Journal Home Online First Current Issue Archive For Authors Journal Information 中文版

Strategic Study of CAE >> 2021, Volume 23, Issue 4 doi: 10.15302/J-SSCAE-2021.04.001

Development Strategy of Smart Agriculture for 2035 in China

1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;

2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
 

Funding project:中国工程院咨询项目“智慧农业发展战略研究” (2019-ZD-05) Received: 2021-04-21 Revised: 2021-06-21 Available online: 2021-07-26

Next Previous

Abstract

Smart agriculture is an important component of high-quality agricultural development and the overall rural revitalization in China. Research on smart agriculture strategy is significant for developing a medium- and long-term scientific and technological layout and clarifying the development ideas and direction of smart agriculture in China. Against the background of rural revitalization, this study summarizes the macro demand of high-quality agricultural development for smart agricultural science and technologies; it also analyzes the strategic conception, strategic tasks, and development route of China’s smart agriculture development toward 2035. Conclusions show that developing smart agriculture helps address the low quality and efficiency and weak competitiveness of China’s agriculture sector. Furthermore, to achieve the replacements of human power with machines and human brains with computers, and promote the independent technological competitiveness of China’s agricultural sector, an industrial technology system for the smart agriculture that integrates biotechnology, information technology, and intelligent equipment should be established; and smart agriculture should be promoted in a staged manner considering different business entities and industrial needs. Specifically, China should strengthen the top-level design, promote technological research, establish a differentiated subsidy mechanism, integrate industry and village, and encourage applied talent training.

Figures

Fig. 1

Fig. 2

Fig. 3

References

[ 1 ] 孙康泰, 王小龙, 蒋大伟, 等. 美国农业和食品领域2030科技突 破计划及启示 [J]. 全球科技经济瞭望, 2020, 35(11): 25–32. Sun K T, Wang X L, Jiang D W, et, al. The 2030 plan of science and technology breakthrough on agricultural and food study in the United States and its enlightenment [J]. Global Science,Technology and Economy Outlook, 2020, 35(11): 25–32. link1

[ 2 ] 赵春江. 智慧农业发展现状及战略目标研究 [J]. 智慧农业, 2019, 1(1): 1–7. Zhao C J. State-of-the-art and recommended development strategic objectives of smart agriculture [J]. Smart Agriculture, 2019, 1(1): 1–7. link1

[ 3 ] 赵春江, 杨信廷, 李斌, 等. 中国农业信息技术发展回顾及展望 [J]. 农学学报, 2018, 8(1): 180–186. Zhao C J, Yang X T, Li B, et al. The retrospect and prospect of agricultural information technology in China [J]. Journal of Agriculture, 2018, 8(1): 180–186. link1

[ 4 ] 李道亮. 面向需求协同推进我国智慧农业发展 [J]. 国家治理, 2020 (19): 18–21. Li D L. Promoting the development of China’s smart agriculture in the face of demand [J]. Governance, 2020 (19): 18–21. link1

[ 5 ] 许世卫, 王东杰, 李哲敏. 大数据推动农业现代化应用研究 [J]. 中国农业科学, 2015, 48(17): 3429–3438. Xu S W, Wang D J, Li Z M. Application research on big data promote agricultural modernization [J]. Scientia Agricultura Sinica, 2015, 48(17): 3429–3438. link1

[ 6 ] 杨印生, 薛春序, 许莹, 等. 智慧农业的社会经济特征、发展逻辑 与系统阐释 [J]. 吉林农业大学学报, 2021, 43(2): 146–152. Yang Y S, Xue C X, Xu Y, et al. Social and economic characteristics, development logic and systematic interpretation of smart agriculture [J]. Journal of Jilin Agricultural University, 2021, 43(2): 146–152. link1

[ 7 ] 于海业, 李晓凯, 于跃, 等. 光谱技术在农作物信息感知中的应 用研究进展 [J]. 吉林农业大学学报, 2021, 43(2): 153–162. Yu H Y, Li X K, Yu Y, et al. Research progress in the application of spectral technology in crop information perception [J]. Journal of Jilin Agricultural University, 2021, 43(2): 153–162. link1

[ 8 ] 宋洪远. 智慧农业发展的状况、面临的问题及对策建议 [J].人民 论坛·学术前沿, 2020 (24): 62–69. Song H Y. The status and problems of smart agriculture development and responses [J]. People’s Tribune·Academic Frontier, 2020 (24): 62–69. link1

[ 9 ] 吴志峰, 骆剑承, 孙营伟, 等. 时空协同的精准农业遥感研究 [J]. 地球信息科学学报, 2020, 22(4): 731–742. Wu Z F, Luo J C, Sun Y W, et al. Research on precision agricultural based on the spatial-temporal remote sensing collaboration [J]. Journal of Geo-information Science, 2020, 22(4): 731–742. link1

[10] Zhu X K, Hu R F, Zhang C, et al. Does Internet use improve technical efficiency? Evidence from apple production in China [J]. Technological Forecasting and Social Change, 2021, 166: 1–11. link1

[11] Park D H, Kang B J, Cho K R, et al. A study on greenhouse smart farm system based on wireless sensor [J]. Wireless Personal Communications, 2011, 56: 117–130.

[12] Sravani V, Santhosh K V, Bhargava S, et al. Design and implementation of a smart controller in agriculture for improved productivity [J]. Journal of Electrical and Electronics Engineering, 2018, 18(1): 45–51. link1

[13] Robertson M J, Llewellyn R S, Mandel R, et al. Adoption of variable rate fertiliser application in the Australian grains industry: Status, issues and prospects [J]. Precision Agriculture, 2012, 13(2): 181–199. link1

[14] 王亚华. 立足国情农情走出中国特色乡村振兴之路 [J].中国农 业资源与区划, 2020, 41(9): 1–8. Wang Y H. Road to rural revitalization with Chinese characteristics based on China’s agricultural conditions [J]. Chinese Journal of Agricultural Resources and Regional Planning, 2020, 41(9): 1–8. link1

[15] Wei H K, Han L. Prospects of China’s agricultural development [J]. China Economist, 2016, 11(4): 46–67. link1

[16] 孙传恒, 于华竟, 徐大明, 等. 农产品供应链区块链追溯技术研 究进展与展望 [J]. 农业机械学报, 2021, 52(1): 1–13. Sun C H, Yu H J, Xu D M, et al. Review and prospect of agri-products supply chain traceability based on blockchain technology [J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(1): 1–13. link1

[17] 余东华. “十四五”期间我国未来产业的培育与发展研究 [J]. 天 津社会科学, 2020, 3(3): 12–22. Yu D H. The cultivation and development of China’s future industries during the 14th Five-Year Plan [J]. Tianjin Social Sciences, 2020, 3(3): 12–22. link1

Related Research