Author:
Shvets Yury,Morkovkin Dmitry,Chupin Alexander,Ostroumov Vladimir,Shmanev Sergey
Abstract
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.
Reference13 articles.
1. Deep learning
2. Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems
3. Paraskevov A.V., “Methods and Technical Requirements for Big Data Analytics in Agriculture,” Scientific Journal of Kubsau, 187(03) (2023)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献