No abstract

Abstract70 species of grasses family (Poaceae), coming from genera: Agrostis, Alopecurus, Anthoxanthum, Apera, Arrhenatherum, Avena, Brachypodium, Briza, Bromus, Calamagrostis, Corynephorus, Cynosurus, Dactylis, Danthonia, Deschampsia, Digitaria, Echinochloa, Elymus, Eragrostis, Festuca, Glyceria, Helictotrichon, Hierochloe, Holcus, Hordeum, Koeleria, Leymus, Lolium, Milium, Molinia, Nardus, Panicum, Phalaris, Phleum, Phragmites, Poa, Saccharum and Setaria, collected mostly from natural stands in Poland during 2020 season, were subjected to GC-MS fingerprinting of headspace volatile fraction above dried material. Obtained mass spectrometry data were analyzed by means of principal component analysis (PCA) and hierarchical cluster analysis (HCA). Five species: Glyceria maxima (Hartm.) Holmb., Lolium multiflorum Lam., Hordeum jubatum L., Bromus tectorum L. and Bromus secalinus L. were identified as outliers, which is consistent with our earlier analysis by thin layer chromatography. These species deserve further look and their outliance is orthogonal to coumarin content, which was independently observed for odorant species of grasses.

The advantages of hyperspectral imaging in videodensitometry are presented and discussed with the example of extracts from 70 Polish grasses. An inexpensive microscope camera was modified to cover the infrared spectrum range, and then 11 combinations of illumination (254 nm, 366 nm, white light), together with various filters (no filter, IRCut, UV, cobalt glass, IR pass), were used to register RGB HDR images of the same plate. It was revealed that the resulting 33 channels of information could be compressed into 5–6 principal components and then visualized separately as grayscale images. We also propose a new approach called principal component artificial coloring of images (PCACI). It allows easy classification of chromatographic spots by presenting three PC components as RGB channels, providing vivid spots with artificial colors and visualizing six principal components on two color images. The infrared region brings additional information to the registered data, orthogonal to the other channels and not redundant with photos in the visible region. This is the first published attempt to use a hyperspectral camera in TLC and it can be clearly concluded that such an approach deserves routine use and further attention.