PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Optimisation of crop rotations : A case study for corn growing practices in forest-steppe of Ukraine

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The formation of optimal crop rotations is virtually unsolvable from the standpoint of the classical methodology of experimental research. Here, we deal with a mathematical model based on expert estimates of “predecessor-crop” pairs’ efficiency created for the conditions of irrigation in the forest-steppe of Ukraine. Solving the problem of incorporating uncertainty assessments into this model, we present new models of crop rotations’ economic efficiency taking into account irrigation, application of fertilisers, and the negative environmental effect of nitrogen fertilisers’ introduction into the soil. For the considered models we pose an optimisation problem and present an algorithm for its solution that combines a gradient method and a genetic algorithm. Using the proposed mathematical tools, for several possible scenarios of water, fertilisers, and purchase price variability, the efficiency of growing corn as a monoculture in Ukraine is simulated. The proposed models show a reduction of the profitability of such a practice when the purchase price of corn decreases below 0.81 EUR∙kg-1 and the price of irrigation water increases above 0.32 EUR∙m-3 and propose more flexible crop rotations. Mathematical tools developed in the paper can form a basis for the creation of decision support systems that recommend optimal crop rotation variations to farmers and help to achieve sustainable, profitable, and ecologically safe agricultural production. However, future works on the actualisation of the values of its parameters need to be performed to increase the accuracy.
Wydawca
Rocznik
Tom
Strony
194--202
Opis fizyczny
Bibliogr. 51 poz., mapa, tab.
Twórcy
  • Institute of Water Problems and Land Reclamation of NAAS, Kyiv, Ukraine
  • V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine, Laboratory of Methods of Mathematical Modeling of Ecology and Energy Processes, Glushkov Ave, 40, 03187, Kyiv, Ukraine
  • Institute of Water Problems and Land Reclamation of NAAS, Kyiv, Ukraine
autor
  • Institute of Water Problems and Land Reclamation of NAAS, Department of Using of Agroresource Potential, Kyiv, Ukraine
  • Institute of Water Problems and Land Reclamation of NAAS, Department of Information Technology and Marketing Innovation, Kyiv, Ukraine
  • Institute of Water Problems and Land Reclamation of NAAS, Department of Information Technology and Marketing Innovation, Kyiv, Ukraine
Bibliografia
  • Agro-Ukraine undated [online]. [Access 10.12.2022]. Available at: https://agro-ukraine.com
  • ALFANDARI L., PLATEAU A., SCHEPLER X. 2015. A branch-and-price-and-cut approach for sustainable crop rotation planning. European Journal of Operational Research. Vol. 241(3) p. 872–879. DOI 10.1016/j.ejor.2014.09.066.
  • AVRAMENKO S.V., TSEKHMEYSTRUK M.G., POPOV S.I., TEMCHUK V.M. 2012. Urozhaynist' kukurudzy zalezhno vid strokiv sivby ta systemy udobrennya u skhidniy chastyni Lisostepu Ukrayiny [Vegetation of corn depending on sowing dates and fertilisation systems in the eastern part of the forest-steppe Ukraine]. Visnyk TsNZ APV Kharkivs'koyi oblastii. No. 12 p. 4–8.
  • BALCHENKO I.V., LYTVYNOV V.V., LYTVYN S.V. 2014. The development of the model of the expert system on the basis of fuzzy sets for panning of agricultural work. Matematychni mashyny i systemy. No. 4 p. 118–128.
  • BioModel undated. Pryrodno-silskohospodarske zonuvannia Ukrajiny [Natural-agricultural zoning of Ukraine] [online]. [Access 10.12.2022]. Available at: https://biomodel.info/ua/training-package/ukraine-nature-agricultural-zoning/
  • CISNEROS J.M., GRAU J.B., ANTON J.M., DE PRADA J.D., CANTERO A., DEGIOANNI A.J. 2011. Assessing multi-criteria approaches with environmental, economic and social attributes, weights and procedures: A case study in the Pampas, Argentina. Agricultural Water Management. Vol. 98(10) p. 1545–1556. DOI 10.1016/j.agwat.2011.05.009.
  • DETLEFSEN N. 2004. Crop rotation modelling. In: Proceedings of the EWDA-04 European workshop for decision problems in agriculture and natural resources. Wrest Park, England. Silsoe Research Institute p. 5–14.
