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作物育种相关数据及大数据技术育种利用 被引量:16

Crop breeding-related data and application of big data technologies in crop breeding
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摘要 从18世纪首次获得人工杂交种到如今基因工程育种,作物育种技术发展迅速,同时几百年的育种历程积攒了大量育种数据,特别是近年来伴随高通量测序技术的发展,产生了海量作物育种相关基因及其表达数据,形成了育种大数据。2012年以来在商业、信息技术等领域发展迅猛的大数据技术,致力于解决大数据采集、存储及处理等壁垒,并在其他领域的应用初露端倪。本文利用创新方法 TRIZ(theory of inventive problem solving)流分析技术,综合分析了育种领域已有资源和目标达成的矛盾问题,提出大数据育种技术应用于作物育种的创新方案,明确了将大数据技术应用于育种领域的框架和实现目标。提出了基于大数据理念的育种技术,拟采集和整合已有育种数据资源,实现数据自动采集等,从而能够平衡育种数据膨胀/利用和育种需求产生的矛盾;构建基于大数据技术的育种数据信息化平台,实现作物育种方法理念的创新,可以为广大育种工作者提供数据支撑和一个育种新途径;为解析生物学数据与目标农艺性状的关系提供信息,加快育种现代化的进程。 Since the first artificial hybrid was created in 1719, significant developments such as transgenic approach have been seen in the methods for crop breeding in recent hundreds of years. A lot of breeding-related data have been collected up to now. The big data technology was developed recently and has been successfully used in economics, IT (information technology) and other fields. With the increasing expansion of data in crops breeding, it becomes extremely necessary for breeders to take advantage of existing data in terms of efficient breeding technology, especially for the information generated from next-generation sequencing which could newly reach terabytes of data in a sequencing platform in one hour. In this study, we proposed a conceptual framework for big data-based crop breeding approach after we analyzed the genetic information flow of crop breeding program using an innovation tool, TRIZ (theory of inventive problem solving). The expected new breeding technique tends to collect all breeding-related data (including data from phenotype, environments, references to molecular markers and sequences) for target crops and set up an automatic approach to collect breeding-related trait data. The technique will include a computer system to analyze the data and a human machine interface for users (breeders). We believe that big data has the potential to revolutionize the breeding of crops and the big data-based breeding approach is our future of crop breeding programs.
出处 《浙江大学学报(农业与生命科学版)》 CAS CSCD 北大核心 2016年第1期30-39,共10页 Journal of Zhejiang University:Agriculture and Life Sciences
基金 中华人民共和国科学技术部创新方法工作专项(2015IM010400) 中华人民共和国科学技术部科技基础性工作专项(2013IM030700)
关键词 作物育种 大数据技术 育种方法 大数据育种技术 创新方法 crop breeding big data technology breeding method big data-based breeding approach innovation method
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