Jing Ye, Jiaqing Huang

(Gansu Agricultural University)

Abstract：

The National Tea Industry Chain Big Data Project is one of the single product big data platforms approved by the Ministry of Agriculture and Rural Affairs. The goal of the project is to provide professional and authoritative data services for tea related government departments, business entities, scientific research institutions, the public, etc. It is committed to supporting scientific decision-making in the tea industry, improving the digitalization level of the tea industry, promoting the digital transformation of China's tea industry, and providing pilot experience for the construction of digital agriculture projects. The center is designed and constructed based on the principles of availability, usability, and ease of use in the tea industry. It carries out the collection, storage, and mining of tea industry data, and follows an integrated management and modular application approach in terms of functionality. It has strengthened data collection and application functions, developed rich and diverse data collection functions, and developed relatively independent data mining and modeling systems based on specific application scenarios. Through preliminary construction and debugging, we now have the ability to collect, analyze, and publish data. Consumer trend data, e-commerce data, and public opinion monitoring data have obvious auxiliary decision-making capabilities, playing a role in comprehensively grasping the operating rules of the tea industry, formulating industrial policies, and guiding scientific decision-making. This article introduces the background, significance, positioning, and construction goals of the national tea industry chain big data pilot project based on the project construction plan and actual progress; The technical roadmap, main modules, and main functions of the project were highlighted; Analyzed the main features of the project and provided an outlook on the later construction plan.

Key Words：

big data of the entire tea industry chain; data collection; data mining and decision-making; functional design; agricultural big data