Mathematical modeling of the colorimetric parameters for remote control over the state of natural bioplato

Authors

DOI:

https://doi.org/10.15587/1729-4061.2017.108415

Keywords:

bioplato, bioproduction process, waterfowls, relation graph, colorimetric parameters, remote control, trajectory of the system

Abstract

An approach to the remote determination of the character of bioproduction processes in aquatic phytocenoses is proposed. The investigated plant communities can be used as natural bioplato for the elimination of biosafety threats to water consumption. The relevance of these studies is determined by the increased need for expanding the arsenal of methods for remote diagnosis of the states of natural systems that are important for biosafety provision. In particular – to ensure biosafety when using natural feed resources by waterfowls, which are a potential reservoir of bird flu.

The similarity in the dynamics of the colorimetric parameters of phytocenoses and the Margalef’s succession model makes it possible to implement a new approach to the generation of productive working hypotheses for the development of remote methods for determining the state of bioproduction processes in natural bioplato. The proposed approach is based on the use of the class of mathematical models, which is called the discrete models of dynamic systems.

Based on the structure of the correlations between the colorimetric components of space photographs of the plavni in the mouth of the river Danube, a description of the structure of the intercomponent and intracomponent relations of the massifs of semi-submerged higher aquatic plants has been obtained. The resulting structure of intercomponent relations allowed us to construct idealized trajectories reflecting the dynamic changes of the system. A unique constant inverse relationship between the parameter reflecting the amount of green chlorophyll pigment affecting the level of photosynthetic production and the parameter reflecting the amount of orange-red pigments in each of the possible matrices of the ratios of colorimetric parameters has been revealed. As a result of analysis of the dynamic aspects of the RGB model, the structure of the system color parameter is shown, which is the mean square deviation of the spread in the degree of alignment of parameter values reflecting the amount of green and orange-red pigments.

As a result of analysis of the systemic colorimetric parameter of photographs of the section of the Danube plavni during various periods of the vegetative season, it is shown that it is advisable to use it as a marker of the risk of secondary water pollution, which can be used for remote determination of the state of bioproduction processes in natural bioplato.

Author Biographies

Yuriі Balym, Kharkiv State Zooveterinary Academy Academichna str., 1, Malaya Danylivka, Dergachi district, Kharkiv region, Ukraine, 62341

Doctor of Veterinary Science, Professor

Department of Reproductology

Marine Georgiyants, Kharkiv Medical Academy of Postgraduate Education Amosova str., 58, Kharkіv, Ukraine, 61176

MD, Professor

Department of Pediatrics Anesthesiology and Intensive Therapy

Olena Vуsotska, Kharkiv National University of Radio Electronics Nauky ave., 14, Kharkiv, Ukraine, 61166

Doctor of Technical Sciences, Professor

Department of Biomedical Engineering

Anna Pecherska, Kharkiv National University of Radio Electronics Nauky ave., 14, Kharkiv, Ukraine, 61166

PhD

Department of Biomedical Engineering

Andrei Porvan, Kharkiv National University of Radio Electronics Nauky ave., 14, Kharkiv, Ukraine, 61166

