Greenhouse Scanalyzer Systems

Automated Indoor Phenotyping

The GREENHOUSE SCANALYZER continuously monitors hundreds of plants under controlled conditions without human intervention. With options for both plant-to-sensor and sensor-to-plant automation, LemnaTec is the world’s leading supplier of automated indoor phenotyping systems. A movie of a sample installation is available here.

Plants are transported by conveyers through a series of imaging cabinets, each cabinet hosting a different sensor, to capture several hundred data points per plant per run. LemnaTec’s innovative MULTIVIEW system rotates each plant to capture images from all sides, as well as from above. This results in comprehensive quantitative data about the physiological and genetic traits of plants and the parameters that control plant development.

GREENHOUSE SCANALYZER systems are built to suit our customers’ requirements using standardised modules. The available imaging cabinet dimensions are shown below.

Request more information and quotation here.

Greenhouse Scanalyzer Plant-to-Sensor
Greenhouse Scanalyzer Plant-to-Sensor

Technical Specifications

Module options

Conveyer systems
Imaging cabinets
Light tunnel
Watering station
Spraying station
Weighing station
Barcodes
Multi-View turn and lift unit

Sensor options

RGB Visible
PS2 Fluorescence
Fluorescence
Near Infrared

Control

Dedicated Windows PC plus database server

Software

Process control, Image processing, Data analysis

RGBPS2FLUNIR
Direct Measures
Size
Morphology
Colour
Fluorescence
NIR reflectance

unusual but maybe possible

Applications

Corn Leaf Segmenter

LemnaGrid can create a topological skeleton from a shape. This allows us to split an imaged plant into its larger constituents: leaf/branch and stem.

Show Application

Graph To Object Converter

In this post, we leverage a few skeleton graphs and morphological operations to analyse the leaf insertion angle, which is defined as the angle between the stem and branching leaf blade.

Show Application

HSI to grey converter

The ‘HSI to grey converter’ is a useful LemnaGrid tool to convert an RGB image into a more human intuitive color appearance system, i.e. the hue-saturation-intensity (HSI) model.

Show Application

References

2017

  • Parlati, Aurora; Valkov, Vladimir T.; D'Apuzzo, Enrica; Alves, Ludovico M.; Petrozza, Angelo; Summerer, Stephan; Costa, Alex; Cellini, Francesco; Vavasseur, Alain; Chiurazzi, Maurizio (2017)

    Ectopic Expression of PII Induces Stomatal Closure in Lotus japonicus. In: Frontiers in Plant Science, DOI: 10.3389/fpls.2017.01299. https://www.frontiersin.org/articles/10.3389/fpls.2017.01299/full

  • van de Velde, Karel; Chandler, Peter Michael; van der Straeten, Dominique; Rohde, Antje (2017)

    Differential coupling of gibberellin responses by Rht-B1c suppressor alleles and Rht-B1b in wheat highlights a unique role for the DELLA N-terminus in dormancy. In: Journal of Experimental Botany, DOI: 10.1093/jxb/erw471. https://academic.oup.com/jxb/article-lookup/doi/10.1093/jxb/erw471

  • Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C. (2017)

    High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging. In: Frontiers in Plant Science, DOI: 10.3389/fpls.2017.01348. http://journal.frontiersin.org/article/10.3389/fpls.2017.01348/full

  • Guo, Doudou; Juan, Jiaxiang; Chang, Liying; Zhang, Jingjin; Huang, Danfeng (2017)

    Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques. In: Scientific reports, DOI: 10.1038/s41598-017-08235-z. http://www.nature.com/articles/s41598-017-08235-z

  • Liang, Zhikai; Pandey, Piyush; Stoerger, Vincent; Xu, Yuhang; Qiu, Yumou; Ge, Yufeng; Schnable, James C. (2017)

    Conventional and hyperspectral time-series imaging of maize lines widely used in field trials. In: bioRxiv, DOI: 10.1101/169045. https://www.biorxiv.org/content/early/2017/09/21/169045

