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Field‐based individual plant phenotyping of herbaceous species by unmanned aerial vehicle

Citation

Guo, Wei; Fukano, Yuya; Noshita, Koji; Ninomiya, Seishi (2020), Field‐based individual plant phenotyping of herbaceous species by unmanned aerial vehicle, Dryad, Dataset, https://doi.org/10.5061/dryad.0cfxpnw0b

Abstract

1. Recent advances in Unmanned Aerial Vehicle (UAVs) and image processing have made high-throughput field phenotyping possible at plot/canopy level in the mass grown experiment. Such techniques are now expected to be used for individual level phenotyping in the single grown experiment. 2. We found two main challenges of phenotyping individual plants in the single grown experiment: plant segmentation from weedy backgrounds and the estimation of complex traits that are difficult to measure manurally. 3. In this study, we proposed a methodological framework for field-based individual plant phenotyping by UAV. Two contributions, which are weed elimination for individual plant segmentation, and complex traits (volume and outline) extraction, have been developed. The framework demonstrated its utility in the phenotyping of Helianthus tuberosus(Jerusalem artichoke), an herbaceous perennial plant species. 4. The proposed framework can be applied to either small and large scale phenotyping experiments.

Methods

Please check the paper for more details.

Usage Notes

This is a support page of paper : Guo, W., Fukano1,Y., Noshita, K., Ninomiya, S..(2020) Field-based individual plant phenotyping of herbaceous species by unmanned aerial vehicle.

Before testing the source code, the following dirctory of files should be downloaded to your PC.

Then,

  1. Run "step1_copyexperimentRe.m" if you need to copy the related files from Pix4Dmapper.
  2. open folder "makeSegModel", follow the steps to generate the color-based segmentation model.
  3. run "step2_weips.m"
  4. play with "*.CSV" files to get results needed.

Check more details here: https://github.com/oceam/WEIPS.