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现代计算机技术促进了作物育种技术的数字化进程。随着作物性状数据采集技术的发展成熟,作物育种过程中产生的数据呈指数增长,促使传统作物育种技术变革。作物育种过程中产生的数据类型十分复杂,数据的存储、分析和利用是作物育种技术的一个组成部分,促成了现代数字育种技术的迅猛发展。通过分析玉米育种过程中涉及到的各类数据,提出概念性的作物育种数据管理系统框架,并阐明各类数据之间的相互关系。完善的育种数据管理系统除核心数据库外,还包括多项数据分析模块,包括系谱树和亲缘分析、分子标记和基因定位、数据采集和性状分解、杂交组合和后代选择、育种策略分析、田间试验设计和统计分析、生长发育系统模拟和基因功能和调控网络等。数据分析模块可以根据作物育种实践的实际需要进行组合,但并非所有模块都是必需的。
Modern computer technology has promoted the digitization of crop breeding technology. With the development of crop characterization data acquisition technology, the data generated during the crop breeding process grow exponentially, prompting the transformation of traditional crop breeding technology. The types of data produced during crop breeding are complex and the storage, analysis and utilization of data are an integral part of crop breeding technology and have contributed to the rapid development of modern digital breeding techniques. By analyzing all kinds of data involved in the breeding process of maize, a conceptual crop breeding data management system framework is put forward and the interrelationship among various data is clarified. In addition to the core database, a well-established breeding data management system includes a number of data analysis modules including genealogical tree and phylogenetic analysis, molecular markers and gene mapping, data collection and characterization, hybrid combinations and offspring selection, breeding strategy analysis, field trials Design and statistical analysis, growth and development system simulation and gene function and regulatory networks. Data analysis modules can be combined according to the actual needs of crop breeding practice, but not all modules are required.