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Ribogospod. nauka Ukr., 2019; 4(50): 37-57
DOI: https://doi.org/10.15407/fsu2019.04.037 
УДК 004:591.5:612:616-006

Creation of fish databases for electronic interactive map: tables and keys

O. Klyuchko, This email address is being protected from spambots. You need JavaScript enabled to view it. , Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology of the National Academy of Sciences of Ukraine, Kyiv
L. Buchatsky, This email address is being protected from spambots. You need JavaScript enabled to view it. , Institute of Fisheries NAAS of Ukraine, Kyiv
Yu. Rud, This email address is being protected from spambots. You need JavaScript enabled to view it. , Institute of Fisheries NAAS of Ukraine, Kyiv
O. Melezhyk, This email address is being protected from spambots. You need JavaScript enabled to view it. , Open International University of Human Development "Ukraine", Kyiv

Purpose. Purpose of the work is to create fish databases using rainbow trout data and basing on new methods of theoretical analysis of fish data and their ordering in hierarchical structures with elements represented as relation tables linked through a system with primary keys with specific codes.

Methodology. The methods of object-oriented system analysis, ER-diagram design, and the methods of computer databases construction were used in process of present work.

Findings. Some well-known fish databases (seafood, aquaculture samples) were reviewed and some of their peculiarities are analyzed from the point of view of professional construction of relational databases within modern electronic information systems. The ways of the construction of such databases for domestic use in connection with the Internet were proposed. A number of algorithm stages for fish database design was described on the example of the information on rainbow trout and locations of its occurrence (catches) in Ukraine; ER-diagram, logical diagram of such database with its elements that can be presented in tables are suggested as well. Such tables should be unmistakably interconnected through the key system, and this procedure is described in detail in the article, as well as the creation of specific key codes, their formation and use to form links between the tables. The implementation of described works can be considered as one of the first stages in the development of interactive map with information of the fish species distribution (and locations of their catches) in Ukraine.

Originality. Such important modern project as an interactive map with the information on the distribution of fish species (and locations of their catches) based on modern information and computer technologies using biological databases has not been implemented yet in Ukraine. The work described in this article is the first step in creating of such a map that will facilitate further intensive introduction of modern information technologies and the development of domestic fishery industry.

Practical value. Rainbow trout is an important object for fishery industry of the country; and development of interactive electronic map with the information on the spread of the rainbow trout and other fish species (and places of their catches) in Ukraine is an important step for the transformation of fishery industry in our country to the contemporary level of the world technologies and for the provision of food safety. Using of contemporary computer technologies suggested in the this article, would make this branch more effective in Ukraine and in the whole world.

Keywords: fish, fishery economy, trout, databases, electronic information systems object-oriented system analysis, key, primary key.

