Characterization of Stromatolite Organic Sedimentary Structure Based on Spectral Image Fusion.

This paper evaluates the potential application of Raman baselines in characterizing organic deposition. Taking the layered sediments (Stromatolite) formed by the growth of early life on the Earth as the research object, Raman spectroscopy is an essential means to detect deep-space extraterrestrial life. Fluorescence is the main factor that interferes with Raman spectroscopy detection, which will cause the enhancement of the Raman baseline and annihilate Raman information. The paper aims to evaluate fluorescence contained in the Raman baseline and characterize organic sedimentary structure using the Raman baseline. This study achieves spectral image fusion combined with mapping technology to obtain high spatial and spectral resolution fusion images. To clarify that the fluorescence of organic matter deposition is the main factor causing Raman baseline enhancement, 5041 Raman spectra were obtained in the scanning area of 710 µm × 710 µm, and the correlation mechanism between the gray level of the light-dark layer of the detection point and the Raman baseline was compared. The spatial distribution of carbonate minerals and organic precipitations was detected by combining mapping technology. In addition, based on the BI-IHS algorithm, the spectral image fusion of Raman fluorescence mapping and reflection micrograph, polarization micrograph, and orthogonal polarization micrograph are realized, respectively. A fusion image with high spectral resolution and high spatial resolution is obtained. The results show that the Raman baseline can be used as helpful information to characterize stromatolite organic sedimentary structure.

Elastic Particle Swarm Optimization for MarSCoDe Spectral Calibration on Tianwen-1 Mars Rover.

China's Tianwen-1 Mars rover carries a laser-induced breakdown spectroscopy (LIBS) payload named MarSCoDe to analyze the mineral and rock composition on Mars. MarSCoDe is expected to experience a wide working temperature range of about 100 °C, which will lead to a spectral shift of up to ∼40 pixels (∼8.13 nm). Even worse, drastic changes in temperature and environment may cause a loss or increase of some spectral lines of an on-board calibration Ti target. An elastic particle swarm optimization (PSO) approach is proposed to fulfill the on-board spectral calibration of MarSCoDe under this harsh condition. Through establishing a standard wavelength set (SWS) and an individual particle wavelength set (PWS), and further elastically selecting a part of PWS to compare with SWS, the problem of spectral shift and number mismatch can be solved gradually with the evolution of the particle swarm. Some tests of standard lamps and Ti with MarSCoDe, placed in a Mars simulation environment chamber (MSEC) in a temperature range of 70 °C, were completed. Compared with the standard spectrum of the Ti target (obtained at 20 °C), the spectral shifts of the first, second, and third channels are approximately 0.33 nm (5 pixels), 0.85 nm (6.4 pixels), and 8.09 nm (39.8 pixels), respectively, at -40 °C before correction; after PSO correction, the spectral shifts are greatly reduced to up to 0.015 nm, and specially for the 626.28 nm line, the spectral shift is reduced from 8.09 nm to about 0 nm. Experimental results demonstrate that the PSO-based approach can not only correct the on-board spectral shift but also solve the number mismatch of spectral lines of MarSCoDe in the harsh working environment of Mars. Further, it can be extended to the on-board calibration of other spectral payloads for deep space exploration.

Spectral detection technology of vegetable oil: Spectral analysis of porphyrins and terpenoids.

In this paper, the existence of porphyrins and terpenoids in different vegetable oils and their spectral characterization techniques are reported. The classification of pure vegetable oils was realised by principal component analysis - support vector machine (PCA-SVM) model. The absorption spectra, Raman spectra, fluorescence spectra and supercontinuum spectra of 8 kinds of pure vegetable oils were studied, and the effects of oil types and processing technology on spectral differences were analysed. The results showed that the fingerprint information of 4 kinds of spectral techniques mainly came from chlorophyll and ß-carotene in vegetable oil. The extra virgin olive oil (EVOO) got by physical cold pressing technology had the most porphyrins and terpenoids content and the strongest activity. Therefore, the spectral characterization of porphyrins and terpenoids in vegetable oil can guide the regulation of the processing technology of vegetable oil and realise the qualitative and quantitative analysis of vegetable oil.

Rapid detection of Chinese-specific peony seed oil by using confocal Raman spectroscopy and chemometrics.

Peony seed oil (PSO) is a new woody nut oil which is unique to China. Its unsaturated fatty acids are over 90% and are rich in α - linolenic acid. Although the PSO industry is in its infancy, it is bound to become a top vegetable oil food material because of its own advantages. The potential high commercial profit of its adulteration with cheap vegetable oil will be an important factor hindering the healthy development of PSO industry. It is of great significance to study the adulteration of PSO for preventing large-scale adulteration. In this study, the qualitative and quantitative analysis of PSO was realised based on Raman spectroscopy combined with chemometrics analysis, and the fatty acid composition of PSO was analysed according to Raman characteristic peaks. The technology can be applied to routine analysis and quality control of PSO.

Dynamic confocal Raman spectroscopy of flowing blood in bionic blood vessel.

How to quickly and safely identify blood species has always been an urgent problem for scientists. Smear test method has the risk of blood contamination, and the blood itself may carry some unknown viruses or pathogens, which will bring health risks to the testing personnel. Therefore, in order to meet the urgent needs of rapid and safe detection of blood, a technology which can detect dynamic confocal Raman spectroscopy of flowing blood in bionic blood vessel was proposed. The blood, which was sealed in the bionic blood vessel, flowed through the focus gaze area of laser by the microfluidic pump, to detect the dynamic blood Raman spectrum. Human blood and cattle blood were selected as experimental objects, and the experiments were carried out under the same parameters. Combined with PCA-LDA (principal component analysis and linear discriminate analysis) classification model, the predictive classification of the two species without error recognition was realized. The hidden weak Raman signals were mined by derivative spectra, and the fundamental differences of Raman spectra of two species were compared. Then the biochemical information that caused the differences was also analyzed. The results show the method can meet the detection requirements of sealed blood, and the Raman spectra of flowing blood is more representative than those of static blood.