E O’Connell, W B Lyons and E Lewis
Optical Fibre Sensors Research Centre, Electronic and Computer Engineering
Department, University of Limerick, Castletroy, Limerick, Ireland. eoin.oconnell@ul.ie
Abstract . Research into the development of an Early Warning Harmful Algae
Bloom (HAB) Sensing System for use in Underwater Monitoring Applications is presented. The sensor proposed by the authors utilises the complex ties between ocean colour, absorption and scattering, along with algae pigmentation. The objective is to develop a robust inexpensive sensor for use in an early warning system for the detection and possible identification of
Harmful Algae Blooms. The sensing mechanism utilised in this system is based on a combination of absorption and reflection spectroscopy and
Principle Component Analysis (PCA) signal processing. Spectroscopy is concerned with the production, measurement, and interpretation of electromagnetic spectra arising from either emission or absorption of radiant energy by various substances (or HABs in this application). Preliminary results are presented from the interrogation of chlorophyll, yeast and saline solutions, as well as levels of absorption obtained utilising two dyes Blue
(brilliant Blue (E133) and Carmoisine (E122) mix) and Red (Ponceau (E124) and Sunset yellow (E110) mix).
1. Introduction
There are over 4000 species of marine algae (phytoplankton) and 2% (69
– 78 species) are known to produce toxins, most of which are dinoflagellates. Traditional approaches for identifying harmful algal bloom (HAB) species and affiliated toxins are central to research and management of marine life, but such methods require the return of discrete samples for laboratory analysis. It is envisaged that a non-expensive method of detection can be developed using plastic optical fibres (POF). The objective is to develop a robust early warning system for the on-line detection and possible identification of individual Harmful
Algae Blooms, and in light of a growing concern about the presence of increased levels of
Domoic acid off the coast of Ireland, we believe now is the time to be concentrating on the development of a cheap sensor for it’s detection [1].
Domoic Acid Poisoning is caused from a harmful algal bloom. A naturally occurring neurotoxin called domoic acid has been responsible for the sickness of many marine animals throughout the world during the last few years [2].
Domoic Acid is one of the main causes of Amnesic Shellfish poisoning (ASP) and
ASP can be a life-threatening syndrome. It is characterized by both gastrointestinal and neurological disorders. Gastroenteritis usually develops within 24 hours of the consumption of toxic shellfish; symptoms include nausea, vomiting, abdominal cramps, and diarrhea. In severe cases, neurological symptoms also appear, usually within 48 hours of toxic shellfish consumption. These symptoms include dizziness, headache, seizures, disorientation, short-

term memory loss, respiratory difficulty, and coma. In 1987, four victims died after consuming toxic mussels from Prince Edward Island, Canada. Since that time, Canadian authorities have monitored both the water column for the presence of the causative diatom, and shellfish for the presence of the toxin, domoic acid [3]. Shellfish beds are closed to harvesting when the domoic acid concentration reaches 20 µg/g shellfish meat. Fish and crab viscera can also contain domoic acid, so the risk to human consumers and animals in the marine food chain is more significant than previously believed. Figure 1 illustrates a map of Europe highlighting
ASP incidences over a 10 year period.
The Objective of this work is the develop a robust early warning system for the detection and possible identification of Harmful Algae Blooms.
2. Experimental Setup
2.1 Sensor Head
The Sensor head or transreflection dip probe, as illustrated in Figure 2, (Ocean Optics T300 dip probe)[4] consists of a pair of 300mm solarisation-resistant optical fibres, one of which is used as an illumination fibre and one as the read (or receiving) fiber to carry light back to the detector. The fibres are housed in a 0.125" outer diameter stainless steel assembly that slides into a 5" long, 0.25" outer diameter stainless steel ferrule. Screw on, interchangeable probe tips are available with 2-mm, 5-mm and 10-mm optical path lengths, so that sampling setups can be configured for optically dense or dilute solutions.
Such a design is robust in nature and allows for ease of cleaning preventing the gradual build up of contaminants and fouling associated with environmental exposure. A plano-convex lens shapes the light coming out of the illumination fiber. The light is transmitted through the sample, reflected off the mirror, interacts with the sample again, and transmitted back through the probe via the read fiber. Because the light travels through the sampling region twice, the optical path length is actually twice the length of the sample aperture. The transmission cell is used to measure absorbance of the fluid that fills the sample compartment between the fibers and the mirror.
2.2 Sensing System
As illustrated in Figure 3, the sensing system configuration consists of the sensor head interfaced to a Stellarnet EPP2000C UV-VIS [5] mini-spectrometer, utilising a length of optical fibre. The spectrometer is interrogated utilising National Instruments LabView Virtual
Instrument (VI) software. The in-house designed VI also provides the data pre-processing require prior to application to the Matlab programme. The sample under test is illuminated via another optical fibre coupling the sensor head at one end to a tungsten halogen white light source, which emits light in the wavelength range 360nm to 2um.
2.3 Sensor Deployment
The sensing element is addressed using standard Plastic Optical Fibre (POF) cable. This will allow for the remote location of the sensor electronics to be housed away from the harsh environment encountered at the sensor head.
POF also offer much larger core diameters than other types of optical fibre. This enables a robust transmission of the signal (light) using low cost optical connectors. POF is also strong and offers relatively small losses when bent – this makes it ideal for this application where it will form part of a robust system required to continuously interrogate a water column for HABs.