  • Meng, Rui; Saade, Stephanie; Kurtek, Sebastian; Berger, Bettina; Brien, Chris; Pillen, Klaus; Tester, Mark; Sun, Ying (2017)

    Growth curve registration for evaluating salinity tolerance in barley. In: Plant methods, S. 18. DOI: 10.1186/s13007-017-0165-7. http://plantmethods.biomedcentral.com/articles/10.1186/s13007-017-0165-7

  • Kerstin Neumann, Yusheng Zhao, Jianting Chu, Jens Keilwagen, Jochen C. Reif, Benjamin Kilian and Andreas Graner (2017)

    Genetic architecture and temporal patterns of biomass accumulation in spring barley revealed by image analysis. In: BMC Plant Biology, DOI: 10.1186/s12870-017-1085-4. https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-017-1085-4

2016

  • Amanda, Dhika; Doblin, Monika Susanne; Galletti, Roberta; Bacic, Antony; Ingram, Gwyneth C.; Johnson, Kim L.; Doblin, Monika S. (2016)

    DEFECTIVE KERNEL1 (DEK1) regulates cell walls in the leaf epidermis // DEFECTIVE KERNEL1 (DEK1) Regulates Cell Walls in the Leaf Epidermis. In: PLANT PHYSIOLOGY, S. 2204–2218. DOI: 10.1104/pp.16.01401. http://www.plantphysiol.org/content/172/4/2204

  • Arend, Daniel; Lange, Matthias; Pape, Jean-Michel; Weigelt-Fischer, Kathleen; Arana-Ceballos, Fernando; Mücke, Ingo; Klukas, Christian; Altmann, Thomas; Scholz, Uwe; Junker, Astrid; Mucke, Ingo (2016)

    Quantitative monitoring of Arabidopsis thaliana growth and development using high-throughput plant phenotyping. In: Scientific Data, S. 160055. DOI: 10.1038/sdata.2016.55. https://www.nature.com/articles/sdata201655

  • Cai, Jinhai; Okamoto, Mamoru; Atieno, Judith; Sutton, Tim; Li, Yongle; Miklavcic, Stanley J. (2016)

    Quantifying the Onset and Progression of Plant Senescence by Color Image Analysis for High Throughput Applications. In: PLoS ONE, S. e0157102. DOI: 10.1371/journal.pone.0157102. http://dx.plos.org/10.1371/journal.pone.0157102

2015

  • Ganguly, Diep; Crisp, Peter; Harter, Klaus; Pogson, Barry J.; Albrecht-Borth, Verónica; Albrecht-Borth, Ver�nica (2015)

    Genetic suppression of plant development and chloroplast biogenesis via the Snowy Cotyledon 3 and Phytochrome B pathways. In: Functional Plant Biology, S. 676. DOI: 10.1071/FP15026. http://www.publish.csiro.au/?paper=FP15026

  • Muscolo, A.; Junker, A.; Klukas, C.; Weigelt-Fischer, K.; Riewe, D.; Altmann, T. (2015)

    Phenotypic and metabolic responses to drought and salinity of four contrasting lentil accessions. In: Journal of Experimental Botany, DOI: 10.1093/jxb/erv208. http://jxb.oxfordjournals.org/lookup/doi/10.1093/jxb/erv208

  • Neilson, E. H.; Edwards, A. M.; Blomstedt, C. K.; Berger, B.; Moller, B. L.; Gleadow, R. M. (2015)

    Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time. In: Journal of Experimental Botany, DOI: 10.1093/jxb/eru526. http://jxb.oxfordjournals.org/lookup/doi/10.1093/jxb/eru526

2014

  • Chen, Dijun; Neumann, Kerstin; Friedel, Swetlana; Kilian, Benjamin; Chen, Ming; Altmann, Thomas; Klukas, Christian (2014)

    Dissecting the Phenotypic Components of Crop Plant Growth and Drought Responses Based on High-Throughput Image Analysis. In: The Plant Cell Online, S. 4636–4655. DOI: 10.1105/tpc.114.129601. http://www.plantcell.org/lookup/doi/10.1105/tpc.114.129601

