Applied Aspects of Humus Balance Modelling in the Rivne Region of Ukraine

• Autorzy: Skrypchuk Petro , Zhukovskyy Viktor , Shpak Halyna , Zhukovska Nataliia , Krupko Halyna

Identyfikatory

DOI

10.12911/22998993/123255

• Języki publikacji: EN

Abstrakty

EN

The balance calculations in agriculture are the basis for assessing the value of land and determining how to use it effectively. Replenishing the humus balance in soils is a long and multifactorial process, and therefore requires considerable expenditures to control it. Therefore, scientists pay particular attention to the benefits and the need to create geoinformation portals, first and foremost, in the agricultural sector in order to create effective market-based tools for balancing soil quality. However, today Ukraine has little experience in creating portals and software for the implementation of soil fertility balance calculations in the online system for the purpose of organizing organic land use. The article deals with the methods of humus balance calculation and the formulation of the humus balance calculation task, which will take into account regional peculiarities of Ukraine’s Rivne region with the possibility of scaling to other areas. A mathematical model of the corresponding problem using differential equations was constructed. A numerical solution was found and implemented as the e-calculator module of online information system. The integration of IT technologies with the example of humus balance e-calculator for organic land use will allow crop rotations modeling and volumes of organic fertilizer application to stabilize or improve the soil quality. The main task of the calculator was to provide specific recommendations for the land plot on the efficiency of its use. In addition, the information system provided the background information on the economic efficiency of the transition to organic farming, certification, processing and marketing rules. The user can independently specify the order of crops cultivation in rotation, the amount of organic fertilizer application and as a result will receive the possible variants of the total humus content in the soil, for different volumes of application of organic fertilizers (biohumus) using the e-calculator of humus balance. The testing and verification of the e-calculator was carried out on the last 40 years data of the Rivne branch of the Soils Protection Institute of Ukraine, taking into account the cultivated crops, the introduction of mineral and organic fertilizers.

Słowa kluczowe

EN

humus balance; e-calculator; mathematical model; organic land use; crop rotation variants modeling; soil quality improvement; biohumus; organic portal

• Wydawca: Polskie Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology
• Czasopismo: Journal of Ecological Engineering
• Rocznik: 2020
• Tom: Vol. 21, nr 6
• Strony: 42--52
• Opis fizyczny: Bibliogr. 47 poz., rys., tab.

Twórcy

autor

Skrypchuk Petro

• National University of Water and Environmental Engineering, Soborna str. 11, Rivne, 33028, Ukraine

autor

Zhukovskyy Viktor

• National University of Water and Environmental Engineering, Soborna str. 11, Rivne, 33028, Ukraine

autor

Shpak Halyna

• National University of Water and Environmental Engineering, Soborna str. 11, Rivne, 33028, Ukraine

autor

Zhukovska Nataliia

• National University of Water and Environmental Engineering, Soborna str. 11, Rivne, 33028, Ukraine

autor

Krupko Halyna

• Rivne Branch of the Soils Protection Institute of Ukraine, Rivnenska str. 3, Shubkiv, 35325, Ukraine

