Li Dongpo, Nanseki Teruaki, Chomei Yosuke, Kuang Jinsong
Key Laboratory of Digital Economy and High-Quality Development, School of Economics and Trade, Hunan University of Technology and Business, Changsha, China.
Faculty of Agriculture, Kyushu University, Fukuoka, Japan.
J Sci Food Agric. 2023 Mar 15;103(4):1609-1620. doi: 10.1002/jsfa.12204. Epub 2022 Sep 21.
Japanese farms currently occur on a small but expanding average physical scale and annual sales, in a decreasing and aging labor force, increasingly abandoned farmland and massive access of corporations powerful in capital and management. The government has proposed to accelerate agricultural growth through adopting high-level smart technologies in large-scale farms, with a series of favorite policies and measures. This paper reviews the connotations, characteristics and technologies of smart agriculture in the views of Japanese scholars, the practice of smart agriculture in Japan, followed by a case study on the smart rice production model 'NoshoNavi1000'. The results show that Japanese scholars have conducted in-depth and massive studies in smart agriculture, with regional characteristics in the orientations on labor-saving, precise management, disaster reduction and inheriting traditional farming skills. The government's ambitious objective is supported by its all-round policy package, including project demonstration, supporting services, environmental improvement, education and training, and overseas outreaching. Closely combined with the planting structure of Japanese agriculture, rice production is an important sector for the R&D and application of smart farming in the form of either individual technologies or models. The policies and technologies have achieved benefits in saving labor and production costs, and improving the profit margin. Through years of on-farm application, 'NoshoNavi1000' has been developed to involve the major technological components of smart agriculture. It has contributed to improving rice yield, production efficiency and profitability of large-scale farms, through real-time data collection, comprehensive and professional data mining, and specific and practical feedbacks. © 2022 Society of Chemical Industry.
目前,日本农场的平均实际规模较小,但在不断扩大,年销售额也在增长,然而劳动力却在减少且日益老龄化,农田被弃耕的情况越来越多,资本和管理实力强大的企业大量进入农业领域。政府提议通过在大型农场采用高水平智能技术,并出台一系列优惠政策和措施来加速农业发展。本文从日本学者的视角回顾了智慧农业的内涵、特点和技术,介绍了日本智慧农业的实践,随后以智慧水稻生产模式“农书导航1000”为例进行了研究。结果表明,日本学者对智慧农业进行了深入且大量的研究,在省力化、精准管理、减灾以及传承传统农耕技能等方面呈现出地域特色。政府的宏伟目标得到了全方位政策组合的支持,这些政策包括项目示范、支持服务、环境改善、教育培训以及海外拓展。紧密结合日本农业的种植结构,水稻生产无论是作为单项技术还是模式,都是智慧农业研发与应用的重要领域。这些政策和技术在节省劳动力和生产成本、提高利润率方面取得了成效。经过多年的田间应用,“农书导航1000”已发展成为涵盖智慧农业主要技术要素的模式。它通过实时数据收集、全面且专业的数据挖掘以及具体实用的反馈,为提高大规模农场的水稻产量、生产效率和盈利能力做出了贡献。© 2022化学工业协会。