DOI: 10.5061/dryad.sxksn033w
title: Acute pseudo-landmarking and Constellation homologies: A generalized workflow to identify and track segmented structures in plant time series images

description: 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.
description: 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.
description: This dataset includes two directories described below (one output
 data and other supplementary image data used to generate these inputs) in
 addition to an R script 'acute_heights_QC.R' which was used for
 ground-truthing the accuracy of the pseudo-landmarks against manual
 measures for ligular plant height (the corresponding data files for this
 script can be found in 'constella_homology_groups.QC_height_testing
 contents'.
 constella_homology_groups.QC_height_testing contents
 Homology group files for each genotype surveyed contain 10
 columns which can be interpreted as follows: [1]
 'group'- de novo homology group assignment either as a serial
 number (constella output) or reannotated into a structure of biological
 interest. Note that '-' are considered NA grouping values given
 that these are rogue points which are considered uninformative for
 downstream morphometric analysis. [2]
 'plmname'-serial name identifiers given to pseudo-landmarks for
 each image frame. [3] 'filename'-name of the
 image frame plmnames are derived from. [4]
 'x' and [5] 'y'-the pseudo-landmark x and y pixel
 coordinate locations in the image frame. [6]
 'SS_x' and [7] 'SS_y'-The bounding Start Site x and y
 pixel coordinate locations for acute islands along a contour which acute
 uses to define a specific plm coordinate location. [8]
 'TS_x' and [9] 'TS_y'-The bounding Termination Site x
 and y pixel coordinate locations for acute islands along a contour which
 acute uses to define a specific plm coordinate location.
 [10] 'cc_ratio'-The Convexity-Concavity Ratio defined
 by the average pixel intensity of the binary mask within the acute island
 which can serve as a useful metadata dimension in downstream homology
 grouping. Ground-truthing heights data provides the
 age, leaf number, and ligular heights which correspond to the plants
 surveyed under this pseudo-landmarking and homology grouping
 strategy. Acute_Constellation_Homology_Images_Masks
 contents  Three different image series directories for
 the genotypes and reps sampled for pseudo-landmarking are stored within
 this folder which include: [1] The raw image files used
 as input data for this workflow.  [2] The initial batch
 binary threshold masks which were performed under a generalized pipeline
 in the PlantCV environment [3] The corrected masks
 which situationally alleviated segmentation issues of the binary mask
 capturing the plants shape, especially around rolling leaves where the
 mask could bifurcate. Additionally corrections may have been secondary
 image thresholding in cases where the generalized color thresholds were
 insufficient to properly capture the plant shape.