A data analytic approach was developed to determine the unique signatures of volatile organic compounds (VOCs) emitted from Gracilaria tikvahiae and Gracilaria vermiculophylla species of macroalgae from the coastal bays of the Delmarva Peninsula. The headspace air samples were collected from these two species, and analyzed using multi-dimensional gas chromatography/mass spectrometry (GC/MS) to achieve a better separation of peaks in chromatograms. The peaks of interest were identified by comparing chromatograms of algal and control samples. The peak location and intensity in the chromatograms are used as the feature elements that define a VOC signature vector. Multivariate statistical analysis of the species’ chromatograms clearly demonstrates that the VOC signatures of the two species can be uniquely discriminated from each other using Principal Component Analysis (PCA), with just the first two principal components capturing more than 98% of the variance in the chromatograms. The two species are found to cluster into individual groups that are well separated from each other, and lie outside of each other’s 95% confidence intervals. The approach of classifying macroalgae VOC signatures, as demonstrated in this study, can be exploited for other marine algae species. The determination of a unique VOC signature for each macroalgal species lays a foundation for developing a sensor technology for monitoring the VOCs associated with certain macroalgae species of interest, to possibly detect certain events such as marine algae blooms.

Determination of volatile organic compound signatures for species of Gracilaria from the coastal bays of the Delmarva Peninsula

ACS Spring Meeting 2021

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