Bibliografia

• 1. Baluk S.A., Grekov V.O., Forest M.V., Komarista A.V. 2011. Calculation of humus and nutrient balance in Ukrainian agriculture at different levels of management. Kharkiv, City Printing House.
• 2. Bernard L., Kanellopoulos I., Annoni A., Smits P. 2005. The European geoportal – one step towards the establishment of a European Spatial Data Infrastructure. Computers, Environment and Urban Systems 29, 15–31.
• 3. Bogdanovich R.P., Oliynyk V.S. 2014. Influence of crop residues of short-rotation crop rotation crops on the content of moving humus substances in the black soil of a typical light-loamed Right-Bank Forest Steppe (in Ukrainian). Scientific papers of the Institute of bioenergy crops and sugar beet, 20–24.
• 4. Boyko P.I., Litvinov D.V., Cymbal E.S., Kudrya S.O. 2018. Principles of development of rotational rotation systems in Ukraine (in Ukrainian). Proceedings of the National Science Center Institute of Agriculture NAAS, 3–14.
• 5. Brock C., Franko U., Oberholzer H.-R. et al. 2013. Humus balancing in Central Europe-concepts, state of the art, and further challenges. Journal of Plant Nutrition and Soil Science 176, 3–11.
• 6. Brock C., Hoyer U., Leithold G., Hülsbergen K.J. 2012. The humus balance model (HU-MOD): A simple tool for the assessment of management change impact on soil organic matter levels in arable soils. Nutrient cycling in agroecosystems 92, 239–254.
• 7. Brock C., Oltmanns M., Leithold G. 2015. What do humus balances really tell about soil organic matter? Acta fytotechnica et zootechnica 18, 50–52.
• 8. Campbell E.E., Paustian K. 2015. Current developments in soil organic matter modeling and the expansion of model applications: a review. Environmental Research Letters 10, 123004.
• 9. Chaban V.I., Kovalenko V.Y., Klauso S.P. 2010. Parameters of humus content in common black earth and forecast of its changes depending on agricultural production. Bulletin of the Grain Institute, 64–69.
• 10. Chertov O.G., Komarov A.S., Nadporozhskaya M., Bykhovets S.S., Zudin S.L. 2001. ROMUL–a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modeling. Ecological modelling 138, 289–308.
• 11. Franko U., Kolbe H., Thiel E., Ließ E. 2011. Multisite validation of a soil organic matter model for arable fields based on generally available input data. Geoderma 166, 119–134.
• 12. Gnatenko O.F., Kapstik M.V., Petrenko L.R., Vitvitsky S.V. 2005. Soil science with the basics of geology. Oranta.
• 13. Gorova A.I., Skvortsova T.V., Lisitska S.M. 2016. Restoration of humus condition and natural fertility of degraded black earths by means of vermicompost as organic fertilizer (in Ukrainian). Bulletin of Dnipropetrovsk State Agrarian and Economic University, 23–28.
• 14. Heitkamp F., Raupp J., Ludwig B. 2011. Soil organic matter pools and crop yields as affected by the rate of farmyard manure and use of biodynamic preparations in a sandy soil. Organic Agriculture 1:111–124.
• 15. Hénin S, Dupuis M. 1945. Essai de bilan de la matière organique du sol. Dudod.
• 16. Hrekov V.O., Datsko V.O. 2009. Rozrakhunok balansu humusu [Calculation of humus balance]. Posibnyk ukrainskoho khliboroba, 202–203.
• 17. Jaafar H.H., Woertz E. 2016. Agriculture as a funding source of ISIS: A GIS and remote sensing analysis. Food Policy 64, 14–25.
• 18. Kätterer T., Andrén O. 2001. The ICBM family of analytically solved models of soil carbon, nitrogen and microbial biomass dynamics–descriptions and application examples. Ecological Modelling 136, 191–207.
• 19. Kolbe H. 2010. Site-adjusted organic matter-balance method for use in arable farming systems. Journal of Plant Nutrition and Soil Science 173, 678–691.
• 20. Lebid E.M., Tsylyuryk O.I. 2014. Reproduction of black soil fertility and productivity of shortrotation steppe rotations depending on the soil mulching system (in Ukrainian). Bulletin of the Grain Institute, 8–14.
• 21. Leithold G., Hülsbergen K.J., Michel D., Schönmeier H. 1997. Humusbilanzierung–Methoden und Anwendung als Agrar-Umweltindikator. Initiativen zum Umweltschutz 5, 43–54.
• 22. Lisetskii F.N., Pichura V.I., Breus D.S. 2017. Use of geoinformation and neurotechnology to assess and to forecast the humus content variations in the steppe soils. Russian Agricultural Sciences 43, 157–161.
• 23. Litvinova E. 2020. The principle of the green field – AgroTimes. [Internet]. Available from: https://agrotimes.ua/article/princip-zelenogo-polya/ (last consult: 2020/04/01).
• 24. Lykov, A., M. 1979. Towards a method for the calculation of soil humus balance in intensive agriculture (in Russian). TLC news, 14–20.
