Published July 20, 2022 | Version v1

PNS-Cyst-Count-Artifical: images of controlled number of nematode cysts with orgnic debris

  • 1. Institute of Imaging and Computer Vision, RWTH Aachen University, Germany
  • 2. Julius Kühn Institute (JKI) – Federal Research Center for Cultivated Plants, Elsdorf, Germany
  • 3. LemnaTec, Aachen, Germany

Description

Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing.

This dataset was generated by manually picking nematode cysts into organic debris, so that the cyst count is known and controlled. A total of 6x8=48 samples were synthesized. Each sample contains 30 images.

We also collected images of real soil samples, which is available from the links:

https://zenodo.org/record/6861775

https://zenodo.org/record/6861814

For details of the data collection and deep learning model training, refer to our paper:

Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [link]

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Cyst120-OM100.zip

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