Identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural production
As the main hypothesis, it is suggested that the existing unevenness in the number of precision farming elements used in agriculture in the subjects of the Russian Federation is related to regional characteristics and specific features of the agricultural sector of the regional economy. The purpose...
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2020-01-01
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doaj-7211e92777cc4efdb278c0939b16dc312021-04-02T18:46:42ZengEDP SciencesE3S Web of Conferences2267-12422020-01-012220502310.1051/e3sconf/202022205023e3sconf_daic2020_05023Identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural productionGusev A.S.0Skvortsov E.A.1Vashukevich N.V.2Ural State Agrarian University, Department of Land ManagementUral State Economic University Ekaterinburg, Department of Competition Law and Antimonopoly RegulationUral State Agrarian University, Department of Land ManagementAs the main hypothesis, it is suggested that the existing unevenness in the number of precision farming elements used in agriculture in the subjects of the Russian Federation is related to regional characteristics and specific features of the agricultural sector of the regional economy. The purpose of the study is to identify the geographical features of the regions that are most preferable for the use of precision farming technology in agricultural production. Mathematical modeling uses data from 20 subjects of the Russian Federation on the dynamics of the introduction and use of precision farming elements and the characteristics of these regions for 14 different indicators that can in one way or another affect the introduction of these technologies. Multiple correlation was obtained using 5 characteristics of regions (the correlation coefficient was r=0.89±0.1). At the same time, two indicators (the change in the level of registered unemployment and the amount of subsidies per 1 ha of agricultural land) were inversely dependent on the result of the introduction of precision farming elements. The selected indicators determined the intensity of introduction of precision farming elements in the regions by almost 80% (the coefficient of determination was D=0.798). The identification of these features and the construction of an appropriate model allows to predict the most preferred regions for the use of precision farming elements in agricultural production based on the generalization of existing experience.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/82/e3sconf_daic2020_05023.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gusev A.S. Skvortsov E.A. Vashukevich N.V. |
spellingShingle |
Gusev A.S. Skvortsov E.A. Vashukevich N.V. Identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural production E3S Web of Conferences |
author_facet |
Gusev A.S. Skvortsov E.A. Vashukevich N.V. |
author_sort |
Gusev A.S. |
title |
Identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural production |
title_short |
Identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural production |
title_full |
Identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural production |
title_fullStr |
Identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural production |
title_full_unstemmed |
Identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural production |
title_sort |
identification of the features of the regions that are most preferable for the use of precision farming technologies in agricultural production |
publisher |
EDP Sciences |
series |
E3S Web of Conferences |
issn |
2267-1242 |
publishDate |
2020-01-01 |
description |
As the main hypothesis, it is suggested that the existing unevenness in the number of precision farming elements used in agriculture in the subjects of the Russian Federation is related to regional characteristics and specific features of the agricultural sector of the regional economy. The purpose of the study is to identify the geographical features of the regions that are most preferable for the use of precision farming technology in agricultural production. Mathematical modeling uses data from 20 subjects of the Russian Federation on the dynamics of the introduction and use of precision farming elements and the characteristics of these regions for 14 different indicators that can in one way or another affect the introduction of these technologies. Multiple correlation was obtained using 5 characteristics of regions (the correlation coefficient was r=0.89±0.1). At the same time, two indicators (the change in the level of registered unemployment and the amount of subsidies per 1 ha of agricultural land) were inversely dependent on the result of the introduction of precision farming elements. The selected indicators determined the intensity of introduction of precision farming elements in the regions by almost 80% (the coefficient of determination was D=0.798). The identification of these features and the construction of an appropriate model allows to predict the most preferred regions for the use of precision farming elements in agricultural production based on the generalization of existing experience. |
url |
https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/82/e3sconf_daic2020_05023.pdf |
work_keys_str_mv |
AT gusevas identificationofthefeaturesoftheregionsthataremostpreferablefortheuseofprecisionfarmingtechnologiesinagriculturalproduction AT skvortsovea identificationofthefeaturesoftheregionsthataremostpreferablefortheuseofprecisionfarmingtechnologiesinagriculturalproduction AT vashukevichnv identificationofthefeaturesoftheregionsthataremostpreferablefortheuseofprecisionfarmingtechnologiesinagriculturalproduction |
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