Scott Madeline, de Lange Orlando, Quaranto Xavaar, Cardiff Ryan, Klavins Eric
Department of Electrical and Computer Engineering, University of Washington, Seattle, USA.
Plant Methods. 2023 Sep 1;19(1):95. doi: 10.1186/s13007-023-01065-3.
Duckweeds, a family of floating aquatic plants, are ideal model plants for laboratory experiments because they are small, easy to cultivate, and reproduce quickly. Duckweed cultivation, for the purposes of scientific research, requires that lineages are maintained as continuous populations of asexually propagating fronds, so research teams need to develop optimized cultivation conditions and coordinate maintenance tasks for duckweed stocks. Additionally, computational image analysis is proving to be a powerful duckweed research tool, but researchers lack software tools to assist with data collection and storage in a way that can feed into scripted data analysis. We set out to support these processes using a laboratory management software called Aquarium, an open-source application developed to manage laboratory inventory and plan experiments. We developed a suite of duckweed cultivation and experimentation operation types in Aquarium, which we then integrated with novel data analysis scripts. We then demonstrated the efficacy of our system with a series of image-based growth assays, and explored how our framework could be used to develop optimized cultivation protocols. We discuss the unexpected advantages and the limitations of this approach, suggesting areas for future software tool development. In its current state, our approach helps to bridge the gap between laboratory implementation and data analytical software for duckweed biologists and builds a foundation for future development of end-to-end computational tools in plant science.
浮萍是一类漂浮水生植物,因其植株小、易于栽培且繁殖迅速,是实验室实验的理想模式植物。出于科学研究目的的浮萍栽培,要求将谱系维持为无性繁殖叶状体的连续群体,因此研究团队需要制定优化的栽培条件,并协调浮萍种源的维护工作。此外,计算图像分析已被证明是一种强大的浮萍研究工具,但研究人员缺乏软件工具来协助以可用于脚本化数据分析的方式收集和存储数据。我们着手使用一款名为Aquarium的实验室管理软件来支持这些流程,Aquarium是一款为管理实验室库存和规划实验而开发的开源应用程序。我们在Aquarium中开发了一套浮萍栽培和实验操作类型,然后将其与新颖的数据分析脚本集成。然后,我们通过一系列基于图像的生长测定证明了我们系统的有效性,并探索了我们的框架如何用于制定优化的栽培方案。我们讨论了这种方法的意外优势和局限性,提出了未来软件工具开发的方向。在当前状态下,我们的方法有助于弥合浮萍生物学家的实验室实施与数据分析软件之间的差距,并为植物科学中端到端计算工具的未来发展奠定基础。