REFERENCE

  1. Buchatsky, L. P., Zaloilo, O. V., Rud, Yu. P., & Zaloilo, I. A. (2018). Contemporary methods of biotechnology in fishery. Kyiv: DIA (In Ukrainian).
  2. Klyuchko, O. М., Buchatsky, L. P., & Melezhyk, O. V. (2019). Biological databases construction using object-oriented system analysis. Biotechnol. Acta, 12 (3), 5-22. https://doi.org/10.15407/biotech12.03.005 
  3. Klyuchko, O. М., Buchatsky, L. P., & Melezhyk, O. V. (2019). Fish information databases construction: data preparation and object-oriented system analysis. Fishery Science of Ukraine, 49 (3), 32-47. https://doi.org/10.15407/fsu2019.03.032 
  4. Klyuchko, O. М., & Klyuchko, Z. F. (2018). Electronic databases for Arthropods: methods and applications. Biotechnol. Acta, 11 (4), 28-49. https://doi.org/10.15407/biotech11.04.028.
  5. Klyuchko, O. М., & Klyuchko, Z. F. (2018). Electronic information systems for monitoring of populations and migrations of insects. Biotechnol. Acta, 11 (5), 5-25. https://doi.org/10.15407/biotech11.05.005.
  6. Young, M., Isaak, D., McKelvey, K., Wilcox, T., Pilgrim, K., Carim, K., Campbell, M., Corsi, M., Horan, D., Nagel, D., & Schwartz, M. A Map and Database of Westslope Cutthroat Trout Hybridization Throughout Idaho and Montana Streams. fs.fed.us. Retrieved from https://www.fs.fed.us/rm/boise/AWAE/projects/GIMP/downloads/17_HybridizationPoster_IDAFS.pdf.
  7. Inland Cutthroat Trout Protocol (ICP) Web-mapping Application: Native Cutthroat Trout Data Compilation and Internet Database Development. sciencebase.gov. Retrieved from https://www.sciencebase.gov/catalog/item/56e9a0b0e4b0f59b85d819e3
  8. Fischdatenbank. baw.at. Retrieved from http://www.baw.at/wasser-fische-IGF/Fischdatenbank.html.
  9. Valdez-Moreno, M., Ivanova, V., Elías-Gutiérrez, M., Pedersen, L., Bessonov, K., & Hebert, N. (2019). Using eDNA to biomonitor the fish community in a tropical oligotrophic lake. PloS One, 14 (4), e0215505. doi: 10.1371/journal.pone.0215505.
  10. Bi, H., Zhong, C., Shao, M., Wang, C., Yi, J., Qiao, L., & Zhang, J. (2019). Differentiation and Authentication of Fishes at Species Level Through Analysis of Fish Skin by MALDI TOF MS. Rapid Commun. Mass. Spectrom., 33 (16), 1336-1343. doi: 10.1002/rcm.8474.
  11. User Reference for Fisheries Improvement ProjectsDatabase (FIP-DB) and Query Viewer. ru.scribd.com. Retrieved from https://ru.scribd.com/document/385739269/Readme-File-for-FIP-DB#download.
  12. Froese, R., & Pauli, D. (2000). FishBase 2000: Concepts, designs and data sources. Los Banos, Philippines: ICLARM.
  13. Moreau, J., & Costa-Pierce, B. (1997). Introduction and present status of exotic carp in Africa. Aquacult. Res., 28, 717-732. https://doi.org/10.1111/j.1365-2109.1997.tb01094.x 
  14. FAO. (2016). The State of World Fisheries and Aquaculture 2016. Contributing to food security and nutrition for all. Rome. fao.org. Retrieved from http://www.fao.org/3/a-i5555e.pdf.
  15. Roessig, J. M., Woodley, Ch. M., Cech, J. J., & Hansen L. J. (2004). Effects of Global Climate Change on Marine and Estuarine Fishes and Fisheries. Fish Biology and Fisheries, 14, 251-275. https://doi.org/10.1007/s11160-004-6749-0 
  16. A Global Information System on Fishes. fishbase.se. Retrieved from https://www.fishbase.se/home.htm.
  17. Arnot, J. A., Mackay, D., Parkerton, T. F., & Bonnell, M. (2008). A database of fish biotransformation rates for organic chemicals. Environmental Toxicology and Chemistry, 27 (11), 2263-2270. setac.onlinelibrary.wiley.com. Retrieved from https://setac.onlinelibrary.wiley.com /doi/full/10.1897/08-058.1. doi: 10.1897/08-058.1.
  18. Tedesco, P. A., Beauchard, О., Bigorne, R., Blanchet, S., Buisson, L., Conti, L., Cornu, J.-F., Dias, M. S., , Grenouillet, G., Hugueny, B., Jézéquel, C., Leprieur, F., Brosse, S., & Oberdorff, T. (2017). A global database on freshwater fish species occurrence in drainage basins. Sci. Data, 4, 170141. doi: 10.1038/sdata.2017.141.
  19. Van der Laan, R., Eschmeyer, W. N., & Fricke, R. (2014). Family-group names of Recent fishes. Zootaxa Monograph., 3882 (1), 1-230. doi:10.11646/zootaxa.3882.1.1.
