Acute pseudo-landmarking and Constellation homologies: A generalized workflow to identify and track segmented structures in plant time series images

Assessing plant phenotypes throughout the lifecycle is integral to exploring the development, genetics, and evolution of morphology, and can be critical for agronomic and basic research studies. Although various automated or semi-automated phenomic approaches have been developed, it has been challenging to analyze differential growth because of difficulties in segmenting and annotating specific structures or positions in the plant body and maintaining their identities throughout time-series data. To address this gap, we have developed a generalized workflow linking our previously published function, Acute, with a companion homology workflow, Constellation, in the PlantCV environment. Acute identifies acute shapes (pseudo-landmarks) in the plant body, most often corresponding to leaf tips and ligular regions. Constellation uses a strategy of dimensionality reduction via starscape followed by hierarchical clustering through constella to identify ‘constellations’ of segments in eigenspace that represent the same landmark in consecutive images of a time-series. We devised a quality control function, constellaQC, to test the accuracy of the clustering approach, and use it to show that the approach appropriately clusters the pseudo-landmarks derived from Acute, with 80-90% accuracy. We discuss the reasons for and consequences of this lack of 100% accuracy in automated workflows and suggest how to develop these functions for other phenomics datasets that may vary in dimensional complexity.

Methods
Images were collected from an imaging cabinet designed from a series of Raspberry Pi 3-Model B boards using the native raspistill function found in the Raspbian version of the Debian OS which were subsequently used to generate the pseudo-landmark datasets available here. Pseudo-landmarks were then grouped into conserved identities through time via the Constellation homology workflow which could then be used for morphometric analysis thereafter. Ground-truthing measures were derived from FIJI using the corresponding images used for pseudo-landmarking and homology analysis.