Department of Biosciences and Territory, University of Molise Pesche, Italy.
authors.forename: Gabriella S
authors.initials: GS
authors.lastname: Scippa
authors.affiliation: Laboratory of Environmental and Applied Botany, Department of Biotechnology and Life Science, University of Insubria Varese, Italy.
authors.forename: Donato
authors.initials: D
authors.lastname: Chiatante
keywords: Fagus sylvatica L.; Picea abies L.; Pinus sylvestris L.; Quercus ilex L.; RGB image analysis; biomass; plant phenotype; seedlings