  20. Fricke, R., Eschmeyer, W. N., & R. van der Laan. Eschmeyer’s catalog of fishes: genera, species. researcharchive.calacademy.org. Retrieved from http://researcharchive.calacademy.org/research/ichthyology/catalog.
  21. Zeldis, D., & Prescott, S. (2000). Fish disease diagnosis program – Problems and some solutions. Aquacultural Engineering, 23 (1–3), 3-11. https://doi.org/10.1016/S0144-8609(00)00047-9 
  22. Frimpong, E. A., & Paul, L. Welcome to the FishTraits Database. fishtraits.info. Retrieved from http://www.fishtraits.info.
  23. Di Génova, A. D., Aravena, A., Zapata, L., González, M., Maass, A., & Iturra, L. (2011). SalmonDB: a bioinformatics resource for Salmo salar and Oncorhynchus mykiss. Database (Oxford). ncbi.nlm.nih.gov. doi: 10.1093/database/bar050. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3225076.
  24. Klyuchko, O. M. (2008). Information and computer technologies in biology and medicine. Kyiv: Nat. Acad. Scienc. Ukraine-druk. (In Ukrainian).
  25. Maistrenko, M. I., Rud, Yu. P., & Buchatsky, L. P. (2014). Accumulation of IPNV on the culture of fish cells. Animal Biology, 16 (4), 93-99 (In Ukrainian). https://doi.org/10.2478/aopf-2014-0012 
  26. Matvienko, N. M., & Buchatsky, L. P. (2014). The use of immunomodulating preparations in fish farming. Modern problems of theoretical and practical ichthyology. Mizhnarodna nauk.-praktych. konf. Kharkiv, 33-35 (In Ukrainian).
  27. Gavrilova, I. P., Maistrenko, M. I., Rumar, V. I., Buchatsky, L. P., & Rud, Yu. P. (2014). New hosts of the third-type of carp herpes virus (CyHV-3). Scientific notes of the Ternopil Ped. University. Series Biology, 58 (1), 16-20 (In Ukrainian).
  28. Maistrenko, M. I., & Buchatsky, L. P. (2014). Biology of Herpesvirus Fish. Problems of ecological and medical genetics and clinical immunology, 3 (123), 19-35 (In Ukrainian).
  29. Rud, Yu. P., Maistrenko, M. I., Bezusy, O. L., & Buchatsky, L. P. (2014). Experimental infection of long-winded cancer (Pontastacus leptodactylus) with virus of infectious pancreatic necrosis. Bulletin of Biology and Medicine, 4, 1 (113), 70-74 (In Ukrainian).
  30. Matvienko, N., Rud, Yu., & Buchatsky, L. (2014). Replication of infectious pancreatic necrosis virus in different cell lines and organism of rainbow trout (Oncorhynchus mykiss) fingerlings. Arch. Pol. Fish., 22, 127-133.
  31. Matvienko, N. M., & Buchatsky, L. P. (2014). Study of reproduction of hemorrhagic septicemia trout virus. Bulletin of Problems of Biology and Medicine, 2 (3), 118-121 (In Russian).
  32. Matvienko, N. M., Buchatsky, L. P., & Deriabin, O. M. (2013). Application of a reverse transcriptase polymerase chain reaction for the detection and identification of the virus of infectious pancreatic necrosis of rainbow trout (Oncorhynchus mykiss). Microbiology and biotechnology, 4 (24), 46-54 (In Ukrainian). https://doi.org/10.18524/2307-4663.2013.4(24).48975 
  33. Matvienko, N., Kharkavlyuk, N., Buchatsky, L., & Didenko, A. (2013). Characteristics of spring viraemia of carp virus strains isolated in different regions of Ukraine. Zoology and Ecology, 23 (3), 198–202. https://doi.org/10.1080/21658005.2013.831530 
  34. Matvienko, N., Rud, Y., & Buchatsky, L. (2013). Replication of infectious pancreatic necrosis virus in different cell lines and organism of rainbow trout (Оncorhynchus mykiss) fingerlings. Archives of Polish Fisheries, 4, 127–133. https://doi.org/10.2478/aopf-2014-0012 
  35. Rud, Yu. P., Maistrenko, M. I., & Buchatsky, L. P. (2013). Amplification and analysis of the nucleotide sequence of VP2 TA NS IPNV genes isolated in Western Ukraine. Problems of ecological and medical genetics and clinical immunology, 4 (118), 34–40 (In Ukrainian).
  36. Maistrenko, M. I., Buchatsky, L. P., & Matvienko, N. M. (2013). Strain of herpesvirus IMB В-4 for the obtaining a vaccine against herpes virus koi. Patent of Ukraine № 79945 (In Ukrainian).
  37. Rud, Yu., Maistrenko, M., & Buchatsky, L. (2013). Іsolation of IPNV from wild-life rainbow trout (Оncorhynchus mykiss) in Western Ukraine. Biology, 3 (65), 63-65.
