Data

CSIRO Australian Phytoplankton Microscopy Dataset (CAPMD) 2022

Commonwealth Scientific and Industrial Research Organisation
Jackett, Chris ; Devine, Carlie ; Jameson, Ian ; Watson, Ros ; Thrall, Pete
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/0xpd-7f75&rft.title=CSIRO Australian Phytoplankton Microscopy Dataset (CAPMD) 2022&rft.identifier=https://doi.org/10.25919/0xpd-7f75&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=The CSIRO Australian Phytoplankton Microscopy Dataset (CAPMD) 2022 is a comprehensive collection of high-quality microscopy images documenting the morphological diversity of phytoplankton species from the Australian National Algae Culture Collection (ANACC).Lineage: Images were acquired using ZEISS Axio Observer and Axio Plan microscopes under standardised laboratory conditions at the CSIRO Battery Point site in Hobart, Tasmania. Live specimens were prepared in suspension and systematically imaged by capturing multiple short videos (50-200 frames) using a focal rolling technique that involved maneuvering the objective lens through different focal planes of the sample to capture key taxonomic features and cellular structures. The imaging protocol implemented multiple modalities including bright field, differential interference contrast, and phase contrast microscopy at magnifications ranging from 100x to 1000x. Specimens were selectively treated with Tylose to immobilise highly motile cells while maintaining their structural integrity, or Lugol's (Iodine) solution as a fixing agent to capture fixed cell imagery, which is a standard approach in phytoplankton identification. The imaging protocol was specifically designed to support the development of automated phytoplankton identification systems using machine learning techniques, with careful attention given to image quality, consistency, and comprehensive coverage of taxonomically significant features across different imaging conditions. This systematic imaging campaign successfully balanced the need for high-quality, representative samples with efficient, high-volume image capture, creating a robust dataset for advancing automated phytoplankton identification methods.&rft.creator=Jackett, Chris &rft.creator=Devine, Carlie &rft.creator=Jameson, Ian &rft.creator=Watson, Ros &rft.creator=Thrall, Pete &rft.date=2025&rft.edition=v1&rft.coverage=147.33873916666667,-42.88742277777778&rft_rights=Creative Commons Attribution-Noncommercial 4.0 Licence https://creativecommons.org/licenses/by-nc/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2025.&rft_subject=microscopy&rft_subject=phytoplankton&rft_subject=algae&rft_subject=high-magnification imaging&rft_subject=cell structures&rft_subject=brightfield&rft_subject=differential interference contrast&rft_subject=phase contrast&rft_subject=laboratory imaging&rft_subject=biological specimens&rft_subject=Australian National Algae Culture Collection&rft_subject=CSIRO&rft_subject=Other environmental sciences not elsewhere classified&rft_subject=Other environmental sciences&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Image processing&rft_subject=Computer vision and multimedia computation&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution-Noncommercial 4.0 Licence
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Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO 2025.

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The CSIRO Australian Phytoplankton Microscopy Dataset (CAPMD) 2022 is a comprehensive collection of high-quality microscopy images documenting the morphological diversity of phytoplankton species from the Australian National Algae Culture Collection (ANACC).
Lineage: Images were acquired using ZEISS Axio Observer and Axio Plan microscopes under standardised laboratory conditions at the CSIRO Battery Point site in Hobart, Tasmania. Live specimens were prepared in suspension and systematically imaged by capturing multiple short videos (50-200 frames) using a focal rolling technique that involved maneuvering the objective lens through different focal planes of the sample to capture key taxonomic features and cellular structures. The imaging protocol implemented multiple modalities including bright field, differential interference contrast, and phase contrast microscopy at magnifications ranging from 100x to 1000x. Specimens were selectively treated with Tylose to immobilise highly motile cells while maintaining their structural integrity, or Lugol's (Iodine) solution as a fixing agent to capture fixed cell imagery, which is a standard approach in phytoplankton identification. The imaging protocol was specifically designed to support the development of automated phytoplankton identification systems using machine learning techniques, with careful attention given to image quality, consistency, and comprehensive coverage of taxonomically significant features across different imaging conditions. This systematic imaging campaign successfully balanced the need for high-quality, representative samples with efficient, high-volume image capture, creating a robust dataset for advancing automated phytoplankton identification methods.

Available: 2025-03-07

Data time period: 2022-01-13 to 2022-12-20

This dataset is part of a larger collection

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Subjects
Australian National Algae Culture Collection | CSIRO | Computer Vision and Multimedia Computation | Environmental Sciences | Information and Computing Sciences | Image Processing | Other Environmental Sciences | Other Environmental Sciences Not Elsewhere Classified | algae | biological specimens | brightfield | cell structures | differential interference contrast | high-magnification imaging | laboratory imaging | microscopy | phase contrast | phytoplankton |

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Identifiers
ACN 633 798 857