Applications And Potentials Of Artificial Neural Networks In Plant Tissue Culture

  • V.S.S. Prasad
  • S. Dutta Gupta
Part of the Focus on Biotechnology book series (FOBI, volume 6)


Neural Network Artificial Neural Network Somatic Embryo Hide Layer Hide Node 
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  1. [1]
    Nazmul Karim, M.; Yoshida, T.; Rivera, S. L.; Saucedo, V. M.; Eikens, B. and Oh, G. S. (1997) global and local neural network models in biotechnology: Application to different cultivation processes. J. Ferment. Bioengg. 83: 1-11.CrossRefGoogle Scholar
  2. [2]
    Hashimota, Y. (1997) Applications of artificial neural networks and genetic algorithms to agricultural systems. Comput. Electro. Agri. 18: 71-72.CrossRefGoogle Scholar
  3. [3]
    Patnaik, P. R. (1999) Applications of neural networks to recovery of biological products. Biotechnol. Adv. 17: 477-488.CrossRefGoogle Scholar
  4. [4]
    Hudson, D. L. and Cohen, M. E. (Eds.) (2000) Neural networks and artificial intelligence for biomedical engineering. The Institute of Electric and Electronics Engineers Press Inc., New York.Google Scholar
  5. [5]
    Haykin, S. (1994) Neural networks: A comprehensive foundation. Macmillan College Publishing Co., New York.Google Scholar
  6. [6]
    Tani, A.; Murase, H.; Kiyota, M. and Honami, N (1992) Growth simulation of alfalfa cuttings in vitro by kalman filter neural network. International Symposium on Transplant Production Systems. Acta. Hort. 319.Google Scholar
  7. [7]
    Uozumia, N; Yoshinoa, T.; Shiotanib, S.; Sueharaa, K. I.; Araib, F.; Fukudab, T. and Kobayashi, T. (1993) Application of image analysis with neural network for plant somatic embryo culture. J. Ferment. Bioengg. 76: 505-509.CrossRefGoogle Scholar
  8. [8]
    Albiol, J.; Campmajo, C.; Casas, C. and Poch, M. (1995) Biomass estimation in plant cell cultures: A neural network approach. Biotechnol. Prog. 11: 8-92.Google Scholar
  9. [9]
    Suroso; Murase, H.; Tani, A.; Hoami, N.; Takigawa, H. and Nishiura, Y. (1996) Inverse technique for analysis of convective heat transfer over the surface of plant culture vessel. Trans. ASAE. 39: 2277-2282.CrossRefGoogle Scholar
  10. [10]
    Honda, H.; Takikawa, N.; Noguchi, H.; Hanai, T. and Kobayashi, T. (1997) Image analysis associated with fuzzy neural network and estimation of shoot length of regenerated rice callus. J. Ferment. Bioeng.84: 342-347.CrossRefGoogle Scholar
  11. [11]
    Zhang, C.; Timmis, R. and Shou Hu, W. (1999) A neural network based pattern recognition system for somatic embryos of Douglas fir. Plant Cell Tissue Org. Cult. 56: 25-35.Google Scholar
  12. [12]
    Mahendra; Prasad, V. S. S. and Dutta Gupta, S. (2004) Trichromatic sorting of in vitroregenerated plants of gladiolus using adaptive resonance theory. Curr. Sci. 87: 348-353.Google Scholar
  13. [13]
    Albiol, J.; Robuste, J.; Casas, C. and Poch, M. (1993) Biomass estimation in plant cell cultures using an extended kalman filter. Biotechnol. Prog. 9: 174-178.CrossRefGoogle Scholar
  14. [14]
    Morohoshi, N. and Komamine, A. (Eds.) (2001) Molecular Breeding of Woody Plants. Elsevier Sci. B. V., The Netherlands.Google Scholar
  15. [15]
    Honda, H.; Ito, T.;Yamada, J;Hanai, T.;Matsuoka, M. and Kobayashi, T. (1999) Selection of embryogenic sugarcane callus by image analysis. J. Biosci. Bioeng. 87: 700-702.Google Scholar
  16. [16]
    Carpenter, G. A. and Grossberg, S. (1987) ART2: Self organisation of stable category recognition codes for analogue input patterns. Appl. Optics. 26: 4919-4930.CrossRefGoogle Scholar

Copyright information

© Springer 2008

Authors and Affiliations

  • V.S.S. Prasad
    • 1
  • S. Dutta Gupta
    • 1
  1. 1.Department of Agricultural and Food EngineeringIndian Institute of TechnologyIndia

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