摘要
集成自动化平台装备和信息化技术手段,获取多尺度、多生境、多源异构的作物表型组大数据,将极大地促进作物功能基因组学、数字育种、智慧栽培的研究进程。本文分析了作物表型组大数据技术及装备的应用需求、产业发展形势,从物理、传输、数据、知识、应用5个层面详细梳理了相应研发现状;从作物表型组大数据高通量获取、作物表型组大数据智能解析技术两方面着手,剖析了我国相关技术、装备、产业应用方面的问题和态势。研究建议,从底层芯片层面突破作物表型传感器关键技术,在可控开源的基础上形成自主化的表型解析技术体系,加强作物表型组大数据技术及装备标准体系建设,提出基因–表型–环境多维大数据驱动的数字育种和智慧栽培创新模式,建设作物表型组大数据技术及装备人才队伍和协作网络。
Automatic equipment and information technologies make it possible to acquire multi-scale and multi-source heterogeneous data of crops under different growth conditions,forming big data on crop phenomics.This will greatly promote the research progress of crop functional genomics,digital breeding,and smart cultivation.In this paper,the demand for and industrial development of technology and equipment of big data on crop phenomics are analyzed.Then,the current situation of research and development in this area is summarized from five aspects:data acquisition hardware,data transmission,data analysis,knowledge formation,and applications.The problems and developmental trends of relevant technologies,equipment,and industrial application in China are analyzed from the perspectives of high-throughput acquisition and intelligent analysis of big data on crop phenomics.At last,the following suggestions are proposed:achieving breakthroughs regarding key crop phenotyping sensor technologies from the underlying chip level,forming an autonomous phenotyping extraction technology system on the basis of controllable open source,strengthening the standards system construction for big data on crop phenomics,creating a new model of genotype‒phenotype‒environment big data-driven digital breeding and smart cultivation,and building a talent pool and collaborative network for crop phenomics.
作者
温维亮
郭新宇
张颖
顾生浩
赵春江
Wen Weiliang;Guo Xinyu;Zhang Ying;Gu Shenghao;Zhao Chunjiang(Information Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;National Engineering Research Center for Information Technology in Agriculture,Beijing 100097,China;Beijing Key Laboratory of Digital Plant,Beijing 100097,China)
出处
《中国工程科学》
CSCD
北大核心
2023年第4期227-238,共12页
Strategic Study of CAE
基金
国家重点研发计划项目(2022YFD2002300)
中国工程院咨询项目“生物育种数字化发展战略研究”(2021-JJZD-04)
“安徽省智慧农业发展战略研究”(2021-DFZ-17)。
关键词
作物表型组学
表型大数据
表型技术及装备
多组学
crop phenomics
phenotyping big data
technology and equipment for phenotyping
multi-omics