文献类型： 外文期刊
作者： Yang, Guijun 1 ; Huang, Yanbo 3 ; Zhao, Chunjiang 2 ;
作者机构： 1.Beijing Res Ctr Informat Technol Agr, Key Lab Quantitat Remote Sensing Agr, Minist Agr, Beijing, Peoples R China
2.Natl Engn Res Ctr Informat Technol Agr, Beijing, Peoples R China
3.Agr Res Serv, US Dept Agr, Crop Prod Syst Res Unit, Stoneville, MS USA
关键词： Big data; Smart farming; Nitrogen requirement
期刊名称：ARTIFICIAL INTELLIGENCE IN AGRICULTURE
ISSN：
年卷期： 2020 年 4 卷
页码：
收录情况： SCI
摘要： Big data provide a pathway to lower crop nitrogen inputs from genetic breeding to field production. Moreover, multidisciplinary efforts from plant health sensing, deep machine learning and cloud computing can integrate multi-source data to form information and knowledge. So big data analysis as a prospective optimal method, will make leaps towards addressing future issues of sustainable agriculture.& COPY; 2020 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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