Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains

Abstract

Fourier-transform infrared (FTIR) spectroscopy enables the chemical characterization and identification of pollen samples, leading to a wide range of applications, such as paleoecology and allergology. This is of particular interest in the identification of grass (Poaceae) species since they have pollen grains of very similar morphology. Unfortunately, the correct identification of FTIR microspectroscopy spectra of single pollen grains is hindered by strong spectral contributions from Mie scattering. Embedding of pollen samples in paraffin helps to retrieve infrared spectra without scattering artifacts. In this study, pollen samples from 10 different populations of five grass species (Anthoxanthum odoratum, Bromus inermis, Hordeum bulbosum, Lolium perenne, and Poa alpina) were embedded in paraffin, and their single grain spectra were obtained by FTIR microspectroscopy. Spectra were subjected to different preprocessing in order to suppress paraffin influence on spectral classification. It is shown that decomposition by non-negative matrix factorization (NMF) and extended multiplicative signal correction (EMSC) that utilizes a paraffin constituent spectrum, respectively, leads to good success rates for the classification of spectra with respect to species by a partial least square discriminant analysis (PLS-DA) model in full cross-validation for several species. PLS-DA, artificial neural network, and random forest classifiers were applied on the EMSC-corrected spectra using an independent validation to assign spectra from unknown populations to the species. Variation within and between species, together with the differences in classification results, is in agreement with the systematics within the Poaceae family. The results illustrate the great potential of FTIR microspectroscopy for automated classification and identification of grass pollen, possibly together with other, complementary methods for single pollen chemical characterization.

Attenuated Total Reflection (ATR) Micro-Fourier Transform Infrared (Micro-FT-IR) Spectroscopy to Enhance Repeatability and Reproducibility of Spectra Derived from Single Specimen Organic-Walled Dinoflagellate Cysts

“…Other micro-FT-IR studies on micro-organisms generally collect a minimum of three replicates. 70–72 Our experiences learn that, in general, there is some intraspecific variation in dinocyst spectra from the same sample, but this tends to be small if the cysts are clean. Usually, three to five spectra on different cysts from the same species are sufficient to capture most of this variation.…”

“…30,79,81–84 and can result in better classification models afterwards. 72,85–93 Since derivation enhances the noise level of spectra, it is only advisable to use on high S/N data.…”

Grass pollen morphology investigation as a basis for monitoring of allergenic biological particles in an automatic mode

“…This is because Poaceae family pollen is mostly spherical in size and has one pore. Therefore, scanning electron microscopy [3,14] and spectroscopy [7] are used for its in-depth study. The latter technique can also be used to detect pollen automatically.…”

A Novel Muscle Synergy Extraction Method Used for Motor Function Evaluation of Stroke Patients: A Pilot Study

“…NMF, which was first proposed by Lee and Seung [ 35 , 36 ], is usually used to reduce data dimension. Because of its nonnegative constraint, NMF is also applied to analyze medical [ 43 ] and space object [ 44 ] data.…”