@article{JahnkeRousselHombachetal.2016,
  author    = {Jahnke, Siegfried and Roussel, Johanna and Hombach, Thomas and Kochs, Johannes and Fischbach, Andreas and Huber, Gregor and Scharr, Hanno},
  title     = {phenoSeeder - A robot system for automated handling and phenotyping of individual seeds},
  series = {Plant physiology},
  volume    = {172},
  journal   = {Plant physiology},
  number    = {3},
  publisher = {Oxford University Press},
  address   = {Oxford},
  issn      = {0032-0889},
  doi       = {10.1104/pp.16.01122},
  pages     = {1358 -- 1370},
  year      = {2016},
  abstract  = {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.},
  language  = {en}
}
@article{JahnkeMenzelDusschotenetal.2009,
  author    = {Jahnke, Siegfried and Menzel, Marion I. and Dusschoten, Dagmar van and Roeb, Gerhard W. and B{\"u}hler, Jonas and Minwuyelet, Senay and Bl{\"u}mler, Peter and Temperton, Vicky M. and Hombach, Thomas and Streun, Matthias and Beer, Simone and Khodaverdi, Maryam and Ziemons, Karl and Coenen, Heinz H. and Schurr, Ulrich},
  title     = {Combined MRI-PET dissects dynamic changes in plant structures and functions},
  series = {The Plant Journal},
  volume    = {59},
  journal   = {The Plant Journal},
  number    = {4},
  publisher = {Wiley},
  address   = {Weinheim},
  isbn      = {1365-313X},
  pages     = {634 -- 644},
  year      = {2009},
  abstract  = {Unravelling the factors determining the allocation of carbon to various plant organs is one of the great challenges of modern plant biology. Studying allocation under close to natural conditions requires non-invasive methods, which are now becoming available for measuring plants on a par with those developed for humans. By combining magnetic resonance imaging (MRI) and positron emission tomography (PET), we investigated three contrasting root/shoot systems growing in sand or soil, with respect to their structures, transport routes and the translocation dynamics of recently fixed photoassimilates labelled with the short-lived radioactive carbon isotope 11C. Storage organs of sugar beet (Beta vulgaris) and radish plants (Raphanus sativus) were assessed using MRI, providing images of the internal structures of the organs with high spatial resolution, and while species-specific transport sectoralities, properties of assimilate allocation and unloading characteristics were measured using PET. Growth and carbon allocation within complex root systems were monitored in maize plants (Zea mays), and the results may be used to identify factors affecting root growth in natural substrates or in competition with roots of other plants. MRI-PET co-registration opens the door for non-invasive analysis of plant structures and transport processes that may change in response to genomic, developmental or environmental challenges. It is our aim to make the methods applicable for quantitative analyses of plant traits in phenotyping as well as in understanding the dynamics of key processes that are essential to plant performance.},
  language  = {en}
}