| Issue |
E3S Web Conf.
Volume 480, 2024
II International Scientific and Practical Conference “Energy, Ecology and Technology in Agriculture” (EEA2023)
|
|
|---|---|---|
| Article Number | 03023 | |
| Number of page(s) | 10 | |
| Section | Agriculture, Engineering and Technology in the Agro-Industrial Complex | |
| DOI | https://doi.org/10.1051/e3sconf/202448003023 | |
| Published online | 18 January 2024 | |
Big data and analytics for crop yield forecasting: Empirical research and development prospects
1 V.A. Trapeznikov Institute of Control Sciences if Russian Academy of Science, 65, Profsoyuznaya str., Moscow, 117997, Russian Federation
2 Financial University under the Government of the Russian Federation, 49/2, Leningradsky avenue, Moscow, 125167, Russian Federation
3 RUDN University, 6, Miklukho-Maklaya str., Moscow, 117198, Russian Federation
* Corresponding author: morkovkinde@mail.ru
The study provides a comprehensive analysis of the role and prospects of applying big data technologies in agriculture. It covers a wide range of issues related to the implementation and use of Big Data in the agro-industrial sector, exploring both the theoretical foundations and practical aspects of their application. Special attention is given to the examination of current trends, identification of key challenges, and opportunities associated with the use of these technologies in agriculture. The authors investigate how big data technologies are transforming approaches to managing agrarian processes, improving crop yields, and optimizing resources. Various aspects are analyzed, including the development of data processing technologies, their application for analysis and forecasting in agriculture, and discussions on issues related to the adoption and dissemination of these technologies in the Russian context. Specific examples of successful projects and initiatives demonstrating the potential of Big Data in agribusiness are presented.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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