Title |
Non-destructive Phenotypic Analysis of Early Stage Tree Seedling Growth Using an Automated Stereovision Imaging Method
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Published in |
Frontiers in Plant Science, October 2016
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DOI | 10.3389/fpls.2016.01644 |
Pubmed ID | |
Authors |
Antonio Montagnoli, Mattia Terzaghi, Nicoletta Fulgaro, Borys Stoew, Jan Wipenmyr, Dag Ilver, Cristina Rusu, Gabriella S. Scippa, Donato Chiatante |
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. |
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Unknown | 1 | 100% |
Demographic breakdown
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 44 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 10 | 23% |
Student > Ph. D. Student | 6 | 14% |
Professor | 5 | 11% |
Other | 4 | 9% |
Student > Master | 4 | 9% |
Other | 5 | 11% |
Unknown | 10 | 23% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 20 | 45% |
Environmental Science | 3 | 7% |
Biochemistry, Genetics and Molecular Biology | 2 | 5% |
Engineering | 2 | 5% |
Computer Science | 1 | 2% |
Other | 3 | 7% |
Unknown | 13 | 30% |