Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Finite Automata Models in Agro-ecosystem and Plant Protection

Print
PDF
International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 119 - Number 18
Year of Publication: 2015
Authors:
Svetla Maneva
Krassimir Manev
10.5120/21164-4223

Svetla Maneva and Krassimir Manev. Article: Finite Automata Models in Agro-ecosystem and Plant Protection. International Journal of Computer Applications 119(18):1-6, June 2015. Full text available. BibTeX

@article{key:article,
	author = {Svetla Maneva and Krassimir Manev},
	title = {Article: Finite Automata Models in Agro-ecosystem and Plant Protection},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {119},
	number = {18},
	pages = {1-6},
	month = {June},
	note = {Full text available}
}

Abstract

Diseases in plants cause major production and economic losses in agricultural industry worldwide. Monitoring of health and detection of diseases in plants and trees is critical for sustainable agriculture. In this paper an approach for building software systems for plant disease control that perform real time prediction of the outbreak and the development of the disease is proposed. Mathematical base of the approach are the finite automata. A method for transforming a given biological model of the disease to a finite automaton is developed. The software system has just to interpret the obtained automaton. The applicability of the developed approach is demonstrated on an example of a software system for prediction of development of Phitophthora infestans on potatoes and tomatoes. Predicting the breakout of the disease is very important for sustainable agriculture of Bulgaria because on favorable conditions the pathogen could destroy nearly 100% of the yield of potatoes and tomatoes.

References

  • A. Kerr and P. Keane. Plant Pathogens and Plant Diseases, chapter Prediction of disease outbreak, pages 299–314. Rockvale Publications, 1997.
  • A. V. Aho, R. Sathi, and J. D. Ulman. Compilers: Principles, Techniques, and Tools. Addison Wesley, 1986.
  • E. D. De Wolf, L. V. Madden, and P. E. Lipps. Risk assessment models for wheat fusarium head blight (abstract). Phytopathology, 90:S19, 2000.
  • E. M. Del Ponte, C. V. Godoy, M. G. Canteri, E. M. Reis, and X. B. Yang. Models and applications for risk assessment and prediction of asian soybean rust epidemics. Fitopatologia Brasileira, 31:533–544, 2006.
  • L. V. Madden. Botanical epidemiology: Some key advances and its continuing role in decease management. European Journal of Plant Pathology, 115:3–23, 2003.
  • P. Mihaylova. Opportunities to use some systems to predict the appearance of mildew on potatoes (Phitophtora investa de bary) in Bulgaria (in Bulgarian). Plant Sciences, 11:56–61, 1965.
  • P. Mihaylova. Relative rate of infection in mildew (in Bulgarian). Plant Sciences, 1:116–124, 1978.
  • P. Popov and P. Mihaylova. Guide for Prerdiction and Signaling Crops Pests (in Bulgarian). Zemizdat, Sofia, 1961.
  • P. Popov, P. Mihaylova, G. Gospodinova, and T. Zaharieva. Guide for Prerdiction and Signaling Crops Pests (in Bulgarian). Zemizdat, Sofia, 1975.
  • S. Sankarana, A. Mishraa, R. Ehsania, and C. Davis. A review of advanced techniques for detecting plant diseases. Computers and Electronics in Agriculture, 72(1):1–13, 2010.
  • P. W. Steiner. Predicting apple blossom infections by erwinia amylovora using the maryblyt model. Acta Horticulturae, 273:139–148, 1990.
  • J. Yuen. Bayesian approaches to plant disease forecasting. Plant Health Progress (online), doi: 10. 1094/PHP-2003-1113- 06-RV, 2003.