Foresight of Disruptive Technologies in Agricultural Engineering

Abstract

This study was the preliminary results of the "Research on Disruptive Technologies in the Agricultural Field" under the Consulting Research Project of the Chinese Academy of Engineering. Our report mainly focused on those active fields in current and future technological innovations including agricultural biotechnology, agricultural information technology and nanomaterial technology. Specifically, five critical directions were investigated in the report, consisting of animal and plant breeding, agricultural biotech medicine and bio-fertilizer, agricultural biomass engineering, intelligent agricultural technology, and non-traditional planting space. Through the analysis of conferences, patents, interviews, and literatures, the development directions of disruptive technology in the agricultural field were suggested. Hopefully, our results can provide references for the development investment of the government and enterprises as well as research directions of scientists.

Keywords

science and technology in agricultural engineering / disruptive technologies / strategy research

References

[[1]] Food and Agriculture Organization of the United Nations. World agriculture towards 2030/2050 [R]. New York: Food and Agriculture Organization of the United Nations, 2012.

[[2]] Hickey J M, Chiurugwi T, Mackay I, et al. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery [J]. Nature Genetics, 2017, 49: 1297–1303.

[[3]] Liu X, Wang Y S, Guo W J, et al. Zinc-finger nickase-mediated insertion of the lysostaphin gene into the beta-casein locus in cloned cows [J]. Nature Communications, 2013, 4(2565): 1–11.

[[4]] Wu H B, Wang Y S, Zhang Y, et al. TALE nickase-mediated SP110 knockin endows cattle with increased resistance to tuberculosis [J]. Proceedings of the National Academy of Sciences, 2015, 112(13): 1530–1539.

[[5]] Gao Y P, Wu H B, Wang Y S, et al. Single Cas9 nickase induced generation of NRAMP1 knockin cattle with reduced off target effects [J]. Genome Biology, 2017, 18(13): 1–15.

[[6]] Bogliotti Y S, Wu J, Vilarino M, et al. Efficient derivation of stable primed pluripotent embryonic stem cells from bovine blastocysts [J]. Proceedings of the National Academy of Sciences, 2018, 115(9): 2090–2095.

[[7]] 李宏伟, 王瑞军, 王志英, 等. 家畜基因组选择研究进展 [J]. 遗 传, 2017, 39(5): 377–387. Li H W, Wang R J, Wang Z Y, et al. The research progress of genomic selection in livestock [J]. Hereditas, 2017, 39(5): 377–387.

[[8]] Office of the President of the White House. Executive order of developing and promoting biobased products and bioenergy [R]. Washington DC: Office of the President of the White House, 1999.

[[9]] 石元春. 决胜生物质(第二版) [M]. 北京: 中国农业大学出版社, 2013. Shi Y C. Biomass: To win the future (Second edition) [M]. Beijing: China Agricultural University Press, 2013.

[[10]] 中国工程院. 我国交通运输用生物燃料产业关键技术开发、示 范与应用研究报告 [R]. 北京: 中国工程院, 2014. Chinese Academy of Engineering. Report on key technologies development, demonstration and application of biofuels industry for transportation in China [R]. Beijing: Chinese Academy of Engineering, 2014.

[[11]] World Bioenergy Association. World biomass energy statistics report 2014 [R]. New York: World Bioenergy Association, 2014.

[[12]] 中华人民共和国农业部. “ 十三五” 全国农业农村信息化发展 规划 [R]. 北京: 中华人民共和国农业部, 2016. Ministry of Agriculture of the PRC. National agricultural and rural informatization development plan for the “13th Five-Year” period [R]. Beijing: Ministry of Agriculture of the PRC, 2016.

[[13]] 李道亮, 杨昊. 农业物联网技术研究进展与发展趋势分析 [J]. 农 业机械学报, 2018, 49(1): 1–20. Li D L, Yang H. State-of-the-art review for Internet of things in agriculture [J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(1): 1–20.

[[14]] 段青玲, 刘怡然, 张璐, 等. 水产养殖大数据技术研究进展与发 展趋势分析 [J]. 农业机械学报, 2018, 49(6): 1–16. Duan Q L, Liu Y R, Zhang L, et al. State-of-the-art review for application of big data technology in aquaculture [J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(6): 1–16.

