A Novel Pre-Processing Algorithm Based on the Wavelet Transform for Raman Spectrum

Xi, Yang; Li, Yuee; Duan, Zhizhen; Yang, Lǜ

doi:10.1177/0003702818789695

Cited by 22 publications

(8 citation statements)

References 29 publications

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“…1 . Firstly, five different pretreatment methods SNV, 42 multivariate scatterincorrection (MSC), 43 first derivative (D1st), 44 wavelet transform (WT) 45 and WT-SNV were used for preprocessing raw spectral data to reduce the interference of instrument noise, environmental noise, and experimental error on raw spectra. In data processing, 10-fold cross-validation (10-fold CV) and R 2 were applied to optimize the parameter of preprocessing methods.…”

Section: Methodsmentioning

confidence: 99%

Quantitative analysis of phenanthrene in soil by fluorescence spectroscopy coupled with the CARS-PLS model

Tang

et al. 2023

RSC Adv.

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Section: Methodsmentioning

confidence: 99%

Quantitative analysis of phenanthrene in soil by fluorescence spectroscopy coupled with the CARS-PLS model

Tang

et al. 2023

RSC Adv.

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“…In combination with the reconstruction schematic diagram of WT in Fig. 2, it could be concluded that D6 extracts the characteristic information of the raw spectrum through eliminating high-frequency random noise and low-frequency fluorescent backgrounds [32,53,54].…”

Section: Quantitative Classifier and Chemical Micro-imaging With Fingmentioning

confidence: 99%

Quantitative visualization of subcellular lignocellulose revealing the mechanism of alkali pretreatment to promote methane production of rice straw

Sha

Xia

et al. 2020

Biotechnol Biofuels

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Background: As a renewable carbon source, biomass energy not only helps in resolving the management problems of lignocellulosic wastes, but also helps to alleviate the global climate change by controlling environmental pollution raised by their generation on a large scale. However, the bottleneck problem of extensive production of biofuels lies in the filamentous crystal structure of cellulose and the embedded connection with lignin in biomass that leads to poor accessibility, weak degradation and digestion by microorganisms. Some pretreatment methods have shown significant improvement of methane yield and production rate, but the promotion mechanism has not been thoroughly studied. Revealing the temporal and spatial effects of pretreatment on lignocellulose will greatly help deepen our understanding of the optimization mechanism of pretreatment, and promote efficient utilization of lignocellulosic biomass. Here, we propose an approach for qualitative, quantitative, and location analysis of subcellular lignocellulosic changes induced by alkali treatment based on label-free Raman microspectroscopy combined with chemometrics. Results: Firstly, the variations of rice straw induced by alkali treatment were characterized by the Raman spectra, and the Raman fingerprint characteristics for classification of rice straw were captured. Then, a label-free Raman chemical imaging strategy was executed to obtain subcellular distribution of the lignocellulose, in the strategy a serious interference of plant tissues' fluorescence background was effectively removed. Finally, the effects of alkali pretreatment on the subcellular spatial distribution of lignocellulose in different types of cells were discovered. Conclusions: The results demonstrated the mechanism of alkali treatment that promotes methane production in rice straw through anaerobic digestion by means of a systemic study of the evidence from the macroscopic measurement and Raman microscopic quantitative and localization two-angle views. Raman chemical imaging combined with chemometrics could nondestructively realize qualitative, quantitative, and location analysis of the lignocellulose of rice straw at a subcellular level in a label-free way, which was beneficial to optimize pretreatment for the improvement of biomass conversion efficiency and promote extensive utilization of biofuel.

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“…With its help, the measured signal is decomposed into components of relatively simple shapes, which are subject to scaling and shifting. It appears especially when there is significant noise in the measured spectra [ 22 , 23 , 24 ]. Its main applications are to replace very popular derivative spectrophotometry methods [ 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

A Wavelet Derivative Spectrum Length Method of TFBG Sensor Demodulation

Cięszczyk

Skorupski

Wawrzyk

et al. 2023

Sensors

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Fibre optic sensors using tilted fibre Bragg grating (TFBG) have high sensitivity for refractive index measurements. In order to achieve good metrological parameters of the measurement, an appropriate method of spectrum demodulation must be used. The method proposed in the article is an improvement of the spectral length algorithm. The spectral length parameter is treated as the sum of the derivative filter responses. In the original version, the first difference of spectrum elements was used, while this article proposes to use the wavelet transform to calculate the numerical derivative approximation. The advantage of this solution is an easy way to select the level of smoothing filtration by changing the scale parameter. The derivation is appropriate even for a relatively low signal-to-noise level. The approximation of the spectral length by the derivative calculated using the wavelet transform eliminates the high-frequency noise of the optical signal. The absolute value of determined spectral derivatives after significant smoothing can be used to estimate the wavelength of the decay of modes. After analyzing experimental data and performing calculations, it turns out that this is a linear method with better resolution than the contour length algorithm.

show abstract

A Novel Pre-Processing Algorithm Based on the Wavelet Transform for Raman Spectrum

Cited by 22 publications

References 29 publications

Quantitative analysis of phenanthrene in soil by fluorescence spectroscopy coupled with the CARS-PLS model

Quantitative analysis of phenanthrene in soil by fluorescence spectroscopy coupled with the CARS-PLS model

Quantitative visualization of subcellular lignocellulose revealing the mechanism of alkali pretreatment to promote methane production of rice straw

A Wavelet Derivative Spectrum Length Method of TFBG Sensor Demodulation

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