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GridScore:一个用于准确、跨平台的表型数据收集和可视化的工具。

GridScore: a tool for accurate, cross-platform phenotypic data collection and visualization.

机构信息

Department of Information and Computational Sciences, The James Hutton Institute, Invergowrie, Dundee, Scotland.

Department of Life Science, University of Dundee, Dundee, Scotland.

出版信息

BMC Bioinformatics. 2022 Jun 6;23(1):214. doi: 10.1186/s12859-022-04755-2.

Abstract

BACKGROUND

Plant breeding and crop research rely on experimental phenotyping trials. These trials generate data for large numbers of traits and plant varieties that needs to be captured efficiently and accurately to support further research and downstream analysis. Traditionally scored by hand, phenotypic data is nowadays collected using spreadsheets or specialized apps. While many solutions exist, which increase efficiency and reduce errors, none offer the same familiarity as printed field plans which have been used for decades and offer an intuitive overview over the trial setup, previously recorded data and plots still requiring scoring.

RESULTS

We introduce GridScore which utilizes cutting-edge web technologies to reproduce the familiarity of printed field plans while enhancing the phenotypic data collection process by adding advanced features like georeferencing, image tagging and speech recognition. GridScore is a cross-platform open-source plant phenotyping app that combines barcode-based systems with a guided data collection approach while offering a top-down view onto the data collected in a field layout. GridScore is compared to existing tools across a wide spectrum of criteria including support for barcodes, multiple platforms, and visualizations.

CONCLUSION

Compared to its competition, GridScore shows strong performance across the board offering a complete manual phenotyping experience.

摘要

背景

植物育种和作物研究依赖于实验表型分析试验。这些试验会产生大量性状和植物品种的数据,需要高效、准确地捕获这些数据,以支持进一步的研究和下游分析。传统上这些数据是通过手工评分获得的,而现在则使用电子表格或专门的应用程序来收集表型数据。虽然有许多解决方案可以提高效率并减少错误,但没有一种解决方案能像已经使用了几十年的打印田间图一样具有相同的熟悉度,它可以直观地提供试验设置、以前记录的数据和仍需评分的地块的概述。

结果

我们引入了 GridScore,它利用最先进的网络技术复制了打印田间图的熟悉感,同时通过添加地理参考、图像标记和语音识别等高级功能增强了表型数据收集过程。GridScore 是一个跨平台的开源植物表型分析应用程序,它将基于条形码的系统与引导式数据收集方法相结合,同时提供了在田间布局中收集数据的自上而下的视图。GridScore 在广泛的标准上与现有工具进行了比较,包括对条形码的支持、多个平台和可视化。

结论

与竞争对手相比,GridScore 在各个方面都表现出色,提供了完整的手动表型分析体验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62e8/9169276/f561bdb87685/12859_2022_4755_Fig1_HTML.jpg

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