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Lincoln's Annotated Spatio-Temporal Strawberry Dataset (LAST-Straw)

arXiv (Cornell University) · 1 Mar 2024 · 10.48550/arxiv.2403.00566

Abstract

Automated phenotyping of plants for breeding and plant studies promises to provide quantitative metrics on plant traits at a previously unattainable observation frequency. Developers of tools for performing high-throughput phenotyping are, however, constrained by the availability of relevant datasets on which to perform validation. To this end, we present a spatio-temporal dataset of 3D point clouds of strawberry plants for two varieties, totalling 84 individual point clouds. We focus on the end use of such tools - the extraction of biologically relevant phenotypes - and demonstrate a phenotyping pipeline on the dataset. This comprises of the steps, including; segmentation, skeletonisation and tracking, and we detail how each stage facilitates the extraction of different phenotypes or provision of data insights. We particularly note that assessment is focused on the validation of phenotypes, extracted from the representations acquired at each step of the pipeline, rather than singularly focusing on assessing the representation itself. Therefore, where possible, we provide \textit{in silico} ground truth baselines for the phenotypes extracted at each step and introduce methodology for the quantitative assessment of skeletonisation and the length trait extracted thereof. This dataset contributes to the corpus of freely available agricultural/horticultural spatio-temporal data for the development of next-generation phenotyping tools, increasing the number of plant varieties available for research in this field and providing a basis for genuine comparison of new phenotyping methodology.

Plant phenotyping relevance

植物の3D点群データセットを提供し、セグメンテーション・骨格化・追跡による表現型抽出パイプラインと、その定量的検証手法を中心に扱っているため。

abstractThis comprises of the steps, including; segmentation, skeletonisation and tracking, and we detail how each stage facilitates the extraction of different phenotypes or provision of data insights.

Code and data availability

The paper's LAST-Straw dataset (84 strawberry plant point clouds with semantic/instance annotations and ground-truth stem skeletons) and supplementary graph-matching code are both publicly available via author-provided URLs in the data availability statement.

Codepublic

Supplementary code for graph matching can be accessed via https://github.com/LCAS/GraphMatching3D.

Open resource ↗LCAS/GraphMatching3D · pdf-page:31 lines:1-39

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