Information technology of optimized agro-biological state management of agricultural lands

dc.citation.epage38
dc.citation.issue4
dc.citation.spage27
dc.citation.volume8
dc.contributor.affiliationTaras Shevchenko Kyiv National University
dc.contributor.affiliationKyiv Cooperative Institute of Business and Law
dc.contributor.authorSnytyuk, V.
dc.contributor.authorBrovarets, O.
dc.coverage.placenameLublin
dc.date.accessioned2020-02-28T09:27:46Z
dc.date.available2020-02-28T09:27:46Z
dc.date.created2019-06-26
dc.date.issued2019-06-26
dc.description.abstractAvailable techniques for dealing with uncertainties in the agro-industrial complex and their use for describing and assessing the adequacy of the decisions taken are incomplete, and often ineffective, as they usually do not take into account the combination of “field-machinetechnological material”, which prevents acceptance effective solutions for managing agro-biological potential of agricultural land and, as a consequence, obtaining the maximum economic efficiency of agricultural production. Reliable estimation of variables of agricultural production parameters using the “field-machine-technological material” model makes it possible to provide optimal control of available technical equipment (machinery, sowing machines, etc.), agro-biological (humus content, presence of nutrients, micro-and macro elements, etc. in soil or plant ) and technological resources for making adequate decisions and managing agro-biological potential of agricultural lands, which will provide the necessary economic efficiency. The task is achieved by ensuring the proper quality of the implementation of technological operations that are an integral indicator of economic efficiency and allow providing the necessary economic efficiency through optimal and efficient management of technical means for optimal action on the agrobiological potential of the field and the use of available technological resources. Such control is possible with the use of information and technical systems of local operational monitoring, which are located on machine-tractor units and provide effective control of technological operations by acting on the executive bodies of agricultural machines on the basis of data characterizing the agro-biological state of the soil environment. Information and technical systems of local operational monitoring of the agro-biological state of agricultural lands are used in the following cases: – before performing a technological operation, – simultaneously with the implementation of the technological operation (sowing, fertilizer application, etc.), – during the growing season and after harvesting. This opens new prospects for organic farming using such “smart” agricultural machines.
dc.format.extent27-38
dc.format.pages12
dc.identifier.citationSnytyuk V. Information technology of optimized agro-biological state management of agricultural lands / V. Snytyuk, O. Brovarets // Econtechmod : scientific journal. — Lublin, 2019. — Vol 8. — No 4. — P. 27–38.
dc.identifier.citationenSnytyuk V. Information technology of optimized agro-biological state management of agricultural lands / V. Snytyuk, O. Brovarets // Econtechmod : scientific journal. — Lublin, 2019. — Vol 8. — No 4. — P. 27–38.
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/46303
dc.language.isoen
dc.relation.ispartofEcontechmod : scientific journal, 4 (8), 2019
dc.relation.references1. Hertz A. Chad and John D. Hibbard. 1993. A Preliminary Assessment of the Economics of Variable Rate Technology for Applying Phosphorus and Potassium in Corn Production. In: Farm Economics iss. 14, Department of Agricultural Economics, University of Illinois, ChampaignUrbana. 218–231.
dc.relation.references2. Medvedev V. V. 2007. Soil heterogeneity and precision farming. Part I. Introduction to the problem. Kharkov. 296.
dc.relation.references3. Ivanov Yu. P, Sinyakov A. N., Filatov I. V. 1984. Integration of information and measuring devices LA. 207 p.
dc.relation.references4. Druzhba-Nova. Available at http://druzhba-nova.com/ru/index. html.
dc.relation.references5. Kbo-agro. Available at http://kbo-agro.com.ua.
dc.relation.references6. Geonics Limited. Available at http://www.geonics.com.
dc.relation.references7. Veristech Available at http://www.veristech.com.
dc.relation.references8. Patent No. 66982 dated January 25, 2012, bullet. No. 2, IPC B62D 01/00.
dc.relation.references9. Vadyunina A. F. 1937. To the assessment of electrical conductivity as a method for determining soil moisture. Soil Science. No. 3: 391–404.
dc.relation.references10. Wilcox G. G. 1947. Determination of electrical conductivity of soil solutions. Soil Science. Vol. 63. 107 p.
dc.relation.references11. Ewart G. Y., Baver L. D. 1950. Salinity Effects on soil moisture electrical resistance relationships. Soil Sciene. Soc. Amer. Vol. 15: 56–63.
