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Acoustic focussing for sedimentation-free high-throughput imaging of microalgae

Acoustic focussing for sedimentation-free high-throughput imaging of microalgae
Acoustic focussing for sedimentation-free high-throughput imaging of microalgae
Microalgae play a key role in aquatic ecology, and methods providing species determination and enumeration can provide critical information about—for instance—harmful algae blooms (HABs) or spreading of invasive species. A crucial step in current methods is the use of sedimentation. This provides the enrichment needed to achieve statistical counts of sometimes rare species within reasonable timeframes, but it comes with the drawback of aggregating the sample. This is a real challenge for computer-aided identification as particle aggregates can often be erroneously classified. In this paper, we propose an alternative method based on flow-through imaging aided by acoustic-focussing, as this provides better input-data for automated counting-methods while simultaneously removing the need for manual sample preparation. We demonstrate that by acoustically focussing microalgae and other particulates in a fast-flowing water sample, it is possible to analyse up to 8 mL sample per minute with sufficient image quality to discriminate the invasive species Ostreopsis ovata from other particulates in samples taken directly from the Mediterranean. We also showcase the ability to achieve sharp images in flow-through at magnifications up to × 50.
Microfluidics, Acoustics, Acoustofluidics, Ostreopsis Ovata, High throughput screening, Imaging cytometry, Environmental Monitoring
0921-8971
1-9
Hammarstrom, Bjorn
e68f865f-bb5e-4170-bc91-cf7b4ea60ba3
Vassalli, Massimo
e6b24b46-2d13-4d0f-98ac-b8670b33758a
Glynne-Jones, Peter
6ca3fcbc-14db-4af9-83e2-cf7c8b91ef0d
Hammarstrom, Bjorn
e68f865f-bb5e-4170-bc91-cf7b4ea60ba3
Vassalli, Massimo
e6b24b46-2d13-4d0f-98ac-b8670b33758a
Glynne-Jones, Peter
6ca3fcbc-14db-4af9-83e2-cf7c8b91ef0d

Hammarstrom, Bjorn, Vassalli, Massimo and Glynne-Jones, Peter (2019) Acoustic focussing for sedimentation-free high-throughput imaging of microalgae. Journal of Applied Phycology, 1-9. (doi:10.1007/s10811-019-01907-5).

Record type: Article

Abstract

Microalgae play a key role in aquatic ecology, and methods providing species determination and enumeration can provide critical information about—for instance—harmful algae blooms (HABs) or spreading of invasive species. A crucial step in current methods is the use of sedimentation. This provides the enrichment needed to achieve statistical counts of sometimes rare species within reasonable timeframes, but it comes with the drawback of aggregating the sample. This is a real challenge for computer-aided identification as particle aggregates can often be erroneously classified. In this paper, we propose an alternative method based on flow-through imaging aided by acoustic-focussing, as this provides better input-data for automated counting-methods while simultaneously removing the need for manual sample preparation. We demonstrate that by acoustically focussing microalgae and other particulates in a fast-flowing water sample, it is possible to analyse up to 8 mL sample per minute with sufficient image quality to discriminate the invasive species Ostreopsis ovata from other particulates in samples taken directly from the Mediterranean. We also showcase the ability to achieve sharp images in flow-through at magnifications up to × 50.

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More information

Accepted/In Press date: 26 August 2019
e-pub ahead of print date: 14 September 2019
Additional Information: Dataset https://doi.org/10.5258/SOTON/D1074
Keywords: Microfluidics, Acoustics, Acoustofluidics, Ostreopsis Ovata, High throughput screening, Imaging cytometry, Environmental Monitoring

Identifiers

Local EPrints ID: 435612
URI: http://eprints.soton.ac.uk/id/eprint/435612
ISSN: 0921-8971
PURE UUID: 0c522f45-8a37-497a-8fad-7006987a47d7
ORCID for Peter Glynne-Jones: ORCID iD orcid.org/0000-0001-5684-3953

Catalogue record

Date deposited: 14 Nov 2019 17:30
Last modified: 17 Mar 2024 02:49

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Contributors

Author: Bjorn Hammarstrom
Author: Massimo Vassalli

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