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Innovation Fund

Early detection of harmful algal blooms

We trialled two innovative technologies to detect and monitor harmful algal blooms in coastal waters

Project LeaderDurationBudget
Dr Lincoln Mackenzie (Cawthron Institute)July 2017 – September 2019$300,000

Overview

Harmful algal blooms are natural phenomena that sometimes occur in coastal ecosystems. They can have detrimental effects on human health, seafood harvesting and aquaculture businesses.  

Our aim was to develop simple, cost-effective sensitive tests that could be used by public health agencies, communities and the aquaculture industry to detect and monitor harmful algal blooms. These can reduce the risk of unnecessary closures. We trialled:

  • qPCR – Detects and quantifies algal DNA in the water. The method was sensitive, simple and practical. We were able to estimate the amount of the algae present within 90 minutes of collecting samples. Cawthron is continuing to optimise this testing method.
  • Imaging FlowCytoBot – This device can automatically identify and count algal cells underwater. Cawthron is now training image recognition software to identify local species, and working with an aquaculture industry consortium to investigate purchasing an IFCB.

The first method detects and quantifies algal DNA in the water. In mid-2018, we field trialled this method when a major bloom of toxic algae (Alexandrium pacificum) occurred in Pelorus Sound. We were able to estimate the amount of the algae present from multiple locations in the area within 90 minutes of collecting samples. The method was sensitive, simple and practical, and we are now working to improve estimates of the quantities of algae present.  

The second method uses a robotic submersible microscope developed by an American company (McLane Research Laboratories). The device, an Imaging FlowCytoBot, can automatically identify and count microscopic algal cells underwater. Before we can start using it, we need to train the software to recognise local species. For this work, we are collaborating with the aquaculture industry and an international expert who has experience with this instrument.  

Our aim is to use these technologies as an early warning system so that impacts on shellfish and finfish harvesting are minimised, and risks of recall of contaminated products are reduced.  

Related News

Project proposal

809 KB | pdf

Location

Tools & Resources

This project has produced or contributed to:

Detecting and forecasting coastal contamination
Presentation
Webinar presentation by Lincoln Mackenzie and Ben Knight, Oct 2019 (42 min + Q&A)
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A long-term time series of Dinophysis acuminata blooms and associated shellfish toxin contamination in Port Underwood, Marlborough Sounds, New Zealand
Academic publication
MacKenzie L (2019) Toxins 11, 74
View
qPCR assays for the detection and quantification of multiple paralytic shellfish toxin-producing species of Alexandrium
Academic publicationGuidance
Ruvindy R, Bolch CJ, MacKenzie L, Smith KF & Murray SA (2018) Frontiers in Microbiology 9:3153
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Metadata catalogue: Early detection of harmful algal blooms project
Dataset
This project has produced 5 datasets. You can find out about them through our metadata catalogue.
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