农业大数据分析的应用实践、理论逻辑与优化路径研究

Research on Practical Applications, Theoretical Logic and Optimization Strategies for Agricultural Big Data Analysis

摘要: 在数字乡村建设与农业现代化转型的双重战略背景下，大数据作为核心数字生产要素，已成为破解传统农业发展痛点、提升农业全产业链运行效率的核心支撑。本文以信息不对称理论、全面风险管理理论、规模经济理论与数字经济理论为核心，构建农业大数据应用的理论分析框架，系统梳理农业大数据在生产管控、流通匹配、风险管理、公共管理四大核心场景的应用逻辑，基于2021~2025年行业统计数据与1855份农业经营主体调研样本，通过量化模型实证分析农业大数据的应用成效，深入剖析当前应用过程中存在的数据壁垒突出、场景适配不足、基层应用能力薄弱、安全体系不健全等现实问题，并结合核心理论提出针对性优化路径。研究旨在为农业大数据的深度落地应用提供理论参考与实践指引，助力农业高质量发展与乡村振兴战略全面实施。

Abstract: Against the dual strategic backdrop of digital rural development and agricultural modernization, big data—as a core digital production factor—has become pivotal in addressing challenges in traditional agriculture and enhancing operational efficiency across the entire agricultural value chain. This study establishes a theoretical analytical framework for agricultural big data applications, grounded in information asymmetry theory, comprehensive risk management theory, economies of scale theory, and digital economy theory. It systematically examines the application logic of agricultural big data across four key scenarios: production management, supply chain coordination, risk mitigation, and public administration. Leveraging industry statistics from 2021~2025 and a survey sample of 1,855 agricultural operators, the study employs quantitative models to empirically evaluate the effectiveness of big data applications. It identifies pressing challenges—including prominent data barriers, inadequate scenario adaptation, limited grassroots implementation capabilities, and incomplete security systems—and proposes targeted optimization strategies based on core theories. The research aims to provide theoretical insights and practical guidance for the comprehensive deployment of agricultural big data, thereby supporting high-quality agricultural development and the full implementation of the rural revitalization strategy.