phenoSeeder - A robot system for automated handling and phenotyping of individual seeds

  • The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning methods delivering only two-dimensional data, often termed seed size. However, three-dimensional traits, such as the volume or mass of single seeds, are very rarely determined in routine measurements. Here, we introduce a device named phenoSeeder, which enables the handling and phenotyping of individual seeds of very different sizes. The system consists of a pick-and-place robot and a modular setup of sensors that can be versatilely extended. Basic biometric traits detected for individual seeds are two-dimensional data from projections, three-dimensional data from volumetric measures, and mass, from which seed density is also calculated. Each seed is tracked by an identifier and, after phenotyping, can be planted, sorted, or individually stored for further evaluation or processing (e.g. in routine seed-to-plant tracking pipelines). By investigating seeds of Arabidopsis (Arabidopsis thaliana), rapeseed (Brassica napus), and barley (Hordeum vulgare), we observed that, even for apparently round-shaped seeds of rapeseed, correlations between the projected area and the mass of seeds were much weaker than between volume and mass. This indicates that simple projections may not deliver good proxies for seed mass. Although throughput is limited, we expect that automated seed phenotyping on a single-seed basis can contribute valuable information for applications in a wide range of wild or crop species, including seed classification, seed sorting, and assessment of seed quality.

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Metadaten
Author:Siegfried Jahnke, Johanna Roussel, Thomas Hombach, Johannes Kochs, Andreas Fischbach, Gregor Huber, Hanno Scharr
DOI:https://doi.org/10.1104/pp.16.01122
ISSN:0032-0889
Parent Title (English):Plant physiology
Publisher:Oxford University Press
Place of publication:Oxford
Document Type:Article
Language:English
Year of Completion:2016
Volume:172
Issue:3
First Page:1358
Last Page:1370
Link:https://doi.org/10.1104/pp.16.01122
Zugriffsart:weltweit
Institutes:FH Aachen / Fachbereich Medizintechnik und Technomathematik
collections:Verlag / Oxford University Press
Open Access / Hybrid