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Modelling Irrigation Regimes of Different Varieties of Rice with AquaCrop Software

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article presents the results of the application of modern information technologies, which allow agricultural producers to precisely control the dynamics of water consumption at the level of irrigation system, farmland and individual fields of rice crop rotations under the conditions of drip irrigation. The use of computer programs enables optimization of irrigation regimes and delivers savings in terms of water, energy, technical means and labor resources, contributing to an increase in yields and improvements of their quality, increases in economic efficiency and environmental safety of agriculture on irrigated lands. As a part of SRW "Development and improvement of irrigation regimes of rice and related crops of rice crop rotation on the basis of normalization of irrigation water and determination of the dynamics of evapotranspiration at the field level", AquaCrop software was used to model the productivity of rice under conditions of drip irrigation. The results of research on the topic of improvement of technological processes for growing modern varieties of rice in order to enhance seeding and harvesting properties, which were conducted in 2017 at the Institute of Rice NAAS, were used as experimental data. Indicator data, including temperature, wind speed and precipitation in 2017 were obtained from the local weather station, whereas information on the duration of the sunny day, local coordinates etc. was gleaned from Internet resources. AquaCrop models water and nutrient consumption to achieve desired yields and establish response to optimal and resource-saving irrigation of crops with different biological parameters, including rice. Components of the cultivation process of different rice varieties were established with simulation modeling. Convenience, accuracy and reliability of the developed model for management, modeling and decision-making from the perspective of yield formation of Vicont, Premium and Ukraine-96 rice varieties as well as development of irrigation regimes for effective agricultural production were demonstrated. Adaptation of the information provided by AquaCrop on studied rice varieties allowed automatic and sufficiently accurate generation of biologically optimal irrigation regimes for Vicont, Premium and Ukraine-96. Yields and water productivity of aforementioned rice varieties were also compared in the experiment, with the highest values for both parameters achieved by Vicont – 9.5 t/ha and 1.29 kg/m3, respectively.
Słowa kluczowe
Twórcy
  • Kherson State Agrarian and Economic University, Stritenska St. 23, 73006, Kherson, Ukraine
  • Institute of Rice of NAAS, Studentska St. 11, Antonivka, Skadovsk district Kherson region, 75705, Ukraine
Bibliografia
  • 1. Vozhegova R.A. Farming systems on irrigated lands of Ukraine. 2014. Kyiv (in Ukrainian).
  • 2. Vozhegova R.A. 2019. Directions of adaptation of the crop industry to regional climate change. Climate change and agriculture. Challenges for agricultural science and education. Collection of abstracts of the II international scientific-practical conference, 6–9 (in Ukrainian).
  • 3. Schwartau V.V., Mikhalskaya L.M., Dudchenko V.V., Skidan V.O. 2019. Content of inorganic elements in rice grain depending on irrigation methods. Plant Varieties Studying and Protection, 4, 417–423 (in Ukrainian).
  • 4. Averchev O.V., Autumn A.O., Kokhorov A.A. 2017. Current state and directions of increasing the efficiency of rice production in Ukraine. Economic potential of the agricultural sector of Ukraine: scientific approaches and implementation practice. Collection of international theses. scientific-practical internet conference, 1, 8–11 (in Ukrainian).
  • 5. Markovska O.Y. 2019. Modelling productivity of crops in short crop rotation at irrigation taking into account agroecological and technological factors: monograph «Current state, challenges and prospects for research in natural sciences».
  • 6. Vozhehova R.A., Lykhovyd P.V., Kokovikhin S.V., Biliaieva I.M., Markovska O.Y., Lavrenko S.O., Rudik O.L. 2019. Artificial neural network and their implementation in agricultural science and practice: monograph, Warsaw.
  • 7. Araya A., Prasad P.V.V., Gowda P.H., Afewerk A., Abadi B., Foster A.J. 2019. Modeling irrigation and nitrogen management of wheat in northern Ethiopia. Agricultural Water Management, 216(C), 264–272.
  • 8. Steduto P., Hsiao T., Fereres E., Raes D. 2012. FAO irrigation and drainage paper by. Food and Agricul- ture Organization of the United Nations, 66, 70–85.
  • 9. García-Vila M., Fereres E., Mateos L., Orgaz F., Steduto P. 2009. Deficit irrigation optimization of cotton with AquaCrop, 101(3), 477–487.
  • 10. Steduto P., Hsiao T.C., Raes D., Fereres D. 2009. AquaCrop–The FAO Crop Modelto Simulate Yield Response to Water:I. Conceptsand Underlying Principles. Agr.Jour, 101(3), 26–37.
  • 11. Raes D., Steduto P., Hsiao T.C., Fereres E. 2012. AquaCrop Reference manual. Running AquaCrop. Book 1. Version 4.0. Chapter 1–3, 1–39.
  • 12. Surendran U., Sushanth C.M., Mammen G., Joseph E.J. 2015. Modelling the Crop Water Requirement Using FAO-CROPWAT and Assessment of Water Resources for Sustainable Water Resource Management: A Case Study in Palakkad District of Humid Tropical Kerala, India, 4, 1211–1219.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7c0188b4-95e2-4a17-91d3-73a406cea8b7
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