Dipta Bhawna, Sood Salej, Devi Rasna, Bhardwaj Vinay, Mangal Vikas, Thakur Ajay Kumar, Kumar Vinod, Pandey N K, Rathore Abhishek, Singh A K
ICAR-Central Potato Research Institute (CPRI), Shimla, Himachal Pradesh-171001, India.
CGIAR Excellence in Breeding Platform (EiB), International Maize and Wheat Improvement Center (CIMMYT), India.
Heliyon. 2023 Jan 20;9(1):e12974. doi: 10.1016/j.heliyon.2023.e12974. eCollection 2023 Jan.
A plant breeding program involves hundreds of experiments, each having number of entries, genealogy information, linked experimental design, lists of treatments, observed traits, and data analysis. The traditional method of arranging breeding program information and data recording and maintenance is not centralized and is always scattered in different file systems which is inconvenient for retrieving breeding information resulting in poor data management and the loss of crucial data. Data administration requires a significant amount of manpower and resources to maintain nurseries, trials, germplasm lines, and pedigree records. Further, data transcription in scattered spreadsheets and files leads to nomenclature and typing mistakes, which affects data analysis and selection decisions in breeding programs. The accurate data recording and management tools could improve the efficiency of breeding programs. Recent interventions in data management using computer-based breeding databases and informatics applications and tools have made the breeder's life easier. Because of its digital nature, the data obtained is improved even further, allowing for the acquisition of images, voice recording and other specific data kinds. Public breeding programs are far behind the industry in the use of data management tools and softwares. In this article, we have compiled the information on available data recording tools and breeding data management softwares with major emphasis on potato breeding data management.
一个植物育种计划涉及数百个实验,每个实验都有许多条目、系谱信息、相关的实验设计、处理列表、观察到的性状以及数据分析。安排育种计划信息以及数据记录与维护的传统方法并不集中,总是分散在不同的文件系统中,这不利于检索育种信息,导致数据管理不善以及关键数据丢失。数据管理需要大量人力和资源来维护苗圃、试验、种质系和系谱记录。此外,在分散的电子表格和文件中进行数据转录会导致命名和打字错误,这会影响育种计划中的数据分析和选择决策。准确的数据记录和管理工具可以提高育种计划的效率。最近利用基于计算机的育种数据库以及信息学应用程序和工具进行的数据管理干预,让育种者的工作变得更轻松。由于其数字特性,所获得的数据甚至得到了进一步改善,能够采集图像、语音记录和其他特定类型的数据。公共育种计划在数据管理工具和软件的使用方面远远落后于行业。在本文中,我们汇编了有关可用数据记录工具和育种数据管理软件的信息,重点是马铃薯育种数据管理。