耦合视角下生产性服务业与智慧农业发展的研究——基于美国的经验与启示

为了推进农业生产性服务业与智慧农业的耦合,进而为我国小农户衔接智慧农业提供桥梁。本文选取美国为典型案例,分析美国生产性服务业与智慧农业耦合发展的模式和措施。采用比较研究法,归纳中美生产性服务业与智慧农业耦合发展的异同。研究表明,美国生产性服务业与智慧农业发展具有服务耦合、产业耦合和利益耦合三种模式,美国为推进其耦合发展而采取了立法保障、信息化建设、农业大数据利用和高素质人才培养等一系列措施。中美两国在智慧农业的高门槛、农业人口流失与老龄化问题、突发性公共卫生危机等方面存在共同点。但与美国相比,中国的生产性服务业与智慧农业之间的关系尚处于并行分离的状态,存在耦合层次较低,创新驱动力不足等问题。因此,为推动生产性服务业与智慧农业耦合发展,提出健全相关配套支持机制、加强大数据平台建设和信息化技术研发、完善农业产业链条和加强专业性人才的培养力度等对策建议。

The development of production services and smart agriculture from the perspective of coupling: Experiences and implications from the case of the United States

To promote the coupling of agricultural production services and smart agriculture, and to provide a bridge for small-scale farms to connect smart agriculture in China, this paper analyzed the coupling development modes and measures of production services and smart agriculture in the United States and discussed its implications for China. In addition, by the comparative research method, this paper summarized the similarities and differences of the coupling development of production services and smart agriculture between China and the United States. Results show that the development of production services and smart agriculture in the United States has three modes: service coupling, industry coupling and benefit coupling. A series of measures taken by the United States to promote its coupling development include legislative guarantee, information construction, agricultural big data utilization and high-quality talent training. Smart agriculture in China and the United States are both facing high threshold, loss and aging of agricultural population, and unexpected public health crisis. However, compared with the United States, the relationship between production services and smart agriculture in China is still in a state of parallel separation, with low coupling level and insufficient innovation driving forces. Therefore, to promote the coupling development of production services and smart agriculture, this paper suggests that China should improve related supporting mechanism, strengthen the construction of big data platforms and information technology research and development, improve the agricultural industry chain, and enhance the training of professional talents.