3. Experimental Results and Analysis
3.1 Concentration tests
In order to investigate the absorption resolution of the current sensor system, two sample colour solutions (Blue and Red) were tested with each sample ranging in concentration from
20% to 0.002% (~ 20ppm). The Blue food colouring contained the following ingredients: water, acetic Acid, brilliant blue (E133) and carmoisine (E122), with the Red food colouring containing water, acetic acid, ponceau (E124) and sunset yellow (E110).
The samples were then measured using the experimental setup with both the peak absorptions and the resulting absorption for each sample recorded. It was noted at this stage that the sensor was able to distinguish that there was a level of absorption for all the samples down to a level of 20ppm. A plot of the absorption levels vs concentration is shown in Figure
4.
3.2 Exposure to various solutions.
The sensing system was exposed to a number of solutions of varying concentrations including Water, Saline, Yeast and Chlorophyll. The various solutions and concentrations are shown in Table 1.
Table 1: Measurement solutions
Solution Description
1
2
3
4
5
6
7
8
9
10
11
Saline
Chlorophyll, 12.5%
Chlorophyll, 25%
Chlorophyll, 50%
Chlorophyll, 100%
Water
Water with Yeast, .125%
Water with Yeast, 0.25%
Water with Yeast, 0.5%
Water with Yeast, 1%
Water with Yeast, 2%
For the initial part of the investigation, a number (400 each) of spectral readings were taken for the following lab based solutions: Water, Saline solution, 5 yeast concentrations (2%, 1%,
0.5%, 0.25% and 0.125%) in a Saline solution, and 4 Chlorophyll solutions. Figure 5 illustrates the raw data from the spectrometer for each of the samples under investigation.
Each spectrograph captured by the Stellarnet EPP2000C UV-VIS spectrometer has
2048 data samples, resulting in a possible maximum resolution of about 0. 0.75 nm, in the range between 190 and 850 nm [2] . However, for this investigation, only the visible range of the spectrum was utilised (400 –700 nm).
3.2.1 Principle Component Analysis:
Principal component analysis (PCA) involves a mathematical procedure that transforms a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables called principal components . Karhunen Loeve decomposition was applied to the data set comprising the spectral readings for each of the measurements under test [6]. This consisted of a total of 400 samples each for the 11 measurements investigated. By

calculating the eigenvalues of the covariance matrix of the dataset it is possible to choose the corresponding eigenvectors (forming the subspace) used to represent the data. The first three components are plotted in Figure 6 for the various saline-yeast concentrations.
The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible. PCA was carried out one each of the solutions investigated and the resulting plots are presented in Figure 7. The resulting PCA plots for the for the various chlorophll concentrations is shown in Figure 8.
4. Conclusions and Future Work
A robust optical fibre based Harmful Algea Bloom (HAB) sensing system has been developed which is capable of accurately classifying various chlorophyll, yeast and saline solutions. The optical sensing mechanism employed has demonstrated the ability to detect colour solutions down to 20ppm.
Principle Component Analysis (PCA) has been applied to the spectra recorded from the solutions under test, which has allowed for accurate classification of the solutions.
Future work will involve the comparison of the sensing systems performance to a calibrated chlorophyll sensor from the Marine Institute, along with the investigation of the systems performance in detecting concentrations of domoic acid.
Various sensing head designs will be investigated to evaluate their performance when exposed to organic matter resulting in the gradual build up of fouling, as d epending on the application and environment, sensors can be rendered useless by fouling in a few days, or they may operate for many months without significant problems.
References
[1] Confirmation of Domoic Acid production by pseudo-nitschia australis
(Bacillariophyceae) isolated from Irish waters by Caroline K. Cusack. Marine Institute,
Galway Technology Park, Parkmore, Galway, Ireland.
[2] New Approaches and Technologies for Observing Harmful Algal Blooms.
Oceanography Vol.18, No.2, June 2005
[3] http://www.ifremer.fr/envlit/documentation/dossiers/ciem/aindex.htm
[4] http://www.oceanoptics.com
[5] http://www.stellarnet-inc.com
[6] O’Farell, M, Lewis, E., Flanagan, C., Lyons, W.B., Jackman, N. “Combining principal component analysis with an artificial neural network to perform online quality assessment of food as it cooks in a largescale industrial oven” Sensors and actuators.
B, Chemical, vol. 107, no1, pp. 104-112, 2005

Figure 1 Map of Europe, highlighting ASP incidences.
Source: International council for the Exploration of the Sea (ICES)
Figure 2. Ocean Optics Dip Probe
Figure 3 Diagram of Experiment Set-up
Red and Blue dye absorption
120.00
100.00
80.00
60.00
40.00
20.00
0.00
20 10 5 1 0.1
0.006 0.004 0.002
Solution concentration (%)
Figure 4. Plot of absorption levels of red and Blue Dye

Figure.5 : Plot of all solutions under test
Figure 6: Plot of the various yeast concentrations Figure 7: Plot of the sub-space for the first 3 PCs for all solutions under test.
Figure 8: Plot of the various chlorophyll concentrations