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The article shows the possibility of using modern methods of artificial intelligence to calculate the yield of biomass of crops according to the given set input data (fertilizer doses, agrochemical parameters of the soil, productivity). The study reflects the results of testing a model of a computer program of an artificial neural network, which allowed forecasting the yield of Panicum virgatum L. (Switchgrass) depending on the joint application of fertilizers mineral and precipitate. On the basis of the calculations, the obtained model of productivity of vegetative mass of switchgrass shows a high level of forecasting efficiency (up to 97%). According to the results of experimental studies, the use of sewage sludge at a doses of 20–40 t/ha provides a dry biomass yield of Panicum virgatum L. (Switchgrass) in the range of 13.1–20.3 t/ha, which is 3.4–7.2 t/ha more than in the option without fertilizer.
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Tom
Strony
62--71
Opis fizyczny
Bibliogr. 43 poz., rys., tab.
Twórcy
- National University of Life and Environmental Sciences of Ukraine, Heroiv Oborony Str.15, 03041, Kyiv, Ukraine
- Ivano-Frankivsk National Technical University of Oil and Gas, Karpatska Street, 15, 76000, Ivano-Frankivsk, Ukraine
- National University of Life and Environmental Sciences of Ukraine, Heroiv Oborony Str.15, 03041, Kyiv, Ukraine
autor
- National University of Life and Environmental Sciences of Ukraine, Heroiv Oborony Str.15, 03041, Kyiv, Ukraine
- National University of Life and Environmental Sciences of Ukraine, Heroiv Oborony Str.15, 03041, Kyiv, Ukraine
- National University of Life and Environmental Sciences of Ukraine, Heroiv Oborony Str.15, 03041, Kyiv, Ukraine
- Ivano-Frankivsk National Medical University, Halytska Str. 2, 76018, Ivano-Frankivsk, Ukraine
Bibliografia
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- 4. Dumitrache A., Natzke J., Rodriguez M.J., Yee K.L., Thompson O.A., Poovaiah C.R., et al. 2017. Transgenic switchgrass (Panicum virgatum L.) targeted for reduced recalcitrance to bioconversion: a two-year comparative analysis of field-grown lines modified for target gene or genetic element expression. Plant Biotechnol, J., 15, 688–697. https://doi.org/10.1111/pbi.12666
- 5. Lehtokangas M. 2000. Determining the number of centroids for CMLP network Neural networks. Elsevier https://doi.org/10.1016/S0893–6080(00)00021–6
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- 7. Elbersen H.W., Christian D.G., El-Bassem N., Bacher W., Sauerbeck G., Alexopoulou E., Sharma N., Piscioneri I., de Visser P., van den Berg D. 2001. Switchgrass variety choice in Europe. Aspects Appl. Biol., 65, 21–28.
- 8. Elbersen W., Poppens R., Bakker R. 2013. Switchgrass (Panicum virgatum L.). A perennial biomass grass for efficient production of feedstock for the biobased economy. A report for the Netherlands Programmes Sustainable Biomass of NL Agency.
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- 11. Jefferson P.G., McCaughey M.P. 2012. Switchgrass (Panicum virgatum L.) cultivar adaptation, biomass production, and cellulose concentration as affected by latitude of origin. ISRN Agronomy; 2012763046 http://dx.doi.org/10.5402/2012/763046
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- 15. Kharchenko O., Zakharchenko E., Kovalenko I., Prasol V., Pshychenko O., Mishchenko Y. 2019. On problem of establishing the intensity level of crop variety and its yield value subject to the environmental conditions and constraints. AgroLife scientific journal, 8(1), 113–119.
- 16. Lesschen J.P., Elbersen W., Poppens R., Galytskaya M., Kulyk M., Lerminiaux L. 2012. The financial and greenhouse gas cost of avoiding ILUC in biomass sourcing – A comparison between switchgrass produced with and without ILUC in Ukraine. In. Eur. Biomass Conf., Milan, Italy 2012.
- 17. Liu W., Mazarei M., Ye R., Peng Y., Shao Y., Baxter H.L., et al. 2018. Switchgrass (Panicum virgatum L.) promoters for green tissue-specific expression of the MYB4 transcription factor for reduced-recalcitrance transgenic switchgrass. Biotechnol. Biofuels, 11, 122. https://doi.org/10.1186/s13068–018–1119–7
- 18. Lopushniak V., Hrytsuliak H. 2021. The Models of the Heavy Metal Accumulation of the Multiple Grain Energy Cultures for Wasterwater Deposition on Oil-Polluted Degraded Soils. Ecological Engineering & Environmental Technology. 22(4), 1–13.
- 19. Mann D.G.J., LaFayette P.R., Abercrombie L.L., King Z.R., Mazarei M., Halter M.C., et al. 2012. Gateway-compatible vectors for high-throughput gene functional analysis in switchgrass (Panicum virgatum L.) and other monocot species. Plant Biotechnol. J. 10, 226–236. https://doi.org/10.1111/j.1467–7652.2011.00658.
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- 24. Oliveira J., West C., Afif E., Palencia P. 2017. Comparison of miscanthus and switchgrass cultivars for biomass yield, soil nutrients, and nutrient removal in northwest Spain, 109–122. http://dx.doi.org/10.2134/agronj2016.07.0440
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6e413fb2-6fdc-4ff3-b1ff-c72bc2b0aef0