Image processing procedure for remote recording of the Gambusia sp. introduced into a water for anti-malaria

Authors

DOI:

https://doi.org/10.15587/2706-5448.2022.252297

Keywords:

image processing procedure, remote image recording, malaria control, unmanned aerial vehicle

Abstract

The object of research is the procedure for processing digital images for remote registration of Gambusia sp., introduced into water bodies to combat malaria, which threatens not only the African region, but also other latitudes of the world. One of the most problematic areas of research is the elimination of the masking effect of a biological object under conditions of interference (for example, water turbidity) that make it difficult to recognize Gambusia sp. on digital images taken from aboard light drones.

In the course of the study, approaches were used that allow dividing a digital image into segments and sub-segments, followed by determining the ratio of the colorimetric parameters of the RGB model of the bottom section. Dispersion and correlation analysis of mean values and mean square deviation values of the RGB model parameters were used. The standard deviation was considered as the degree of diversity of colorimetric parameters in the color of a biological object.

The proposed procedure made it possible to reveal a moderate negative correlation between the predominance of green and yellow-orange-red phytopigments in the dynamics of the Margalef model of phytocenosis succession in the places of introduction and habitation of Gambusia sp. This is due to the fact that the shielding of phytocenosis areas by Gambusia sp. is reflected in the nature of the relationship of the colorimetric parameters of the RGB model of the bottom area, namely, they affect the correlation between the average values of the parameters G/(R+G+B) and R/G or between the mean value and the standard deviation of the parameter G/(R+G+B). This makes it possible to use Gambusia sp. in regions affected by malaria, a wide range of light drones with remote photofixation of relatively low quality. The implementation of these possibilities will require much less material costs and a small number of personnel than underwater video filming and other known methods for studying the ichthyofauna of small water bodies in conditions of interference. It is about the registration of the results of the introduction of Gambusia sp. in such water bodies to fight malaria.

Author Biographies

Olena Vуsotska, National Aerospace University «Kharkiv Aviation Institute»

Doctor of Technical Sciences, Professor, Head of Department

Department of Radio-Electronic and Biomedical Computer-Aided Means and Technologies

Konstantin Nosov, V. N. Karazin Kharkiv National University

PhD, Associate Professor

Department of Theoretical and Applied Informatics

Igor Hnoevyi, State Biotechnological University

Doctor of Agricultural Sciences, Professor, Head of Department

Department of Applied Biology, Aquatic Bioresources and Hunting them Professor A. S. Tertyshny

Andrii Porvan, National Aerospace University «Kharkiv Aviation Institute»

PhD, Associate Professor

Department of Radio-Electronic and Biomedical Computer-Aided Means and Technologies

Lyubov Rysovana, Kharkiv National Medical University

PhD, Associate Professor

Department of Medical and Biological Physics and Medical Informatics

Alexandr Dovnar, National Aerospace University «Kharkiv Aviation Institute»

PhD, Associate Professor

Department of Radio-Electronic and Biomedical Computer-Aided Means and Technologies

Mikhail Babakov, National Aerospace University «Kharkiv Aviation Institute»

PhD, Professor

Department of Radio-Electronic and Biomedical Computer-Aided Means and Technologies

Marharyta Kalenichenko, National Aerospace University «Kharkiv Aviation Institute»

Department of Radio-Electronic and Biomedical Computer-Aided Means and Technologies

