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Open AccessArticle

Application of High-Throughput Screening Raman Spectroscopy (HTS-RS) for Label-Free Identification and Molecular Characterization of Pollen

1
Leibniz Institute of Photonic Technology, Albert Einstein Str. 9, 07745 Jena, Germany
2
Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
3
Department of Medical Engineering and Biotechnology, University of Applied Sciences – Jena, Carl-Zeiss Promenade 2, 07745 Jena, Germany
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(20), 4428; https://doi.org/10.3390/s19204428
Received: 29 August 2019 / Revised: 23 September 2019 / Accepted: 10 October 2019 / Published: 12 October 2019
(This article belongs to the Section Chemical Sensors)
Pollen studies play a critical role in various fields of science. In the last couple of decades, replacement of manual identification of pollen by image-based methods using pollen morphological features was a great leap forward, but challenges for pollen with similar morphology remain, and additional approaches are required. Spectroscopy approaches for identification of pollen, such as Raman spectroscopy has potential benefits over traditional methods, due to the investigation of the intrinsic molecular composition of a sample. However, current Raman-based characterization of pollen is complex and time-consuming, resulting in low throughput and limiting the statistical significance of the acquired data. Previously demonstrated high-throughput screening Raman spectroscopy (HTS-RS) eliminates the complexity as well as human interaction by incorporation full automation of the data acquisition process. Here, we present a customization of HTS-RS for pollen identification, enabling sampling of a large number of pollen in comparison to other state-of-the-art Raman pollen investigations. We show that using Raman spectra we are able to provide a preliminary estimation of pollen types based on growth habits using hierarchical cluster analysis (HCA) as well as good taxonomy of 37 different Pollen using principal component analysis-support vector machine (PCA-SVM) with good accuracy even for the pollen specimens sharing similar morphological features. Our results suggest that HTS-RS platform meets the demands for automated pollen detection making it an alternative method for research concerning pollen.
Keywords: Raman spectroscopy; high throughput screening; pollen detection, PCA-SVM, HCA; Raman spectroscopy; high throughput screening; pollen detection, PCA-SVM, HCA;
MDPI and ACS Style

Mondol, A.S.; Patel, M.D.; Rüger, J.; Stiebing, C.; Kleiber, A.; Henkel, T.; Popp, J.; Schie, I.W. Application of High-Throughput Screening Raman Spectroscopy (HTS-RS) for Label-Free Identification and Molecular Characterization of Pollen. Sensors 2019, 19, 4428.

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