  • Hairmansis, Aris; Berger, Bettina; Tester, Mark; Roy, Stuart John (2014)

    Image-based phenotyping for non-destructive screening of different salinity tolerance traits in rice. In: Rice, S. 16. http://www.biomedcentral.com/content/pdf/s12284-014-0016-3.pdf

  • Harshavardhan, Vokkaliga Thammegowda; van Son; Seiler, Christiane; Junker, Astrid; Weigelt-Fischer, Kathleen; Klukas, Christian; Altmann, Thomas; Sreenivasulu, Nese; Bäumlein, Helmut; Kuhlmann, Markus; Zhang, Jin-Song (2014)

    AtRD22 and AtUSPL1, Members of the Plant-Specific BURP Domain Family Involved in Arabidopsis thaliana Drought Tolerance. In: PLoS ONE, S. e110065. DOI: 10.1371/journal.pone.0110065. http://dx.plos.org/10.1371/journal.pone.0110065

  • Petrozza, Angelo; Santaniello, Antonietta; Summerer, Stephan; Di Tommaso, Gianluca; Di Tommaso, Donata; Paparelli, Eleonora; Piaggesi, Alberto; Perata, Pierdomenico; Cellini, Francesco (2014)

    Physiological responses to Megafol® treatments in tomato plants under drought stress: A phenomic and molecular approach. In: Scientia Horticulturae, S. 185–192. DOI: 10.1016/j.scienta.2014.05.023. http://linkinghub.elsevier.com/retrieve/pii/S0304423814002891

2013

  • Albrecht-Borth, Verónica; Kauss, Dominika; Fan, Dayong; Hu, Yuanyuan; Collinge, Derek; Marri, Shashikanth; Liebers, Monique; Apel, Klaus; Pfannschmidt, Thomas; Chow, Wah S.; Pogson, Barry J. (2013)

    A novel proteinase, SNOWY COTYLEDON4, is required for photosynthetic acclimation to higher light intensities in Arabidopsis. In: PLANT PHYSIOLOGY, S. 732–745. DOI: 10.1104/pp.113.216036. http://www.plantphysiol.org/content/early/2013/08/12/pp.113.216036.abstract

  • Cazzonelli, Christopher I.; Vanstraelen, Marleen; Simon, Sibu; Yin, Kuide; Carron-Arthur, Ashley; Nisar, Nazia; Tarle, Gauri; Cuttriss, Abby J.; Searle, Iain R.; Benkova, Eva; Mathesius, Ulrike; Masle, Josette; Friml, Jiří; Pogson, Barry J.; Muday, Gloria (2013)

    Role of the Arabidopsis PIN6 Auxin Transporter in Auxin Homeostasis and Auxin-Mediated Development. In: PLoS ONE, S. e70069. DOI: 10.1371/journal.pone.0070069. http://dx.plos.org/10.1371/journal.pone.0070069

  • Hayes, Julie E.; Pallotta, Margaret; Baumann, Ute; Berger, Bettina; Langridge, Peter; Sutton, Tim (2013)

    Germanium as a tool to dissect boron toxicity effects in barley and wheat. In: Functional Plant Biology, S. 618. DOI: 10.1071/FP12329. http://www.publish.csiro.au/?paper=FP12329

2011

  • Golzarian, Mahmood R.; Frick, Ross A.; Rajendran, Karthika; Berger, Bettina; Roy, Stuart; Tester, Mark; Lun, Desmond S. (2011)

    Accurate inference of shoot biomass from high-throughput images of cereal plants. In: Plant methods, S. 1–11. http://link.springer.com/article/10.1186/1746-4811-7-2

2010

2009

  • Rajendran, Karthika; Tester, Mark; Roy, Stuart J. (2009)

    Quantifying the three main components of salinity tolerance in cereals. In: Plant, Cell & Environment, S. 237–249. DOI: 10.1111/j.1365-3040.2008.01916.x. http://doi.wiley.com/10.1111/j.1365-3040.2008.01916.x