References

  1. The World Malaria report 2021 (2021). World Health Organization, 322. Available at: https://www.who.int/publications/i/item/9789240040496
  2. Ndwigah, S., Stergachis, A., Abuga, K., Mugo, H., Kibwage, I. (2018). The quality of anti-malarial medicines in Embu County, Kenya. Malaria Journal, 17 (1). doi: http://doi.org/10.1186/s12936-018-2482-3
  3. Huxley, P. J., Murray, K. A., Pawar, S., Cator, L. J. (2021). The effect of resource limitation on the temperature dependence of mosquito population fitness. Proceedings of the Royal Society B: Biological Sciences, 288 (1949). doi: http://doi.org/10.1098/rspb.2020.3217
  4. Butler, D. (2019). Promising malaria vaccine to be tested in first large field trial: The vaccine can confer up to 100 % protection and will be tested in 2,100 people on the west African island of Bioko. Nature. doi: http://doi.org/10.1038/d41586-019-01232-4
  5. Vekemans, J., Schellenberg, D., Benns, S., O’Brien, K., Alonso, P. (2021). Meeting report: WHO consultation on malaria vaccine development, Geneva, 15–16 July 2019. Vaccine, 39 (22), 2907–2916. doi: http://doi.org/10.1016/j.vaccine.2021.03.093
  6. Bilgo, E., Lovett, B., St. Leger, R. J., Sanon, A., Dabiré, R. K., Diabaté, A. (2018). Native entomopathogenic Metarhizium spp. from Burkina Faso and their virulence against the malaria vector Anopheles coluzzii and non-target insects. Parasites & Vectors, 11 (1). doi: http://doi.org/10.1186/s13071-018-2796-6
  7. Girard, M., Martin, E., Vallon, L., Raquin, V., Bellet, C., Rozier, Y. et. al. (2021). Microorganisms Associated with Mosquito Oviposition Sites: Implications for Habitat Selection and Insect Life Histories. Microorganisms, 9 (8), 1589. doi: http://doi.org/10.3390/microorganisms9081589
  8. Hou, L., Chen, S., Chen, H., Ying, G., Chen, D., Liu, J. et. al. (2019). Rapid masculinization and effects on the liver of female western mosquitofish (Gambusia affinis) by norethindrone. Chemosphere, 216, 94–102. doi: http://doi.org/10.1016/j.chemosphere.2018.10.130
  9. Huang, G.-Y., Liu, Y.-S., Liang, Y.-Q., Shi, W.-J., Yang, Y.-Y., Liu, S.-S. et. al. (2019). Endocrine disrupting effects in western mosquitofish Gambusia affinis in two rivers impacted by untreated rural domestic wastewaters. Science of The Total Environment, 683, 61–70. doi: http://doi.org/10.1016/j.scitotenv.2019.05.231
  10. Asanov, A. Y. (2021). The method’ features for assessing the number of fish in small reservoirs and watercourses using an underwater video camera. University Proceedings. Volga Region. Natural Sciences, 3, 85–97. doi: http://doi.org/10.21685/2307-9150-2021-3-8
  11. Whitehead, K., Hugenholtz, C. H., Myshak, S., Brown, O., LeClair, A., Tamminga, A. et. al. (2014). Remote sensing of the environment with small unmanned aircraft systems (UASs), part 2: scientific and commercial applications. Journal of Unmanned Vehicle Systems, 2 (3), 86–102. doi: http://doi.org/10.1139/juvs-2014-0007
  12. Groves, P. A., Alcorn, B., Wiest, M. M., Maselko, J. M., Connor, W. P. (2017). Testing unmanned aircraft systems for salmon spawning surveys. FACETS, 1 (1), 187–204. doi: http://doi.org/10.1139/facets-2016-0019
  13. Kudo, H., Koshino, Y., Eto, A., Ichimura, M., Kaeriyama, M. (2012). Cost-effective accurate estimates of adult chum salmon, Oncorhynchus keta, abundance in a Japanese river using a radio-controlled helicopter. Fisheries Research, 119-120, 94–98. doi: http://doi.org/10.1016/j.fishres.2011.12.010
  14. Groves, P. A., Alcorn, B., Wiest, M. M., Maselko, J. M., Connor, W. P. (2017). Testing unmanned aircraft systems for salmon spawning surveys. FACETS, 1 (1), 187–204. doi: http://doi.org/10.1139/facets-2016-0019
  15. Endler, J. A., Mappes, J. (2017). The current and future state of animal coloration research. Philosophical Transactions of the Royal Society B: Biological Sciences, 372 (1724). doi: http://doi.org/10.1098/rstb.2016.0352
