State and development prospects of the agricultural tractor fleet in the context of digital transformation of agriculture

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Abstract

BACKGROUND: The digital transformation of various sectors of the national economy including agriculture is one of the main tasks of economic development. The implementation of digital technologies in production processes helps to improve the technical and economic indicators of production by ensuring the timely adoption of optimal management decisions, increasing labor productivity, and reducing the impact of the human factor on production. To ensure the digital transformation of agricultural production, first of all, it is necessary to assess the state of machinery and technology provision for agriculture, in particular, the tractor fleet, in terms of the level of equipment readiness for being equipped with digital systems and the availability of standard technical solutions for equipment adaptation to digital agriculture.

AIMS: Determination the expected values of indicators of the level of technical and technological state of agricultural production by developing a forecast for the development of the agricultural tractor fleet and the level of provision with these types of equipment for the period up to 2030 taking into account current trends.

METHODS: For the tractor fleet state assessment, the data taken from specialized databases on the tractor fleet and the area of arable land retired from active agricultural circulation, statistical materials of the Rosstat and Avtoselkhozmash-Holding organizations were used. Statistical extrapolation methods implemented in the Microsoft Excel environment were used to predict the development of the tractor fleet.

RESULTS: The forecast for the tractor fleet development was made according to two scenarios: pessimistic and optimistic, taking into account the use of digital technologies.

CONCLUSIONS: The development forecast made it possible to assess the state of the tractor fleet by 2030 according to various scenarios.

About the authors

Ivan A. Starostin

Federal Scientific Agroengineering Center VIM

Email: starwan@yandex.ru
ORCID iD: 0000-0002-8890-1107

Cand. Sci. (Tech.), Head of the of the Forecasting the Development of Machine Systems and Technologies in Agro-Industrial Sector Laboratory

Russian Federation, Moscow

Aleksandr V. Lavrov

Federal Scientific Agroengineering Center VIM

Author for correspondence.
Email: vimlavrov@mail.ru
ORCID iD: 0000-0002-9070-206X
SPIN-code: 3198-2929

Cand. Sci. (Tech.), Head of the of the Forecasting the Development of Machine Systems and Technologies in Agro-Industrial Sector Laboratory

Russian Federation, Moscow

Aleksandr V. Eshchin

Federal Scientific Agroengineering Center VIM

Email: eschin-vim@yandex.ru
ORCID iD: 0000-0002-9368-7758

Cand. Sci. (Tech.), Senior Researcher of the Forecasting the Development of Machine Systems and Technologies in Agro-Industrial Sector Laboratory

Russian Federation, Moscow

Svetlana A. Davydova

Federal Scientific Agroengineering Center VIM

Email: davidova-sa@mail.ru
ORCID iD: 0000-0002-1219-3335
SPIN-code: 1050-6034

Cand. Sci. (Tech.), Leading Researcher of the Forecasting the Development of Machine Systems and Technologies in Agro-Industrial Sector Laboratory

Russian Federation, Moscow

References

  1. Zabaznova DO. Digital technologies in accounting and control of agricultural holdings. Ekonomika i upravlenie: problemy, resheniya. 2020;3(2):94–104. (In Russ).
  2. Tarasov VI. Digitalization as the next stage of informatization of small and medium-sized businesses in the agrarian sector of Russia and China. Ekonomika i biznes: teoriya i praktika. 2021;4–2(74):185–189. (In Russ).
  3. Rasporyazhenie Pravitelstva Rossiyskoy Federatsii ot 8 sentyabrya 2022 goda № 2567-r. Strategiya razvitiya agropromyshlennogo i rybokhozyaystvennogo kompleksov Rossiyskoy Federatsii na period do 2030 goda. (In Russ). Accessed: 03.04.2023. Available from: http://static.government.ru/media/files/G3hzRyrGPbmFAfBFgmEhxTrec694MaHp.pdf
  4. Truflyak EV, Kurchenko NYu, Kreimer AS. Monitoring of the scientific and technological development of the agro-industrial complex in the field of precision agriculture. Krasnodar: KubGAU; 2021. (In Russ).
  5. Oborin MS. Digital innovative technologies in agriculture. Agrarnyy vestnik Urala. 2022;05(220):82–92. (In Russ).
  6. Buraeva EV. Digitalization of agriculture as a determinant of economic growth in the agricultural sector of the economy. Vestnik agrarnoy nauki. 2020;2(83):99–107. (In Russ).
  7. Fedorenko VF, Chernoivanov VI, Goltyapin VYa, et al. Global trends in the intellectualization of agriculture: scientific. analyte review. Moscow: Rosinformagrotekh; 2018. (In Russ).
  8. Shevtsov VG, Lavrov AV. Database “Quantitative-age composition of agricultural organizations of the Russian Federation by years (for the period from 1990 to 2009)”. In: Resource-saving technologies and technical support of grain production: Sat. report International scientific-technical conf. Moscow: VIM; 2010:392–397. (In Russ).
  9. Shevtsov VG, Lavrov AV. Formation of quantitative and age composition of tractor fleet in conditions of unprofitable agricultural production. Tractors and Agricultural Machinery. 2012;79(3):3–6. (In Russ). doi: 10.17816/0321-4443-69322
  10. Federal State Statistics Service. Agriculture, hunting and forestry. (In Russ). Accessed: 03.04.2023. Available from: https://rosstat.gov.ru/enterprise_economy
  11. Starostin IA, Zagoruiko MG. The material and technical base of agriculture: the availability of tractors and the state of the tractor industry. Agrarnyy nauchnyy zhurnal. 2020;10:136–130. (In Russ).
  12. National report on the progress and results of the implementation in 2021 of the State Program for the Development of Agriculture and the Regulation of Agricultural Products, Raw Materials and Food Markets. Moscow: Ministry of Agriculture of the Russian Federation; 2022. (In Russ). Accessed: 03.04.2023. Available from: https://mcx.gov.ru/upload/iblock/60d/60d8f2347d3eb724ab9b57c61a9ac269.pdf
  13. Rosstat. Agriculture, hunting and game management, forestry in Russia. 2015. Statistical compendium. Moscow: Rosstat; 2015. (In Russ). Accessed: 03.04.2023. Available from: https://rosstat.gov.ru/storage/mediabank/selhoz15.pdf
  14. Rosstat. Agriculture in Russia. 2019. Statistical compendium. Moscow: Rosstat; 2015. (In Russ). Accessed: 03.04.2023. Available from: https://rosstat.gov.ru/storage/mediabank/sh_2019.pdf
  15. Rosstat. Agriculture in Russia. 2021. Statistical compendium. Moscow: Rosstat; 2015. (In Russ). Accessed: 03.04.2023. Available from: https://rosstat.gov.ru/storage/mediabank/S-X_2021.pdf

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2. Fig. 1. Forecast of changes in the quantitative composition of the agricultural tractor fleet.

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3. Fig. 2. Forecast of changes in the provision with agricultural tractors.

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4. Fig. 3. Target volumes of agricultural tractors purchasing by years for the implementation of the optimistic scenario.

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