Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Non-destructive phenotypic analysis of early stage tree seedling growth using an automated stereovision imaging method
RISE, Swedish ICT, Acreo.
Show others and affiliations
2016 (English)In: Frontiers in Plant Science, ISSN 1664-462X, E-ISSN 1664-462X, Vol. 7, article id 1644Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2016. Vol. 7, article id 1644
Keywords [en]
Biomass, Fagus sylvatica L, Picea abies L, Pinus sylvestris L, Plant phenotype, Quercus ilex L, RGB image analysis, Seedlings
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-32564DOI: 10.3389/fpls.2016.01644Scopus ID: 2-s2.0-84994646159OAI: oai:DiVA.org:ri-32564DiVA, id: diva2:1155608
Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus
By organisation
Acreo
In the same journal
Frontiers in Plant Science
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 4 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.34.0