  • DURY J., SCHALLER N., GARCIA F., REYNAUD A., BERGEZ J.E. 2012. Models to support cropping plan and crop rotation decisions. A review. Agronomy for Sustainable Development. Vol. 32(2) p. 567–580. DOI 10.1007/s13593-011-0037-x.
  • GADZALO YA .M., KAMINSKY V.F., SAIKO V.F. 2015. Crop rotations in agriculture of Ukraine. Zemlerobstvo. No. 1 p. 3–6.
  • GARCIA F., GUERRIN F., MARTIN-CLOUAIRE R., RELLIER J.-P. 2005. The human side of agricultural production management – The missing focus in simulation approaches [online]. In: MODSIM 2005 International Congress on Modelling and Simulation p. 203–209. [Access 10.12.2022]. Available at: https://agritrop.cirad.fr/531833/1/document_531833.pdf
  • GLUSHKO T.V. 2012. Vplyv zroshennya ta mineral'nykh dobryv na urozhaynist' hibrydiv kukurudzy v umovakh pivdennoho Stepu Ukrayiny [Influence of irrigation and mineral fertilisers on the yield of corn hybrids under the conditions of the southern steppe of Ukraine] [online]. Zroshuvane zemlerobstvo. No. 57 p. 125–130. [Access 10.12.2022]. Available at: http://izpr.ks.ua/archive/2012/57/21.pdf
  • GOLDBERG D.E. 1989. Genetic algorithms in search, optimization and machine learning. Boston, USA. Addison-Wesley Professional. ISBN 978-0-201-15767-3 pp. 372.
  • HANHUR V., KOHAN V., LEN O., SEMIASHKINA A. 2015. Vyroshchuvannya kukurudzy na zerno v bezzminnomu posivi ta sivozmini [Growing corn for grain in non-alternated sowing and crop rotation] [online]. Byuleten' Instytutu sil's'koho hospodarstva stepovoyi zony NAAN Ukrayiny. No. 8 p. 138–140. [Access 10.12.2022]. Available at: http://www.irbis-nbuv.gov.ua/cgi-bin/irbis_nbuv/cgiirbis_64.exe?I21DBN=LINK&P21DBN=UJRN&Z21ID=&S21-REF=10&S21CNR=20&S21STN=1&S21FMT=ASP_meta&C21-COM=S&2_S21P03=FILA=&2_S21STR=bisg_2015_8_26
  • HOSPODARENKO H.M., PROKOPCHUK I.V., STASINIEVYCH O.Y., BOIKO V.P. 2019. Produktyvnist' pol'ovoyi sivozminy za riznykh doz i spivvidnoshen' dobryv [Productivity of field crop rotation at different doses and ratios of fertilisers] [online]. Naukovi horyzonty. No. 3 p. 80–86. [Access 10.12.2022]. Available at: http://www.irbis-nbuv.gov.ua/cgi-bin/irbis_nbuv/cgiirbis_64.exe?I21DBN=LINK&P21DB- N=UJRN&Z21ID=&S21REF=10&S21CNR=20&S21STN=1&S21FMT=ASP_meta&C21COM=S&2_S21P03=FILA=&2_S21STR=Vzhnau_2019_3_12
  • IAS “Ahrariyi razom” undated. Kalkuliator dobryv dlia gruntovoho vnesennia [Calculator of fertilisers for the application in a soil] [online] [Access 10.12.2022]. Available at: https://agrarii-razom.com.ua/calculators/kalkulyator-dobriv-dlya-gruntovogo-vnesennya
  • KAMINSKY V.F., BOYKO P.I. 2014a. Strategy of development and implementation of crop rotations in Ukraine (Part 1). Zbirnyk naukovykh prats' NNTs “Instytut zemlerobstva NAAN”. No. 3 p. 3–9.
  • KAMINSKY V.F., BOYKO P.I. 2014b. Strategy of development and implementation of crop rotations in Ukraine (Part 2). Zbirnyk naukovykh prats' NNTs “Instytut zemlerobstva NAAN”. No. 4 p. 3–11.
  • KHAMUKOV V.B., MALAMATOVA B.V. 2004. Dozy i sochetaniya udobreniy pod gibridy kukuruzy razlichnykh srokov sozrevaniya [Doses and combinations of fertilisers for maize hybrids of different maturation periods]. Agrokhimicheskiy vestnik. No. 5 p. 18–20.