  38. Maistrenko, M. I., Rud, Yu. P., Matvienko, N. M., Cholodna, L. S., & Buchatsky, L. P. (2013). Identification of virus SyNV-3 by the methods of electron microscopy and polymerase chain reaction. Reports of the National Academy of Sciences of Ukraine, 4, 139-143 (In Ukrainian).
  39. Matvienko, N. M., Vashchenko, А. V., Tsiganok, I. O., & Buchatsky, L. P. (2015). Results of surveillance studies of infectious fish diseases in freshwater aquaculture of Ukraine. Agricultural science and practice, 2 (2), 32-38. https://doi.org/10.15407/agrisp2.02.032 
  40. Rud, Y. P., & Buchatsky, L. P. (2015). Detection of infectious pancreatic necrosis virus in the western Ukraine. Virologica sinica, 30 (2), 1-4. https://doi.org/10.1007/s12250-014-3513-z 
  41. Movchan, Yu. V. (2009). Fishes of Ukraine (taxonomy, nomenclature, remarks). Collection of works of Zoological Museum, 40, 47-87.
  42. Duan, Y., Fu, Z., & Li, D. (2003). Toward Developing and Using Web-based Tele-Diagnosis in Aquaculture. Expert System ith Applications, 25 (2), 247-254. https://doi.org/10.1016/S0957-4174(03)00050-2 
  43. Klyuchko, O. M. (2018). Method for monitoring of chemicals influence on bioorganisms in few time intervals. Patent of Ukraine. № 134575. (In Ukrainian).
  44. Klyuchko, O. М. (2017). Application of artificial neural networks method in biotechnology. Biotechnol. acta, 10 (4), 5–-13. https://doi.org/10.15407/biotech10.04.005.
  45. Klyuchko, O. М. (2017). Cluster analysis in biotechnology. Biotechnol. acta, 10 (5), 5-18. https://doi.org/10.15407/biotech10.05.005.
  46. Klyuchko, O. М., & Onopchuk, Yu. M. (2018). Some trends in mathematical modeling for biotechnology. Biotechnol. acta, 11 (1), 39-57. https://doi.org/10.15407/biotech11.01.039.
  47. Klyuchko, O. М. (2018). Electronic information systems in biotechnology. Biotechnol. acta, 11 (2), 5-22. https://doi.org/10.15407/biotech11.02.005.
  48. Klyuchko, O. М. (2018). Information computer technologies for biotechnology: electronic medical information systems. Biotechnol. acta, 11 (3), 5-26. https://doi.org/10.15407/biotech11.03.005.
  49. Klyuchko, O. М. (2018). Expert systems for biology and medicine. Biotechnol. аcta, 11 (6), 5-28. https://doi.org/10.15407/biotech11.06.005.
  50. Klyuchko, O. М. (2019). Biotechnical information systems for monitoring of chemicals in environment: biophysical approach. Biotechnol. acta, 12 (1), 5-28. https://doi.org/10.15407/biotech12.01.005 
  51. Klyuchko, O. М. (2017). On the mathematical methods in biology and medicine. Biotechnol. acta, 10 (3), 31-40. https://doi.org/10.15407/biotech10.03.031.
  52. Sachnyuk, G. V., & Melezhyk, O. V. (2017). Current state of water resources protection against pollution. Youth: education, science, spirituality: theses of reports XV Ukr. Sci. conf. Kyiv, 409-410.
  53. Schnase, J. L., Cushing, J., & Frame, M. (2003). Information technology challenges of biodiversity and ecosystems informatics. Inform. syst., 28 (4), 339-345. https://doi.org/10.1016/S0306-4379(02)00070-4 
  54. Linne, C. (1761). Fauna Suecica. Stocholmiac.
  55. Microsoft Academy: Methods and means of software engineering. intuit.ru. Retrieved from https://www.intuit.ru/studies/courses/2190/237/lecture/6124.
  56. Chomonenko, A. D., Tzygankov, V. M., & Maltzev, M. G. (2009). Databases. 6-th edn. Moskow: Binom Press. (In Russian).
  57. Harrington, Jan L. (2005). Object-oriented database design clearly explained. USA: Academic Press.
  58. Chen, Y., Shi, M., Cheng, Y., Zhang, W., Tang, Q., & Xia Q. (2018). FVD: The fish-associated virus database. Infect Genet., 58, 23-26. doi: 10.1016/j.meegid.2017.11.004.
  59. Smirnov, I. S., Voronina, E. P., Lobanov, A. L., Golikov, A. A., & Neyelov, A. V. (2004). Creation of Information retrieval systems on collections of marine animals (fishes and invertebrates) in the Zoological Institute of RAS. Proceedings of the Sixth National Russian Research Conference RCDL’2004. Moscow, 30-33.
  60. Zhang, Q., & Gui, J. F. (2015). Virus genomes and virus-host interactions in aquaculture animals. Sci. China Life Sci., 58 (2), 156-169. doi: 10.1007/s11427-015-4802-y.
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