dc.relation.references12. Vorobev N. I. 1955. To the question of conductometric determination of soil and soil salinity. Soil Science. No. 4. P. 103.
dc.relation.references13. Rhoades J. D. Schifgaarde J. Van. 1967. An electrical conductivity probe for determining soil salinity. Soil Scien. Soc. Amer. J. No. 5: 647–651.
dc.relation.references14. Kopikova L. P. 1979. Experience in the use of electrical conductivity for the preparation of detailed soil and soil maps. Bulletin of the VIUA. No. 43:21–23.
dc.relation.references15. GOST 26423-85. Soils. Methods for the determination of electrical conductivity, pH and dense residue of the aqueous extract. p.7.
dc.relation.references16. Pansu M. Gautheyrou J. 2006. Handbook of soil analysis. Mineralogical, organic and inorganic methods. Springer-Verlag Berlin Heidelberg. 993 p.
dc.relation.references17. Agrotehnology. Available at http://agrotehnology.com/tochnoe-zemledelie/ideologi/o-chemrasskazyvaet-udelnaya-elektroprovodnost-pochvy.
dc.relation.references18. Gukov Ya. S., Linnik N. K., Mironenko V. G. 2001. Automated system of locally dosed application of fertilizers, ameliorants and plant protection products. In: Proceedings of the 2nd MNPK on the problems of differential application of fertilizers in the coordinate farming system. Ryazan: 48–50.
dc.relation.references19. Brovarets O. 2002. From the Straightforward to the Global Smart Agriculture. Engineering and Technology of Agroindustrial Complex. No. 10(85): 28–30.
dc.relation.references20. Adamchuk V. V., Moiseenko V. K., Kravchuk V. I., Voytyuk D. G. 2002. Technique for future agriculture. In: Mechanization and electrification of agriculture. Glevakha: NSC “IMESG”. Ed. 86: 20–32.
dc.relation.references21. Modern trends in the development of agricultural machinery designs. Editors V. I. Kravchuk, M. I. Grytsyshina, S. M. Koval. – Kyiv, Agrarian Science, 2004. 398 p.
dc.relation.references22. Ormadzhi K. S. 1991. Quality control of field work. M.: Rosagropromizdat. 191.
dc.relation.references23. Pontryagin L. S., Boltyansky V. G., Gamkrelidze R. V., Mishchenko E. F. 1983. Mathematical theory of optimal processes. M.: Science. 392.
dc.relation.references24. Burachek V. G. Zheleznyak O. O., Zatserkovny V. I. 2011. Geoinformation analysis of spatial data. Nizhyn: Aspect-Polygraph Publishing Ltd. 440.
dc.relation.references25. Maslo I. P. Mironenko V. G. 1999. Automated system of locally-doped fertilizer and chemical plant protection products. UAAN: Developmentproduction. Kyiv, Agrarian Science: 348–349.
dc.relation.references26. Ivakhnenko A. G., Yurachkovsky Yu. P. 1987. Modeling of complex systems by experimental data. Mosow, Radio and communication. 120.
dc.relation.references27. Snytyuk V. Ye. 2005. Evolutionary simulation of the process of recovery of missing values in data tables In: Proceedings VII intern. sci. pract. conf. “System Analysis and Information Technologies”. Kyiv: NTUU of Ukraine “KPI”, 157.
dc.relation.references28. Wasserman F. 1992 Neurocomputer engineering: theory and practice. Moscow, Mir. 240.
dc.relation.references29. Brovarets O. 2019. Method of calculation of specific electrical conductivity of agro-biological soil environment by stationary contact method of operating electrodes of information and technical system of local operating monitoring. Econtechmod. Vol. 8, no 1: 3–10.
dc.relation.references30. Brovarets O., Chovnyk Yu. 2017. Technical – economic models of business management in the processes of agricultural production. Econtechmod. Vol. 6, No 3: 61–70.
dc.relation.referencesen1. Hertz A. Chad and John D. Hibbard. 1993. A Preliminary Assessment of the Economics of Variable Rate Technology for Applying Phosphorus and Potassium in Corn Production. In: Farm Economics iss. 14, Department of Agricultural Economics, University of Illinois, ChampaignUrbana. 218–231.
dc.relation.referencesen2. Medvedev V. V. 2007. Soil heterogeneity and precision farming. Part I. Introduction to the problem. Kharkov. 296.
dc.relation.referencesen3. Ivanov Yu. P, Sinyakov A. N., Filatov I. V. 1984. Integration of information and measuring devices LA. 207 p.
dc.relation.referencesen4. Druzhba-Nova. Available at http://druzhba-nova.com/ru/index. html.
dc.relation.referencesen5. Kbo-agro. Available at http://kbo-agro.com.ua.
dc.relation.referencesen6. Geonics Limited. Available at http://www.geonics.com.
dc.relation.referencesen7. Veristech Available at http://www.veristech.com.
dc.relation.referencesen8. Patent No. 66982 dated January 25, 2012, bullet. No. 2, IPC B62D 01/00.
dc.relation.referencesen9. Vadyunina A. F. 1937. To the assessment of electrical conductivity as a method for determining soil moisture. Soil Science. No. 3: 391–404.
dc.relation.referencesen10. Wilcox G. G. 1947. Determination of electrical conductivity of soil solutions. Soil Science. Vol. 63. 107 p.
