Performance and accuracy of the automated measurement software: Simple Online Automated Plant Phenomics (SOAPP)

Abstract

Abstract Many new tools for morphological and developmental studies have become available to plant biology researchers, including software capable of collecting data, nearly automatically, from phenotypic assays. In this study, we compare the validity and accuracy of data on the growth of seedlings collected using ImageJ software with data collected using a more automated software, termed Simple Online Automated Plant Phenomics (SOAPP). Images from a Genome-Wide Association Study (GWAS) investigating the responses of twenty wild-type plants to gravity were analyzed using both methods and compared. Seedlings were grown in either static or stationary conditions or mounted on a rotating 2D clinostat. We found that although human error did create variability between repeated measurements using ImageJ, while SOAPP exhibited none, the validity of data collected using ImageJ was greater than that collected using SOAPP automation. The manual measurements with ImageJ revealed that one of the Arabidopsis thaliana wild-type lines, AP-Ara-4, experienced less stress due to altered gravitational conditions than the other nineteen lines analyzed. Updates and new features added to the SOAPP software will continue to improve the user interface and the quality of data collected, but it is already valuable as a tool capable of perfect replicability in its measurements of plant growth and development.

Plant phenotyping relevance

植物成長の画像測定ソフトウェアSOAPPをImageJと比較し、妥当性・精度・再現性を評価した研究であり、植物表現型取得手法が中心である。

Code and data availability

The paper's SOAPP analysis software is explicitly not public yet ('SOAPP source code is not publicly available at this time but will be made available for public use in the future on GitHub'), and no public phenotype dataset, image collection, or author code URL is provided. Streamlit, PlantCV, and Docker URLs are only

No evidence-backed public reproduction asset is currently recorded.