Automated extraction of seed morphological traits from images

Abstract

1. The description of biological objects, such as seeds, mainly relies on manual measurements of few characteristics, and on visual classification of structures, both of which can be subjective, error prone and time-consuming. Image analysis tools offer means to address these shortcomings, but we currently lack a method capable of automatically handling seeds from different taxa with varying morphological attributes and obtaining interpretable results. 2. Here, we provide a simple image acquisition and processing protocol and introduce Traitor, an open-source software available as a command-line interface (CLI), which automates the extraction of seed morphological traits from images. The workflow for trait extraction consists of scanning seeds against a high-contrast background, correcting image colours, and analysing images with the software.Traitor is capable of processing hundreds of images of varied taxa simultaneously with just three commands, and without a need for training, manual fine-tuning or thresholding. The software automatically detects each object in the image and extracts size measurements, traditional morphometric descriptors widely used by scientists and practitioners, standardised shape coordinates, and colorimetric measurements.3. The method was tested on a dataset comprising of 91,667 images of seeds from 1228 taxa. Traitor's extracted average length and width values closely matched the average manual measurements obtained from the same collection (concordance correlation coefficient of 0.98). Further, we used a large image dataset to demonstrate how Traitor's output can be used to obtain representative seed colours for taxa, determine the phylogenetic signal of seed colour, and build objective classification categories for shape with high levels of visual interpretability. 4. Our approach increases productivity and allows for large-scale analyses that would otherwise be unfeasible. Traitor enables the acquisition of data that are readily comparable across different taxa, opening new avenues to explore functional relevance of morphological traits and to advance on new tools for seed identification.

DiasMorph: a dataset of morphological traits and images of Central European diaspores

“…We used an image analysis method described and validated by Dayrell et al . 16 to obtain images and extract quantitative measurements of diaspore morphology.…”

“…(2) We measured diaspores without scales or covering structures when most diaspores in a vial of the seed collection had detached from these structures without handling. (3) Hairy appendages (e.g., pappus and plumes) were removed due to requirements of the method 16 . The structures that were not present in the scanned diaspores were recorded as ‘missing structures’ in the dataset.…”

“…The Traitor software https://github.com/TankredO/traitor was used to segment, align, and extract morphological traits from images 16 . The extracted traits include: (1) morphometric measurements (length, width, aspect ratio, area, perimeter, diaspore surface structure, solidity, circularity); (2) colour measurements for human recognition purposes (Fig.…”

“…Here, we present DiasMorph , a comprehensive dataset of morphological traits and images of diaspores from Central Europe. It provides images of 94,214 diaspores from 1,442 taxa in 519 genera, and 96 families, captured against a high-contrast background with a standardised and reproducible method 16 . The dataset also compiles information on quantitative morphological traits extracted from the images following an image analysis method 16 and include not only traditional morphometric measurements, but also colour, and contour features made available for the first time in a large dataset.…”

“…It provides images of 94,214 diaspores from 1,442 taxa in 519 genera, and 96 families, captured against a high-contrast background with a standardised and reproducible method 16 . The dataset also compiles information on quantitative morphological traits extracted from the images following an image analysis method 16 and include not only traditional morphometric measurements, but also colour, and contour features made available for the first time in a large dataset. The quantitative traits records correspond to measurements of individual diaspores, an input currently unavailable in trait databases that will allow for several approaches to be used for a complete exploration of the morphological traits of these species.…”