PhD

Department of Biomedical Engineering

References

  1. Kozlova, T. V., Kozlov, A. I., Shalak, M. V., Glushakov, O. A. (2014). Ispol'zovanie muskusnoy utki v integrirovannom rybovodstve na meliorativnom vodoeme Pripyatskogo Poles'ya. Rybovodstvo i rybnoe hozyaystvo, 1, 40–45.
  2. Wikramaratna, P. S., Pybus, O. G., Gupta, S. (2014). Contact between bird species of different lifespans can promote the emergence of highly pathogenic avian influenza strains. Proceedings of the National Academy of Sciences, 111 (29), 10767–10772. doi: 10.1073/pnas.1401849111
  3. Titova, T. A. (2013). Effektivnost' primeneniya infil'tratsionnyh bioplato pri ochistke kommunal'nyh stochnyh vod. Vestnik Rossiyskogo gosudarstvennogo agrarnogo zaochnogo universiteta, 15 (20), 67–70.
  4. Matyushenko, V. A. (2015). Otsenka vegetatsionnogo indeksa geosistem rechitskogo rayona. Tvorchestvo yunyh – shag v uspeshnoe budushchee. Tomsk, 528–530.
  5. Cherepanov, A. S. (2011). Vegetatsionnye indeksy. Geomatika, 2, 98–102.
  6. Antipov, T. I., Pavlova, A. I., Kalichkin, V. A. (2012). Primery avtomatizirovannyh metodov analiza geoizobrazheniy dlya agroekologicheskoy otsenki zemel'. Izvestiya vysshih uchebnyh zavedeniy. Geodeziya i aerofotos'emka, 2/1, 40–44.
  7. Hohm, T., Zitzler, E., Simon, R. (2010). A Dynamic Model for Stem Cell Homeostasis and Patterning in Arabidopsis Meristems. PLoS ONE, 5 (2), e9189. doi: 10.1371/journal.pone.0009189
  8. Lee, Y.-S., Tong, L.-I. (2011). Forecasting time series using a methodology based on autoregressive integrated moving average and genetic programming. Knowledge-Based Systems, 24 (1), 66–72. doi: 10.1016/j.knosys.2010.07.006
  9. Anderson, T. W. (1994). The statistical analysis of time series. John Wiley & Sons, 704. doi: 10.1002/9781118186428
  10. Dupont, F., Padala, C., Anning, H. et. al. (2011). A NEMO based modelling system for the Great Lakes. 15th Workshop on Physical Processes in Natural Waters. Burlington, 46–52.
  11. Gal, G., Hipsey, M. R., Parparov, A., Wagner, U., Makler, V., Zohary, T. (2009). Implementation of ecological modeling as an effective management and investigation tool: Lake Kinneret as a case study. Ecological Modelling, 220 (13-14), 1697–1718. doi: 10.1016/j.ecolmodel.2009.04.010
  12. Hernandez-Clemente, R., Navarro-Cerrillo, R. M., Zarco-Tejada, P. J. (2012). Carotenoid content estimation in a heterogeneous conifer forest using narrow-band indices and PROSPECT+DART simulations. Remote Sensing of Environment, 127, 298–315. doi: 10.1016/j.rse.2012.09.014
  13. Feret, J.-B., François, C., Asner, G. P., Gitelson, A. A., Martin, R. E., Bidel, L. P. R. et. al. (2008). PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments. Remote Sensing of Environment, 112 (6), 3030–3043. doi: 10.1016/j.rse.2008.02.012
  14. Chavez, R. O., Clevers, J. G. P. W., Herold, M., Ortiz, M., Acevedo, E. (2013). Modelling the spectral response of the desert tree Prosopis tamarugo to water stress. International Journal of Applied Earth Observation and Geoinformation, 21, 53–65. doi: 10.1016/j.jag.2012.08.013
  15. Ruiz-Verdu, A., Simis, S. G. H., de Hoyos, C., Gons, H. J., Pena-Martinez, R. (2008). An evaluation of algorithms for the remote sensing of cyanobacterial biomass. Remote Sensing of Environment, 112 (11), 3996–4008. doi: 10.1016/j.rse.2007.11.019
  16. 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: 10.1007/s10441-013-9184-6
  17. Zholtkevych, G. N., Nosov, K. V., Bespalov, Y. G. et. al. (2016). Descriptive models of system dynamics. 12th International Conference on ICT in Education, Research and Industrial Applications, ICTERI 2016. Kyiv, 57–72.
  18. Vysotska, O., Bespalov, Y., Rak, L. et. al. (2016). Modeling the dynamics of the cardiovascular system parameters coherence at different stages of the adaptation syndrome. Bulletin of NTU “KhPI”. Series: Mechanical-technological systems and complexes, 4 (1176), 79–84.
  19. Vysotskaya, E. V., Zholtkevych, G. N., Klochko, T. A. et. al. (2016). Unmasking the soil cover’s disruption by modeling the dynamics of ground vegetation parameters. Visnyk Natsionalnoho Tekhnichnoho Universytetu Ukrainy «KPI». Seriya: Radiotekhnika. Radioaparatobuduvannia, 64, 101–109.
  20. Landsat collections. Provding a stable environmental record. Available at: https://landsat.usgs.gov/
  21. Vysotska, O. V., Bespalov, Y. G., Pecherska, A. I., Parvadov, D. A. (2016). Using of Margalef succession model in remote detection technologies for indications of human impact on vegetation cover. Radioelektronni i kompiuterni systemy, 2 (76), 15–19.

Downloads

Published

2017-08-22

How to Cite

Balym, Y., Georgiyants, M., Vуsotska O., Pecherska, A., & Porvan, A. (2017). Mathematical modeling of the colorimetric parameters for remote control over the state of natural bioplato. Eastern-European Journal of Enterprise Technologies, 4(10 (88), 29–36. https://doi.org/10.15587/1729-4061.2017.108415

Issue

Vol. 4 No. 10 (88) (2017): Ecology

Section

Ecology

License

Copyright (c) 2017 Yuriі Balym, Marine Georgiyants, Olena Vуsotska, Anna Pecherska, Andrei Porvan

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.