Date of Award




Document Type

Master's Thesis

Degree Name

Master of Science (MS)


Department of Chemistry

Content Description

1 online resource (ix, 67 pages) : color illustrations.

Dissertation/Thesis Chair

Rabi A Musah

Committee Members

Ting Wang


Corals, High resolution spectroscopy, Coral communities, Coral reef conservation, Mass spectrometry

Subject Categories

Analytical Chemistry


Coral reefs are one of the most biologically diverse ecosystems, and the accurate identification of the species is essential for diversity assessment, species delimitation and conservation. Current species and genus determination approaches are time consuming, resource intensive and can be highly subjective. To explore the hypothesis that the small molecule profiles of coral are species and genus specific, and can be used as a rapid tool to catalogue, classify and identify coral genera and species, the small-molecule chemical fingerprints of coral belonging to the species Acanthastrea echinata, Catalaphyllia jardinei, Duncanopsammia axifuga, Echinopora lamellosa, Euphyllia divisa, Euphyllia paraancora, Euphyllia paradivisa, Galaxea fascicularis, Herpolitha limax, Montipora confusa, Monitpora digitata, Montipora setosa, Pachyseris rugosa, Pavona cactus, Plerogyra sinuosa, Pocillopora acuta, Seriatopora hystrix, Sinularia dura, Turbinaria peltata, Turbinaria reniformis, Xenia elongata and Xenia umbellata were generated using direct analysis in real time-high resolution mass spectrometry (DART-HRMS). It is demonstrated here that the mass spectrum-derived small molecule profiles for coral of different genera and different species within a genus are distinct, even when they contain overlapping mass spectral characteristics. The observed intraspecies and intragenus similarities, combined with the interspecies and intergenus differences, were exploited using multivariate statistical analysis processing of the DART-HRMS data, to enable rapid genus- and species-level differentiation for coral identification. Coral samples were analyzed in their native form with no sample preparation required, making the approach rapid and efficient. The resulting spectra, which were acquired in positive ion mode, were subjected to kernel discriminant analysis (KDA) which furnished accurate species and genus differentiation of the coral. Leave-one-out cross-validation (LOOCV) was carried out to determine the classification accuracy of each model and confirm that this approach can be used for coral genus and species identification. Depending on the genus, the prediction accuracy ranged from 86.67% to 97.33% on the genus-level and 94.44% to 100.00% on the species-level. The advantages and application of the statistical analysis to DART-HRMS derived coral chemical signatures for genus- and species-level differentiation are discussed. The results provide a foundation for the establishment of a database of mass spectra of coral genera and species that can be used for rapid genus and species identification in the field.