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

This dataset is a snapshot of our GitHub repository and other data which accompanies our published paper:

Feldman, A., Wang, H.,Fukano, Y., Kato, Y., Ninomiya, S., and Guo, W. (2021). EasyDCP: an affordable, high-throughput tool to measure plant phenotypic traits in 3D. Methods in Ecology and Evolution.

Abstract

1. 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. 
2. 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.
3. 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).  
4. EasyDCP is an open-source software tool to measure phenotypic traits of container plants with high throughput and low labor and financial costs.

Usage Notes

Download and extract "EasyDCP_Data.zip" anywhere on your pc, e.g.: D:_Data

Follow all steps in "EasyDCP-GitHub-repository-master-master.md" to ensure EasyDCP is setup properly.

To generate 3D point cloud (.ply) files using EasyDCP_Creation

1. Navigate to "EasyDCP-GitHub-repository-master/EasyDCP-master/easydcp/creation/"
2. Open "params.ini" in text editor and modify the root_folder variable (line 4) to match the location of the EasyDCP_Data folder. e.g., if you extracted to D:_Data, 

   root_folder = D:_Data_test_Image_acquisition

   Note that there are no quotes.

3. Run "creation-win.bat" (Windows) or "creation-mac.sh" (Mac/Linux) and wait for completion.
4. .ply and .pdf files will be outputted in each subfolder in "Performance test_Image_acquisition". You can compare these with the files in "1_EasyDCP_Creation". Note they will not be identical because Agisoft Metashape generates slightly different results every time, but they should be very similar.

To analyze the 3D point cloud (.ply) files using EasyDCP_Analysis:

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