  16. Panayotova, I. N., Horth, L. (2018). Modeling the impact of climate change on a rare color morph in fish. Ecological Modelling, 387, 10–16. doi: http://doi.org/10.1016/j.ecolmodel.2018.08.008
  17. Vissio, P. G., Darias, M. J., Di Yorio, M. P., Pérez Sirkin, D. I., Delgadin, T. H. (2021). Fish skin pigmentation in aquaculture: The influence of rearing conditions and its neuroendocrine regulation. General and Comparative Endocrinology, 301, 113662. doi: http://doi.org/10.1016/j.ygcen.2020.113662
  18. Valkonen, J. K., Vakkila, A., Pesari, S., Tuominen, L., Mappes, J. (2020). Protective coloration of European vipers throughout the predation sequence. Animal Behaviour, 164, 99–104. doi: http://doi.org/10.1016/j.anbehav.2020.04.005
  19. Guillermo-Ferreira, R., Bispo, P. C., Appel, E., Kovalev, A., Gorb, S. N. (2019). Structural coloration predicts the outcome of male contests in the Amazonian damselfly Chalcopteryx scintillans (Odonata: Polythoridae). Arthropod Structure & Development, 53, 100884. doi: http://doi.org/10.1016/j.asd.2019.100884
  20. Duarte, R. C., Flores, A. A. V., Stevens, M. (2017). Camouflage through colour change: mechanisms, adaptive value and ecological significance. Philosophical Transactions of the Royal Society B: Biological Sciences, 372 (1724). doi: http://doi.org/10.1098/rstb.2016.0342
  21. Green, J. B. A. (2021). Computational biology: Turing’s lessons in simplicity. Biophysical Journal, 120 (19), 4139–4141. doi: http://doi.org/10.1016/j.bpj.2021.08.041
  22. Salis, P., Lorin, T., Laudet, V., Frédérich, B. (2019). Magic Traits in Magic Fish: Understanding Color Pattern Evolution Using Reef Fish. Trends in Genetics, 35 (4), 265–278. doi: http://doi.org/10.1016/j.tig.2019.01.006
  23. Turing, А. М. (1952). The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 237 (641), 37–72. doi: http://doi.org/10.1098/rstb.1952.0012
  24. Balym, Y., Vуsotska, O., Pecherska, A., Bespalov, Y. (2017). Mathematical modeling of systemic colorometric parameters unmasking wild waterfowl. Eastern-European Journal of Enterprise Technologies, 5 (2 (89)), 12–18. doi: http://doi.org/10.15587/1729-4061.2017.110107
  25. Zholtkevych, G. N., Bespalov, G. Y., Nosov, K. V., Abhishek, M. (2013). Discrete Modeling of Dynamics of Zooplankton Community at the Different Stages of an Antropogeneous Eutrophication. Acta Biotheoretica, 61 (4), 449–465. doi: http://doi.org/10.1007/s10441-013-9184-6
  26. Bespalov, Y., Kabalyants, P., Zuev, S. (2021). Relationships of diversity and evenness in adaptation strategies of the effect of protective coloration of animals. doi: http://doi.org/10.1101/2021.05.06.441914
  27. Bespalov, Y., Nosov, K., Levchenko, O., Grigoriev, O., Hnoievyi, I., Kabalyants, P. (2019). Mathematical modeling of the protective coloration of animals with usage of parameters of diversity and evenness. doi: http://doi.org/10.1101/822999
  28. Bespalov, Y. G., Nosov, K. V., Kabalyants, P. S. (2017). DIscrete Dynamical Model of Mechanisms Determining the Relations of Biodiversity and Stability at Different Levels of Organization of Living Matter. doi: http://doi.org/10.1101/161687
  29. Margalef, R. (1967). Concepts relative to the organization of plankton. Oceanography and Marine Biology, 5, 257–289.
  30. Grigoriev, A. Ya., Levchenko, A. V., Ryabovol, A., Vysotska, O. V., Kalashnikova, V. I. (2021). Distance reading fishes in the water area by colorimetric parameters related to productivity and diversity of phytobentos. Information systems and technologies in medicine (ISM–2021), 57.

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Published

2022-01-17

How to Cite

Vуsotska O., Nosov, K., Hnoevyi, I., Porvan, A., Rysovana, L., Dovnar, A., Babakov, M., & Kalenichenko, M. (2022). Image processing procedure for remote recording of the Gambusia sp. introduced into a water for anti-malaria. Technology Audit and Production Reserves, 1(2(63), 14–18. https://doi.org/10.15587/2706-5448.2022.252297

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Section

Systems and Control Processes: Original Research