  • KOKOVYKHIN S.V., PISARENKO P.V., PRYSIAZHNYJ Y U.I., PYLYARSKAYA O.O. 2011. Vplyv volohozabezpechenosti, fonu mineral'noho zhyvlennya ta hustoty stoyannya roslyn na urozhaynist' dilyanok hibrydyzatsiyi kukurudzy v umovakh zroshennya [Influence of water supply, mineral nutrition background and plant density on the yield of maize hybridisation areas under irrigation]. Zroshuvane zemlerobstvo. No. 56 p. 20–25.
  • KOVALENKO N.P. 2007. Optymizatsiya struktury posivnykh ploshch i spetsializovanykh sivozmin metodom ekonomiko-matematychnoho modelyuvannya [Optimisation of the structure of sown areas and specialised crop rotations by the method of economical and mathematical modelling]. Pratsi Instytutu tsukrovoho buryaka NAAN Ukrayiny. No. 9 p. 245–251.
  • KOVALENKO N.P. 2012. Rozvytok ta udoskonalennya sivozmin dlya umov nedostatn'oho zvolozhennya ukrayiny [Development and improvement of crop rotations for the conditions of insufficient humidification in Ukraine]. Visnyk Poltavs'koyi derzhavnoyi ahrarnoyi akademiyi. No. 4 p. 27–32.
  • KRASNOVS'KYY S. 2017. Efectyvne udobrennia kukurudzy [Effective fertilisation of corn] [online]. Ahronom. [Access 10.12.2022]. Available at: https://www.agronom.com.ua/efektyvne-udobrennya-kukurudzy/
  • LAVRYNENKO Y.O., KOKOVIKHIN S.V., PYSARENKO P.V., NAIDIONOV V.H., MYKHAILENKO I.V. 2009. Kukurudza na zroshuvanykh zemlyakh pivdnya Ukrayiny: Monohrafiya [Corn on irrigated lands in southern Ukraine: Monograph]. Kherson, Ukraine. Ailant pp. 428.
  • LAZER P.N., MIKHEIEV I E .K. 2006. Instrumentariy i tekhnolohiyi orhanizatsiyi informatsiyi v zemlerobstvi. Navchal'nyy posibnyk [Tools and technologies of information organisation in agriculture. Teaching guide]. Kherson, Ukraine. Vydavnychij dim KhDU pp. 368.
  • LEE G., BAO C H., LANGRENE N., Z HU Z. 2015. Choosing crop rotations under uncertainty: A multi-period dynamic portfolio optimization approach [online]. In: 21st International Congress on Modelling and Simulation. Gold Coast, Australia p. 1084–1090. [Access 10.12.2022]. Available at: https://www.mssanz.org.au/modsim2015/E6/lee.pdf
  • MACKAY D.C., EAVES C.A. 1962. The influence of irrigation treatments on yields and on fertilizer utilization by sweet corn and snap beans. Canadian Journal of Plant Science. Vol. 42. No. 2 p. 219–228. DOI 10.4141/cjps62-032.
  • MANZHOS D.M., SHULJHA Z.F. 1998. Informatsiyno-poshukova avtomatyzovana systema ahronoma. V: Systemni doslidzhennya ta modelyuvannya v zemlerobstvi: Zbirnyk naukovykh prats' za redaktsiyeyu akademika AIN Ukrayiny O.A. Shevchenka [Informational retrieval automated system for agronomists. In: System studies and modeling in agriculture: A collection of scientific works edited by academician of the National Academy of Sciences of Ukraine O.A. Shevchenko]. Kyiv, Ukraine. Nyva p. 76–86.
  • Map of Europe undated [online]. [Access 10.12.2022]. Available at: https://d31xsmoz1lk3y3.cloudfront.net/games/images/map_img_1041394_1583453046.jpg
  • MARINICH A.M., PASCHENKO V.M., SHISHCHENKO P.G. 1985. Priroda Ukrainskoy SSR. Landshafty i fiziko-geograficheskoye rayonirovaniye [The nature of the Ukrainian SSR. Landscapes and physical-geographical zoning]. Kyiv, Ukraine. Naukova dumka pp. 224.
