Application of Fourier-transform infrared technology to the classification of harmful algal blooms (HABS)

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dc.contributor.author Kenne, Gabriel Jacob
dc.date.accessioned 2013-08-06T12:29:01Z
dc.date.available 2013-08-06T12:29:01Z
dc.date.issued 2013-08-06
dc.identifier.uri http://hdl.handle.net/2097/16188
dc.description.abstract Cyanobacteria are Gram-negative photosynthetic bacteria capable of producing toxins responsible for morbidity and mortality in humans and domestic animals. Many are capable of forming concentrated blooms that impact the environment by limiting the growth of sub-surface plants and phytoplankton. Harmful algal blooms (HABs) are also capable of producing multiple types of toxins, creating a potential hazard to recreational water users and animals drinking water from or near a bloom. Characterization of HABs is necessary to prevent these human and animal exposures and includes classifying of the type of cyanobacteria present and whether or not they are capable of toxin production, and the exact type of cyanotoxin that is actually present in bloom. Current methods used to classify cyanobacteria and cyanotoxins include microscopy, bioassays, ELISA, PCR, HPLC, and LC/MS. All of these methods, however, have limitations that include time, labor intensity, or cost. Fourier-Transform Infrared Spectroscopy (FTIR) is another potential tool for cyanobacterial classification that is not limited by these factors. To examine the practicality of this method, library screening with default software algorithms was performed on diagnostic samples received at the Kansas State University Veterinary Diagnostic Lab, followed by PCA of samples meeting minimum quality requirements to produce cluster analyses and dendrograms. Both spectrometers and software packages used were successful at distinguishing cyanobacteria from green algae in clean samples with 89.13% agreement. PCA resulted in clear classification of cyanobacteria or green algae demonstrated by a large order of magnitude difference produced by average Euclidian distance dendrograms. While this method is only capable of differentiating cyanobacteria from green algae or other aquatic environmental constituents, its simple, rapid use and low cost make it a beneficial screening tool when coupled with toxin-detection methods to characterize HABs. en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Cyanobacteria en_US
dc.subject Harmful algal bloom en_US
dc.subject Environmental public health en_US
dc.subject Fourier-transform infrared spectroscopy en_US
dc.title Application of Fourier-transform infrared technology to the classification of harmful algal blooms (HABS) en_US
dc.type Thesis en_US
dc.description.degree Master of Public Health en_US
dc.description.level Masters en_US
dc.description.department Department of Diagnostic Medicine/Pathobiology en_US
dc.description.advisor Deon Van der Merwe en_US
dc.subject.umi Environmental Health (0470) en_US
dc.subject.umi Public Health (0573) en_US
dc.date.published 2013 en_US
dc.date.graduationmonth August en_US


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