摘 要
信息技术的快速发展使农业大数据成为推动农业现代化和提高生产效率的关键。农业大数据覆盖了农业的全过程，特点包括实时性、多样性和大量数据。主要数据来源有生产实时数据、市场消费数据、资源环境数据和管理数据，这些数据为农业生产决策提供了全面的信息支持。农业大数据在生产决策中的应用广泛，帮助农民和企业精准指导农事、预测市场需求、优化种植管理，支持精准农业发展，提高生产效率和质量，降低成本，增强市场竞争力。但应用中也存在挑战，如数据获取难、隐私风险、数据不完整和人才缺乏。为应对这些挑战，需优化数据采集、加强数据保护、建立校验机制，并培养复合型人才。农业大数据在现代农业决策中越来越重要，通过克服挑战和优化应用，将有力支持农业现代化和可持续发展。
关键词：农业大数据；生产决策；应用研究
RESEARCH ON THE APPLICATION OF AGRICULTURAL BIG DATA IN PRODUCTION DECISION-MAKING
ABSTRACT
The rapid development of information technology makes agricultural big data become the key to promote agricultural modernization and improve production efficiency. Agricultural big data covers the whole process of agriculture, characterized by real-time, diversity and a large amount of data. The main data sources are real-time production data, market consumption data, resource and environment data and management data, which provide comprehensive information support for agricultural production decision-making. Agricultural big data is widely used in production decision-making, helping farmers and enterprises to accurately guide agriculture, predict market demand, optimize planting management, support the development of precision agriculture, improve production efficiency and quality, reduce costs, and enhance market competitiveness. But there are also challenges in applications, such as difficult data access, privacy risks, incomplete data and lack of talent. To meet these challenges, it is necessary to optimize data collection, strengthen data protection, establish a verification mechanism, and cultivate compound talents. Agricultural big data is becoming increasingly important in modern agricultural decision-making. It will overcome challenges and optimize its applications to strongly support agricultural modernization and sustainable development.
KEY WORDS：Agricultural big data; Production decision-making ;Application research
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 研究背景及意义 1
1.2 国内外研究现状 1
第2章 相关理论概述 2
2.1 农业大数据的定义 2
2.2 农业大数据的特点 2
第3章 农业大数据在生产决策中的应用 4
3.1 指导农事生产 4
3.2 预测农产品市场需求 4
3.3 优化种植管理 4
3.4 支持精准农业 4
第4章 农业大数据在生产决策应用中面临的挑战 6
4.1 数据获取困难 6
4.2 数据隐私泄露风险 6
4.3 数据不完整 6
4.4 人才短缺 6
第5章 农业大数据在生产决策应用中的应对策略 8
5.1 优化数据采集流程 8
5.2 加强数据加密 8
5.3 建立数据校验机制 8
5.4 引进外部人才 8
第6章 结论 10
参考文献 11
致 谢 12