dc.relation.referencesen11. Ewart G. Y., Baver L. D. 1950. Salinity Effects on soil moisture electrical resistance relationships. Soil Sciene. Soc. Amer. Vol. 15: 56–63.
dc.relation.referencesen12. Vorobev N. I. 1955. To the question of conductometric determination of soil and soil salinity. Soil Science. No. 4. P. 103.
dc.relation.referencesen13. Rhoades J. D. Schifgaarde J. Van. 1967. An electrical conductivity probe for determining soil salinity. Soil Scien. Soc. Amer. J. No. 5: 647–651.
dc.relation.referencesen14. Kopikova L. P. 1979. Experience in the use of electrical conductivity for the preparation of detailed soil and soil maps. Bulletin of the VIUA. No. 43:21–23.
dc.relation.referencesen15. GOST 26423-85. Soils. Methods for the determination of electrical conductivity, pH and dense residue of the aqueous extract. p.7.
dc.relation.referencesen16. Pansu M. Gautheyrou J. 2006. Handbook of soil analysis. Mineralogical, organic and inorganic methods. Springer-Verlag Berlin Heidelberg. 993 p.
dc.relation.referencesen17. Agrotehnology. Available at http://agrotehnology.com/tochnoe-zemledelie/ideologi/o-chemrasskazyvaet-udelnaya-elektroprovodnost-pochvy.
dc.relation.referencesen18. Gukov Ya. S., Linnik N. K., Mironenko V. G. 2001. Automated system of locally dosed application of fertilizers, ameliorants and plant protection products. In: Proceedings of the 2nd MNPK on the problems of differential application of fertilizers in the coordinate farming system. Ryazan: 48–50.
dc.relation.referencesen19. Brovarets O. 2002. From the Straightforward to the Global Smart Agriculture. Engineering and Technology of Agroindustrial Complex. No. 10(85): 28–30.
dc.relation.referencesen20. Adamchuk V. V., Moiseenko V. K., Kravchuk V. I., Voytyuk D. G. 2002. Technique for future agriculture. In: Mechanization and electrification of agriculture. Glevakha: NSC "IMESG". Ed. 86: 20–32.
dc.relation.referencesen21. Modern trends in the development of agricultural machinery designs. Editors V. I. Kravchuk, M. I. Grytsyshina, S. M. Koval, Kyiv, Agrarian Science, 2004. 398 p.
dc.relation.referencesen22. Ormadzhi K. S. 1991. Quality control of field work. M., Rosagropromizdat. 191.
dc.relation.referencesen23. Pontryagin L. S., Boltyansky V. G., Gamkrelidze R. V., Mishchenko E. F. 1983. Mathematical theory of optimal processes. M., Science. 392.
dc.relation.referencesen24. Burachek V. G. Zheleznyak O. O., Zatserkovny V. I. 2011. Geoinformation analysis of spatial data. Nizhyn: Aspect-Polygraph Publishing Ltd. 440.
dc.relation.referencesen25. Maslo I. P. Mironenko V. G. 1999. Automated system of locally-doped fertilizer and chemical plant protection products. UAAN: Developmentproduction. Kyiv, Agrarian Science: 348–349.
dc.relation.referencesen26. Ivakhnenko A. G., Yurachkovsky Yu. P. 1987. Modeling of complex systems by experimental data. Mosow, Radio and communication. 120.
dc.relation.referencesen27. Snytyuk V. Ye. 2005. Evolutionary simulation of the process of recovery of missing values in data tables In: Proceedings VII intern. sci. pract. conf. "System Analysis and Information Technologies". Kyiv: NTUU of Ukraine "KPI", 157.
dc.relation.referencesen28. Wasserman F. 1992 Neurocomputer engineering: theory and practice. Moscow, Mir. 240.
dc.relation.referencesen29. Brovarets O. 2019. Method of calculation of specific electrical conductivity of agro-biological soil environment by stationary contact method of operating electrodes of information and technical system of local operating monitoring. Econtechmod. Vol. 8, no 1: 3–10.
dc.relation.referencesen30. Brovarets O., Chovnyk Yu. 2017. Technical – economic models of business management in the processes of agricultural production. Econtechmod. Vol. 6, No 3: 61–70.
dc.relation.urihttp://druzhba-nova.com/ru/index
dc.relation.urihttp://kbo-agro.com.ua
dc.relation.urihttp://www.geonics.com
dc.relation.urihttp://www.veristech.com
dc.relation.urihttp://agrotehnology.com/tochnoe-zemledelie/ideologi/o-chemrasskazyvaet-udelnaya-elektroprovodnost-pochvy
dc.rights.holder© Copyright by Lviv Polytechnic National University 2019
dc.rights.holder© Copyright by University of Engineering and Economics in Rzeszów 2019
dc.subjectsoil
dc.subjectsamples
dc.subjectsize
dc.subjectvariability
dc.subjectuncertainty
dc.subjectadequacy
dc.subjectoperational monitoring
dc.subjectinformation and technical system
dc.titleInformation technology of optimized agro-biological state management of agricultural lands
dc.typeArticle

Files

Original bundle

Now showing 1 - 2 of 2
Thumbnail Image
Name:
2019v8n4_Snytyuk_V-Information_technology_of_27-38.pdf
Size:
520.86 KB
Format:
Adobe Portable Document Format
Thumbnail Image
Name:
2019v8n4_Snytyuk_V-Information_technology_of_27-38__COVER.png
Size:
502.46 KB
Format:
Portable Network Graphics

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.95 KB
Format:
Plain Text
Description: