| Issue |
BIO Web Conf.
Volume 108, 2024
International Scientific and Practical Conference “From Modernization to Rapid Development: Ensuring Competitiveness and Scientific Leadership of the Agro-Industrial Complex” (IDSISA 2024)
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|
|---|---|---|
| Article Number | 06002 | |
| Number of page(s) | 6 | |
| Section | Intelligent Technologies in Crop Production | |
| DOI | https://doi.org/10.1051/bioconf/202410806002 | |
| Published online | 15 May 2024 | |
Superfrontiers of Crop Production: Artificial Intelligence in Formation the Grain Production Ecosystem
1 Federal State Budgetary Educational Institution of Higher Education «Kuban State University», Krasnodar, 149, Stavropolskaya st., 350040, Krasnodar, Russia
2 Federal State Budgetary Educational Institution of Higher Education «Kuban State Agrarian University named after I.T. Trubilin», 13, Kalinina st., 350044, Krasnodar, Russia
* Corresponding author: iarinichev@gmail.com
The paper presents a study dedicated to analyzing the role of crop production superfrontiers in forming the agricultural production ecosystem, with a focus on the grain sector. Special attention is given to the superfrontier - data intelligence analytics as an effective tool for optimizing grain production. The authors consider specific examples of successful integration of intelligent analytical methods into practice, identifying their positive impact on improving production efficiency, including cost reduction and business process management enhancement. Among the main barriers to the implementation and use of intelligent technologies and systems, the lack of a unified methodology for collecting and preparing data for training and configuring intelligent grain production systems as a whole is noted. It is shown that artificial intelligence forms the basis of modern monitoring systems, permeating the ecosystem at all levels (supply, production, sales). Considering these features, the article presents a fundamental scheme for organizing the grain production ecosystem.
© 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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