Digital solutions for agricultural business processes: challenges in organizing neural network-based diagnostics of grain crop plantings

Issue № 1, 2024, article № 3, pages 26-33

Section: Digitalization in agrarian and industrial complex

Language: Russian

Original language title: ЦИФРОВЫЕ РЕШЕНИЯ БИЗНЕС-ПРОЦЕССОВ АПК: ПРОБЛЕМЫ ОРГАНИЗАЦИИ НЕЙРОСЕТЕВОЙ ДИАГНОСТИКИ ПОСЕВОВ ЗЕРНОВЫХ КУЛЬТУР

Keywords: DIGITAL SOLUTIONS, DIGITIZATION, BUSINESS PROCESS, ARTIFICIAL INTELLIGENCE, INTELLIGENT SYSTEM, GRAIN PRODUCTION, CROP DIAGNOSTICS

Abstract: The paper delves into pertinent issues related to the integration and application of digital intelligent solutions in the operational aspects of agricultural production, with a particular focus on their utilization in diagnosing diseases within grain crop plantings. The article's core objective centers on the analysis of challenges associated with orchestrating intelligent diagnostics within the grain complex's activities. To uncover these intricacies, a project management system has been introduced to outline the progressive sequence from preparing IT solutions to their effective implementation in the production cycle. This systematic approach facilitates the identification of primary barriers within the business process of agricultural crop diagnostics, grouping them into functional blocks: data management, infrastructure development, framework and platform utilization, human resources, and regulatory requisites. Given the predominance of conventional diagnostic practices, the article presents a conceptual operational foundation for neural network-based diagnosis of grain crop plantings. This foundation is structured across three hierarchical tiers: individual, regional, and federal. Each level tackles specific tasks within its purview, aimed at enriching databases, thereby adapting analytical systems and decision-making processes to ensure maximum relevance and precision. The proposed framework could serve as a foundational model for developing a comprehensive methodology for well-founded managerial decisions in grain production within the evolving context of digital agriculture. The conceptual strategies for forming an organizational strategy for intelligent diagnostics, as presented in the article, have been meticulously developed, taking into account established decisions driving the development of the digital economy within the agricultural sector.

Authors: Arinichev Igor Vladimirovich, Sidorov Viktor Aleksandrovich