EasyDCP: An affordable, high-throughput tool to measure plant phenotypic traits in 3D

Alexander Feldman, Haozhou Wang, Yuya Fukano, Yoichiro Kato, Seishi Ninomiya, Wei Guo

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

High-throughput 3D phenotyping is a rapidly emerging field that has widespread application for measurement of individual plants. Despite this, high-throughput plant phenotyping is rarely used in ecological studies due to financial and logistical limitations. We introduce EasyDCP, a Python package for 3D phenotyping, which uses photogrammetry to automatically reconstruct 3D point clouds of individuals within populations of container plants and output phenotypic trait data. Here we give instructions for the imaging setup and the required hardware, which is minimal and do-it-yourself, and introduce the functionality and workflow of EasyDCP. We compared the performance of EasyDCP against a high-end commercial laser scanner for the acquisition of plant height and projected leaf area. Both tools had strong correlations with ground truth measurement, and plant height measurements were more accurate using EasyDCP (plant height: EasyDCP r2 = 0.96, Laser r2 = 0.86; projected leaf area: EasyDCP r2 = 0.96, Laser r2 = 0.96). EasyDCP is an open-source software tool to measure phenotypic traits of container plants with high-throughput and low labour and financial costs.

Original languageEnglish
Pages (from-to)1679-1686
Number of pages8
JournalMethods in Ecology and Evolution
Volume12
Issue number9
DOIs
Publication statusPublished - Sep 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecological Modelling

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