Plant Screen Mobile: an open-source mobile device app for plant trait analysis

• Published in: Plant methods Vol. 15; no. 1; p. 2
• Main Authors: Müller-Linow, Mark, Wilhelm, Jens, Briese, Christoph, Wojciechowski, Tobias, Schurr, Ulrich, Fiorani, Fabio
• Format: Journal Article
• Language: English
• Published: London BioMed Central 11.01.2019; BioMed Central Ltd; BMC
• Subjects: Analysis; Android; Automation; Biological Techniques; Biomass; Biomedical and Life Sciences; case studies; Cellular telephones; color; Correlation analysis; Data acquisition; Data collection; Data processing; Destructive testing; Digital imaging; Eragrostis; Flowers; genotype; Genotypes; greenhouses; Ground truth; Image analysis; Image processing; Leaf area; Leaves; Life Sciences; Machine learning; Measurement methods; Mobile application; Mobile applications; Mobile communication systems; Mobile devices; mobile telephones; Musa; Plant growth; Plant image segmentation; Plant physiology; Plant Sciences; Plant tissues; Plants; portable equipment; Projected leaf area; Proxy; screening; Seeds; Sensors; Smartphones; Software; United States; Image analysis; Mobile application; Projected leaf area; Plant image segmentation; Machine learning; Android
• ISSN: 1746-4811; 1746-4811
• DOI: 10.1186/s13007-019-0386-z

Background The development of leaf area is one of the fundamental variables to quantify plant growth and physiological function and is therefore widely used to characterize genotypes and their interaction with the environment. To date, analysis of leaf area often requires elaborate and destructive measurements or imaging-based methods accompanied by automation that may result in costly solutions. Consequently in recent years there is an increasing trend towards simple and affordable sensor solutions and methodologies. A major focus is currently on harnessing the potential of applications developed for smartphones that provide access to analysis tools to a wide user basis. However, most existing applications entail significant manual effort during data acquisition and analysis. Results With the development of Plant Screen Mobile we provide a suitable smartphone solution for estimating digital proxies of leaf area and biomass in various imaging scenarios in the lab, greenhouse and in the field. To distinguish between plant tissue and background the core of the application comprises different classification approaches that can be parametrized by users delivering results on-the-fly. We demonstrate the practical applications of computing projected leaf area based on two case studies with Eragrostis and Musa plants. These studies showed highly significant correlations with destructive measurements of leaf area and biomass from both ground truth measurements and estimations from well-established screening systems. Conclusions We show that a smartphone together with our analysis tool Plant Screen Mobile is a suitable platform for rapid quantification of leaf and shoot development of various plant architectures. Beyond the estimation of projected leaf area the app can also be used to quantify color and shape parameters of other plant material including seeds and flowers.