Automatic Image-Based Method for Quantitative Analysis of Photosynthetic Cell Cultures

  • Alzbeta Vlachynska
  • Jan Cerveny
  • Vratislav Cmiel
  • Tomas Turecek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9648)


This work deals with an automatic quantitative analysis of photosynthetic cell cultures. It uses images captured by a confocal fluorescent microscope for automatic determination the number of cells in sample containing complex 3D structure of cell clusters. Experiments were performed on the confocal microscope Leica TCS SP8 X. The cell nuclei were stained by SYBR® Green fluorescent DNA binding marker. In the first step we used combination of adaptive thresholding to found out areas where nuclei were located. Proposed segmentation steps allowed reduction of noise and artefacts. Z-axis position was obtained as a location of peak from intensity profile. Finally model of scene can be created by emplacement of spheres with adequate diameter to found 3D coordinates. Number of cells per volumetric unit were determined in structurally different culture samples of cell cultures Chenopodium rubrum (Cr) and Solanum lycopersicum (To). The results were verified by manual counting.


Automated cell counting Image segmentation Plant cell Suspension cultures 3D reconstruction Visualization 



This work was supported by the Internal Grant Agency at TBU in Zlín, project No. IGA/CebiaTech/2016/007 and by the Ministry of Education, Youth and Sports of CR within the National Sustainability Program I (NPU I), grant number LO1415 (J.C.).


  1. 1.
    Schillberg, S., Raven, N., Fischer, R., Twyman, R.M., Schiermeyer, A.: Molecular farming of pharmaceutical proteins using plant suspension cell and tissue cultures. Curr. Pharm. Des. 19(31), 5531?5542 (2013)CrossRefGoogle Scholar
  2. 2.
    Roitsch, T., Sinha, A.K.: Application of photoautotrophic suspension cultures in plant science. Photosynthetica 40(4), 481?492 (2002)CrossRefGoogle Scholar
  3. 3.
    Hampp, C., Richter, A., Osorio, S., Zellnig, G., Sinha, A.K., Jammer, A., et al.: Establishment of a photoautotrophic cell suspension culture of arabidopsis thaliana for photosynthetic, metabolic, and signaling studies. Mol. Plant 5(2), 524?527 (2012)CrossRefGoogle Scholar
  4. 4.
    Husemann, W., Barz, W.: Photoautotrophic growth and photosynthesis in cell suspension cultures of Chenopodium rubrum. Physiol Plantarum 40(2), 77?81 (1977)CrossRefGoogle Scholar
  5. 5.
    Naill, M.C., Roberts, S.C.: Preparation of single cells from aggregated Taxus suspension cultures for population analysis. Biotechnol. Bioeng. 86(7), 817?826 (2004)CrossRefGoogle Scholar
  6. 6.
    de Gunst, M.C.M., Harkes, P.A.A., Val, J., van Zwet, W.R., Libbenga, K.: Modeling the growth of a batch culture of plant-cells - a corpuscular approach. Enzyme Microb. Technol. 12(1), 61?71 (1990)CrossRefGoogle Scholar
  7. 7.
    Nicoloso, F.T., Val, J., Vanderkeur, M., Vaniren, F., Kijne, J.W.: Flow-cytometric cell counting and dna estimation for the study of plant-cell population-dynamics. Plant Cell, Tissue Organ Cult. 39(3), 251?259 (1994)CrossRefGoogle Scholar
  8. 8.
    Lamboursain, L., Jolicoeur, M.: Determination of cell concentration in a plant cell suspension using a fluorescence microplate reader. Plant Cell Rep. 23(10?11), 665?672 (2005)CrossRefGoogle Scholar
  9. 9.
    Havenith, H., Raven, N., Di Fiore, S., Fischer, R., Schillberg, S.: Image-based analysis of cell-specific productivity for plant cell suspension cultures. Plant Cell, Tissue Organ Cult. 117(3), 393?399 (2014)CrossRefGoogle Scholar
  10. 10.
    Murashige, T., Skoog, F.: A revised medium for rapid growth and bio assays with tobacco tissue cultures. Physiol. Plant. 15, 473?497 (1962)CrossRefGoogle Scholar
  11. 11.
    Lin, G., Adiga, U., Olson, K., Guzowski, J.F., Barnes, C.A., Roysam, B.: A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry A 56(1), 23?36 (2003)CrossRefGoogle Scholar
  12. 12.
    Cloppet, F., Boucher, A.: Segmentation of overlapping/aggregating nuclei cells in biological images. In: 19th International Conference on Pattern Recognition, vols. 1?6, pp. 789?792 (2008)Google Scholar
  13. 13.
    Zanella, C., Campana, M., Rizzi, B., Melani, C., Sanguinetti, G., Bourgine, P., et al.: Cells segmentation from 3-D confocal images of early Zebrafish embryogenesis. IEEE Trans. Image Process. 19(3), 770?781 (2010)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Yang, Q., Parvin, B.: CHEF: convex hull of elliptic features for 3D blob detection. In: Proceedings of the 16th International Conference on Pattern Recognition, vol 2, pp. 282?285 (2002)Google Scholar
  15. 15.
    Nixon, M.S., Aguado, A.S.: Feature Extraction and Image Processing. Newnes, Oxford (2002)Google Scholar
  16. 16.
    Vlachynska, A.: Photosynthetic cell suspension cultures quantitative image data processing. MSc thesis (Czech language), Brno University of Technology, Brno, May 2015Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Alzbeta Vlachynska
    • 1
  • Jan Cerveny
    • 2
  • Vratislav Cmiel
    • 3
  • Tomas Turecek
    • 1
  1. 1.Tomas Bata University in ZlinZlinCzech Republic
  2. 2.Global Change Research Institute CASBrnoCzech Republic
  3. 3.Brno University of TechnologyBrnoCzech Republic

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