  • MARYNYCH O.M. 1993. Heohrafichna entsyklopediya Ukrayiny [Geographical encyclopaedia of Ukraine]. Kyiv, Ukraine. “Ukrayins'ka Radyans'ka Entsyklopediya” im. M.P. Bazhana. ISBN 5-88500-015-8 pp. 1376.
  • MATYASH T.V. 2009. Naukove obhruntuvannya systemy pryynyattya rishen' v platnomu vodokorystuvanni pry zroshenni [Scientific substantiation of the decision-making system in paid water use during irrigation]. Kyiv. Ukrayins'kyy instytut hidrotekhniky i melioratsiyi pp. 234.
  • NUPPENAU E.A. 2011. Linking crop rotation and fertility management by a transition matrix: Spatial and dynamic aspects in programming of ecosystem service. In: Congress EAAE “Change and Uncertainty Challenges for Agriculture, Food and Natural Resources” (12), 2011 International Congress, August 30 –September 2, 2011, Zurich, Switzerland 114600. European Association of Agricultural Economists p. 1–12. DOI 10.22004/ag.econ.114600.
  • OSMAN J., INGLADA J., DEJOUX J.-F. 2015. Assessment of a Markov logic model of crop rotations for early crop mapping. Computers and Electronics in Agriculture. Vol. 113 p. 234–243. DOI 10.1016/j.compag.2015.02.015.
  • OSTAPENKO R., HERASYMENKO Y., NITSENKO V., KOLIADENKO S., BALEZENTIS T., STREIMIKIENE D. 2020. Analysis of production and sales of organic products in Ukrainian agricultural enterprises. Sustainability. Iss. 12. No. 8, 3416. DOI 10.3390/su12083416.
  • PAVÓN R., BRUNELLI R., VON LÜCKEN C H. 2009. Determining optimal crop rotations by using multiobjective evolutionary algorithms. In: International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science. Eds. J.D. Velásquez, S.A. Ríos, R.J. Howlett, L.C. Jain. Vol. 5711. Berlin, Heidelberg. Springer p. 147–154. DOI 10.1007/978-3-642-04595-0_18.
  • PLOURDE J.D., PIJANOWSKI B.C., PEKIN B.K. 2013. Evidence for increased monoculture cropping in the Central United States. Agriculture, Ecosystems & Environment. Vol. 165 p. 50–59. DOI 10.1016/j.agee.2012.11.011.
  • ROMASHCHENKO M., TARARIKO Y U., SHATKOVSKYI A., SAYDAK R., SOROKA YU . 2015. Naukovi zasady rozvytku zemlerobstva u zoni Stepu Ukrayiny [Scientific principles of development of systems of farming agriculture in zone of Steppe of Ukraine]. Bulletin of Agricultural Science. Vol. 93(10) p. 5–9. DOI 10.31073/agrovisnyk201510-01.
  • ROMASHCHENKO M.I., MATYASH T.V., KOVALCHUK V.P., BOHAIENKO V.O. 2016a. Avtomatyzatsiya i optymizatsiya pidboru dobryv za balansovym metodom [Automation and optimisation of the selection of fertilisers by the balance method]. Melioratsiya i vodne hospodarstvo. No. 104 p. 82–86.
  • ROMASHCHENKO M.I., MUZYKA O.P., VOZHEHOVA R.A., MALIARCHUK M.P. 2016b. Productivity of crop rotations on irrigated lands at their different saturation with grain-growing and technical cultures. Bulletin of Agricultural Science. Vol. 94(2) p. 32–37. DOI 10.31073/agrovisnyk201602-07.
  • ROMASHCHENKO M.I., VOZHEHOVA R.A., SHATKOVSKY A.P. 2017. Naukovi zasady rozvytku ahrarnoho sektora ekonomiky pivdennoho rehionu Ukrayiny [Scientific base of agricultural sector of the economy of the southern region of Ukraine]. Kherson, Ukraine. OLDI-PLYUS. ISBN 978-966-289-163-8 pp. 438.
  • ROMASHCHENKO M., MATIASH T., BOHAIENKO V., KOVALCHUK V., LUKASHUK V., SAYDAK R. 2021. Algorithms to optimise cropping diversity with cover crops. In: Cover crops and sustainable agriculture. Eds. R. Islam, B. Sherman. Boca Raton. CRC Press p. 58–68. DOI 10.1201/9781003187301-5.