• 25. Maguire D.J., Longley P.A. 2005. The emergence of geoportals and their role in spatial data infrastructures. Computers, Environment and Urban Systems 29, 3–14.
• 26. Manzoni S., Porporato A. 2009. Soil carbon and nitrogen mineralization: theory and models across scales. Soil Biology and Biochemistry 41, 1355–1379.
• 27. Medvedev V.V. 2007. Soil heterogeneity and precision agriculture (in Russian). Part I. Introduction to the problem. Kharkov Ed 13.
• 28. Mishra A.K., Deep S., Choudhary A. 2015. Identification of suitable sites for organic farming using AHP & GIS. The Egyptian Journal of Remote Sensing and Space Science 18, 181–193.
• 29. Montgomery B., Dragićević S., Dujmović J., Schmidt M. 2016. A GIS-based Logic Scoring of Preference method for evaluation of land capability and suitability for agriculture. Computers and Electronics in Agriculture 124, 340–353.
• 30. Morozov V.V., Plotkin S. I ., Polyakov M.G. 2007. Modeling and forecasting for geoinformation systems projects: Tutorial book. Kherson: KSU Publishing House.
• 31. Oliver Y.M., Gabriel A.J., Germanovich O.M., Sivak L.M. 2014. Dynamics of the labile part of the humus of light-gray forest surface-covered soil, depending on long fertilization and periodic liming (in Ukraine). Foothills and mountain farming and animal husbandry, 141–147.
• 32. Oumenskou H., El Baghdadi M., Barakat A. et al. 2018. Assessment of the heavy metal contamination using GIS-based approach and pollution indices in agricultural soils from Beni Amir irrigated perimeter, Tadla plain, Morocco. Arabian Journal of Geosciences 11, 405.
• 33. Pichura V.I., Potravka L.A., Dudiak N.V., Skrypchuk P.M., Stratichuk N.V. 2019. Retrospective and Forecast of Heterochronal Climatic Fluctuations Within Territory of Dnieper Basin. Indian Journal of Ecology 46, 402–407.
• 34. Romashchenko M.I, Rachinska E.S, Shevchenko, A.M. (Eds). 2005. Information support for irrigated agriculture. The concept, structure, methodology of the organization (in Ukrainian). Kyiv: Agrarian science.
• 35. Schulz F., Brock C., Schmidt H., Franz K.-P., Leithold G. 2014. Development of soil organic matter stocks under different farm types and tillage systems in the Organic Arable Farming Experiment Gladbacherhof. Archives of Agronomy and Soil Science 60, 313–326.
• 36. Shostak L., Boiko M., Stepanchenko O., Kozhushko O. 2019. Analysis of soil organic matter transformation dynamics models. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 9, 40–45.
• 37. Skrylnik E.V., Shevchenko M.V., Popirny M.A. 2017. Influence of soil tillage systems on the distribution and quality of humic soil of typical black soil (in Ukrainian). Fundamental and Applied Soil Science 18, 46–54.
• 38. Skrypchuk P.M., Shcherbakova O.Y., Suduk O.Y., Rybak V.V. 2020. Renewable Biomass Growing in Low Fertile Land and Forest-Steppe of Ukraine. Indian Journal of Ecology 47, 155–163.
• 39. Skrypchuk PM. (Ed). 2018a. Information support for the development of organic agriculture. Rivne: NUWEE.
• 40. Skrypchuk P.M. (Ed). 2018b. Organizational and economic principles of information support of the economy. Rivne: NUWEE.
• 41. Skrypchuk P.M. (Ed). 2019. Geo-management in organic agriculture. Podhajska, Slovensko: Europsky institut dalsieho vzdelavania.
• 42. Tait M.G. 2005. Implementing geoportals: applications of distributed GIS. Computers, Environment and Urban Systems 29, 33–47.
• 43. Vlasyuk A., Zhukovska N., Zhukovskyy V., Hesham R. 2020a. Mathematical Modelling of Spatial Deformation Process of Soil Massif with Free Surface. Advances in intelligent systems and computing IV 1080, 107–120.
• 44. Vlasyuk A., Zhukovskyy V., Zhukovska N., Pinchuk O., Rajab H. 2020b. Mathematical Modeling of Heat, Mass and Moisture Transfer in Catalytic Porous Media. WSEAS Transactions on Applied and Theoretical Mechanic 15, 52–59.
• 45. Vlasyuk A.P., Borowik B., Zhukovska, N.A., Zhukovskyy V.V., Karpinskyi V. 2018a. Computer modelling of heat and mass transfer effect on the threedimensional stressed-strained state of soil massif. 18th International Multidisciplinary Scientific Geoconference SGEM 2018 18, 153–160.
• 46. Vlasyuk A.P., Kochan R.V., Zhukovskyy V.V., Zhukovska N.A. 2018b. Mathematical and computer modeling of contaminant migration to filter trap in two-dimensional nonlinear case. 18th International Multidisciplinary Scientific Geoconference SGEM 2018 18, 293–300.
• 47. Volkogon V.V., Berdnikov O.M., Tokmakova L.M. et al. 2016. Orientation of processes of biological transformation of nitrogen in the rhizospheric soil of potato plants under the action of biotic and abiotic factors of crop fertilizer (in Ukrainian). Agricultural Microbiology, 3–9.