Validation of plant part measurements using a 3D reconstruction method suitable for high-throughput seedling phenotyping

Franck Golbach, Gert Kootstra*, Sanja Damjanovic, Gerwoud Otten, Rick van de Zedde

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Scopus)

Abstract

In plant phenotyping, there is a demand for high-throughput, non-destructive systems that can accurately analyse various plant traits by measuring features such as plant volume, leaf area, and stem length. Existing vision-based systems either focus on speed using 2D imaging, which is consequently inaccurate, or on accuracy using time-consuming 3D methods. In this paper, we present a computer-vision system for seedling phenotyping that combines best of both approaches by utilizing a fast three-dimensional (3D) reconstruction method. We developed image processing methods for the identification and segmentation of plant organs (stem and leaf) from the 3D plant model. Various measurements of plant features such as plant volume, leaf area, and stem length are estimated based on these plant segments. We evaluate the accuracy of our system by comparing the measurements of our methods with ground truth measurements obtained destructively by hand. The results indicate that the proposed system is very promising.

Original languageEnglish
Pages (from-to)663-680
JournalMachine Vision Applications
Volume27
Issue number5
DOIs
Publication statusPublished - 2016

Keywords

  • 3D Plant model
  • High-throughput phenotyping
  • Plant trait measurements
  • Seedling phenotyping

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