Improving preservation state assessment of carbonate microfossils in paleontological research using label-free stimulated Raman imaging

Raman Spectra and Ancient Life: Vibrational ID Profiles of Fossilized (Bone) Tissues

Raman micro-spectroscopy is a non-destructive and non-contact analytical technique that combines microscopy and spectroscopy, thus providing a potential for non-invasive and in situ molecular identification, even over heterogeneous and rare samples such as fossilized tissues. Recently, chemical imaging techniques have become an increasingly popular tool for characterizing trace elements, isotopic information, and organic markers in fossils. Raman spectroscopy also shows a growing potential in understanding bone microstructure, chemical composition, and mineral assemblance affected by diagenetic processes. In our lab, we have investigated a wide range of different fossil tissues, mainly of Mesozoic vertebrates (from Jurassic through Cretaceous). Besides standard spectra of sedimentary rocks, including pigment contamination, our Raman spectra also exhibit interesting spectral features in the 1200-1800 cm-1 spectral range, where Raman bands of proteins, nucleic acids, and other organic molecules can be identified. In the present study, we discuss both a possible origin of the observed bands of ancient organic residues and difficulties with definition of the specific spectral markers in fossilized soft and hard tissues.

Porosity of the porous carbonate rocks in the Jingfengqiao-Baidiao area based on finite automata

This study is based on the processing of computed microtomography images of rock samples. In this study, a finite automation is constructed using the grey value, red-green-blue (RGB) value and Euler number of polarized images of carbonate rocks from the Jingfengqiao-Baidiao area. The finite automaton is used to perform black and white binary processing of the polarized images of the carbonate rocks. The porosity of the carbonate rock is calculated based on the black and white binarization processing results of the polarized images of the carbonate rocks. The obtained porosity is compared with the carbonate porosity obtained by use of the traditional carbonate research method. When the two porosities are close, the image processing threshold of the finite automata is considered to be credible. Based on the finite automata established using the image processing threshold, the black and white binary images of the polarized images of the carbonate rocks are used to establish a rock pore image using ImageJ2X. The polarized images of the carbonate rocks are classified according to their RGB values using the finite automata for the porosity classification, and the obtained images are used as textures to paste onto a cube to construct a three-dimensional data model of the carbonate rocks. This study also uses 16S rDNA analysis to verify the formation mechanism of the carbonate pores in the Jingfengqiao-Baidiao area. The results of the 16S rDNA analysis show that the pores in the carbonate rocks in the Jingfengqiao-Baidiao area are closely related to microorganisms, represented by denitrifying bacteria.