The concept of digitalization of agricultural production in the Russian Federation provides for the implementation of measures to develop and create a system of geographic information monitoring and decision support in crop production. The aim of the research was to conduct geoinformation monitoring of rice crops to develop methods for automated mapping of their condition and yield forecasting. The studies were carried out on a test site of the Federal State Budgetary Scientific Institution “Federal Scientific Rice Centre” with an area of 274 hectares. The survey was performed by a quadcopter with a MicaSense RedEdge-M multispectral camera mounted on a fixed suspension. The shooting period using an unmanned aerial vehicle (UAV) was limited to early June and additionally used the Sentinel-2A satellite. To assess the state of rice crops, the normalized relative vegetative index NDVI was used. Based on the NDVI distribution and yield information from the combine TUCANO 580 (CLAAS), a statistical analysis was carried out in fields 7 and 9. Testing of the experimental methodology for monitoring crops in 2019 on the basis of remote sensing of test plots and geoinformation modeling and the statistical apparatus should be considered satisfactory.
In this work, changes in the composition and properties of alluvial meadow-boggy soils are considered, with prolonged use in rice crop rotation and not involved in agricultural production - a virgin plot. The morphological differences of meadow-boggy soils of a rice field from a virgin area were revealed, which subsequently determine the properties of the soil cover of the Kuban River delta. The regularities of the interdependence of the granulometric composition of the soil, which lie in the mineralogical composition of alluvial soils and rocks, have been revealed. The tendency of an increase in soil density with an increase in the content of physical clay and silt, as well as an increase in the density of the solid phase of soils, has been established. No significant differences were found in the indices of the agrophysical properties of the subsurface horizons of soils and underlying sediments. The assessment of fertility indicators of meadow-boggy soil of a rice field and virgin analogue is given. Hydromorphic soil-forming processes have led to a significant change in the properties of alluvial deposits and soils involved in the rice crop rotation.
Селекция, семеноводство, технология возделывания и переработка сельскохозяйственных культур: материалы Международной научно-практической конференции -Краснодар: ФГБНУ «ФНЦ риса», 2021. -372 с.Предлагаемый сборник научных материалов составлен на основе представленных докладов, выступлений участников Международной научно-практической конференции «Селекция, семеноводство, технология возделывания и переработка сельскохозяйственных культур», состоявшейся в Федеральном научном центре риса (г. Краснодар) 26-27 августа 2021 года.Представленные в сборнике труды отражают результаты фундаментальных и прикладных исследований в области агропромышленного комплекса. Освещены вопросы селекции, семеноводства, генетики, биотехнологии и молекулярной биологии, защиты, технологии возделывания и переработки сельскохозяйственных культур. Большинство статей подготовлено молодыми учеными научно-исследовательских и образовательных учреждений РФ.Издание адресовано научным работникам, преподавателям, студентам, аспирантам и специалистам сельского хозяйства.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.