  • SANTOS L.M.R., MUNARI P., COSTA A.M., SANTOS R.H.S. 2015. A branch-price-and-cut method for the vegetable crop rotation scheduling problem with minimal plot size. European Journal of Operational Research. Vol. 245(2) p. 581–590. DOI 10.1016/j.ejor.2015.03.035.
  • SCHÖNHART M., SCHMID E., SCHNEIDER U.A. 2009. CropRota – A model to generate optimal crop rotations from observed land use [online]. Working Paper No. DP-45-2009. Vienna. Institute for Sustainable Economic Development, Department of Economics and Social Sciences, University of Natural Resources and Life Sciences pp. 27. [Access 10.12.2022]. Available at: https://www.econstor.eu/bitstream/10419/235171/1/dp45-2009.pdf
  • SENCHUK M.M. 2017. Obhruntuvannya metodyky vyznachennya normy vnesennya orhanichnykh ta mineral'nykh dobryv dlya systemy orhanichnoho zemlerobstva [Substantiation of the methodic for the determination of organic and mineral fertilisers’ norms for organic agriculture system] [online]. Tekhnika i tekhnolohiyi APK. No. 1 p. 34–38. [Access 10.12.2022]. Available at: http://rep.btsau.edu.ua/bitstream/BNAU/1064/1/obgruntuvannja%20metodiki.pdf
  • SHEVCHENKO A.O., MANZHOS D.M. 1998. Ekspertno-kibernetychna systema optymizatsiyi tekhnolohiyi u zemlerobstvi. V: Systemni doslidzhennia ta modeliuvannia v zemlerobstvi. Zbirnyk naukovych pratsya za redaktsiyeyu akademika AIN Ukrayiny O.A. Shevchenka [Expert-cybernetic system for technology optimisation in agriculture. In: System studies and modeling in agriculture. A collection of scientific works edited by academician of the National Academy of Sciences of Ukraine O.A. Shevchenko]. Kyiv, Ukraine. Nyva p. 274–285.
  • THRUPP L.A. 2000. Linking agricultural biodiversity and food security: The valuable role of agrobiodiversity for sustainable agriculture. International Affairs. Vol. 76(2) p. 265–281. DOI 10.1111/1468-2346.00133.
  • TREVISAN L. 2011. Combinatorial optimization: Exact and approximate algorithms. San Francisco. Stanford University pp. 139.
  • USHKARENKO V.O., LIKHOVID P.V. 2016. Rehresiyna model' urozhaynosti kukurudzy tsukrovoyi zalezhno vid ahrotekhnolohiyi v zroshuvanykh umovakh sukhoho stepu Ukrayiny [Regression model of yield of sugar corn depending on agrotechnology in irrigated conditions of dry steppe of Ukraine] [online]. Visnyk Umans'koho natsional'noho universytetu sadivnytstva. No. 1 p. 31–34. [Access 10.12.2022]. Available at: https://visnyk-unaus.udau.edu.ua/assets/files/articles/Bulleten2016/2/10.pdf
  • VERGUNOVA I.M. 2000. Osnovy matematychnoho modelyuvannya dlya analizu ta prohnozu ahronomichnykh protsesiv [Fundamentals of mathematical modelling for the analysis and prognosis of agronomic processes]. Kyiv, Ukraine. Nora-Print pp. 146.
  • VYSHNEVSKII V.V. 1999. Vplyv tryvaloho zastosuvannya dobryv na rodyuchist' dernovo-slabkopidzolystoho hlynysto-pishchanoho hruntu ta produktyvnist' kul'tur v pol'ovykh sivozminakh [Influence of long-term application of fertilisers on the fertility of sod-weakly podzolic clay-sandy soil and the productivity of crops in field crop rotations] [online]. PhD Thesis summary. Kyiv. Natsional'nyy ahrarnyy universytet. [Access 10.12.2022]. Available at: http://library.nuft.edu.ua/ebook/file/06.01.04VVVKPS.pdf
  • YURKEVICH Y E.O., KOVALENKO N.P., BAKUMA A.V. 2011. Ahrobiolohichni osnovy sivozmin Stepu Ukrayiny: Monohrafiya [Agrobiological basis of crop rotations in the steppe of Ukraine]. Odessa, Ukraine. VMV pp. 237.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b7c1be1e-165c-4c33-8bce-727e284bf3a7
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.