[[15]] 赵春江. 人工智能引领农业迈入崭新时代 [J]. 中国农村科技, 2018 (1): 29–31. Zhao C J. Artificial intelligence leads agriculture into a new era [J]. China Rural Science & Technology, 2018 (1): 29–31.

[[16]] 李道亮. 农业4.0——即将来临的智能农业时代 [M]. 北京: 机械 工业出版社, 2018. Li D L. Agriculture 4.0—The coming era of intelligent agriculture [M]. Beijing: Machinery Industry Press, 2018.

[[17]] 李家洋. “ 跨越2030” 农业科技发展战略 [M]. 北京: 中国农业科 学技术出版社, 2016. Li J Y. “Spanning 2030” agricultural science and technology development strategy [M]. Beijing: China Agricultural Science and Technology Publishing House, 2016.

[[18]] 高宁, 华晨, 朱胜萱, 等. 农业城市主义策略体系初探——浅析 荷兰《鹿特丹城市农业空间》研究 [J]. 国际城市规划, 2013, 28 (1): 74–79. Gao N, Hua C, Zhu S X, et al. A preliminary study on the strategic system of agricultural urbanism—Brief analysis of the study of Rotterdam Urban Agricultural Space in the Netherlands [J]. Urban Planning International, 2013, 28 (1): 74–79.

[[19]] Neena M, Elizabeth A W, Karl E R, et al. Clay nanosheets for topical delivery of RNAi for sustained protection against plant viruses [J]. Nature Plants, 2017, 3: 16207.

[[20]] James A B, Thierry B, William C, et al. Control of coleopteran insect pests through RNA interference [J]. Nature Biotechnology, 2007, 25: 1322–1326.

[[21]] Yi Z F, Hashmath I H, Feng C F, et al. Functionalized mesoporous silica nanoparticles with redox responsive short-chain gatekeepers for agrochemical delivery [J]. ACS Applied Materials and Interfaces, 2015, 7: 9937–9946.

[[22]] Si L, Xu H, Zhou X, et al. Generation of influenza A viruses as live but replication-incompetent virus vaccines [J]. Science, 2016, 354(6316): 1170–1173.

[[23]] Xu L, Xiang J, Liu Y, et al. Functionalized graphene oxide serves as a novel vaccine nano-adjuvant for robust stimulation of cellular immunity [J]. Nanoscale, 2016, 8(6): 3785–3795.

[[24]] Peleteiro M, Presas E, González-Aramundiz J V, et al. Polymeric nanocapsules for vaccine delivery: Influence of the polymeric shell on the interaction with the immune system [J]. Frontiers in Immunology, 2018, 9: 791–799.

[[25]] Peiffer J A, Spor A, Koren O, et al. Diversity and heritability of the maize rhizosphere microbiome under field conditions [J]. Proceedings of the National Academy of Sciences, 2013, 110: 6548– 6553.

[[26]] Edwards J, Johnson C, Santos-Medellín C, et al. Structure, variation, and assembly of the root-associated microbiomes of rice [J]. Proceedings of the National Academy of Sciences, 2015, 112: 911–920.

[[27]] Pieterse C M, de Jonge R, Berendsen R L. The soil-borne supremacy [J]. Trends in Plant Science, 2016, 21: 171–173.

[[28]] Hu L, Ren W, Tang J, et al. The productivity of traditional rice– fish co-culture can be increased without increasing nitrogen loss to the environment [J]. Agriculture Ecosystems & Environment, 2013, 177(2): 28–34.

[[29]] Andrew J R , Jeffrrey M L. Comparing salinities of 10, 20, and 30‰ in minimal-exchange, intensive shrimp (Litopenaeus vannamei) cultrue systems [J]. Aquaculture, 2017, 476(1): 29–36.

[[30]] Yan B, Wang X, Cao M. Effects of salinity and temperature on survival, growth, and energy budget of juvenile Litopenaeus vannamei [J]. Journal of Shellfish Research, 2007, 26(4): 141–146.

Funding

CAE Advisory Project “Strategic Research on Disruptive Technologies for Engineering Science and Technology” (2017-ZD-10)