Quantitative Approach for Simultaneous In Situ Profiling of Lignin, Cellulose, and Hemicellulose Using Confocal Raman Microscopy.

Abstract

Label-free confocal Raman microscopy (CRM) is characterized by its high chemical specificity, making it a promising tool for the in situ quantitative analysis of plant cell walls. However, the simultaneous quantification of components in Gramineous species remains challenging. This is due to the complex "lignin-ferulate-carbohydrate" cross-linked network, as well as the amorphous property of hemicellulose, specifically its weak Raman signal and severe spectral overlap with cellulose. To address these issues, this study developed a quantitative strategy that combines CRM with cosine similarity (CRM-CS). We acquired CRM mapping images of rice stems pretreated with acidified sodium chlorite (ASC) for varying durations. The CS values between the preprocessed cell wall spectra and reference spectra (milled wood lignin, microcrystalline cellulose, and xylan) were then calculated and used as quantitative indicators. The results showed that CS values allow for accurate profiling, exhibiting significant positive correlations with the contents of lignin, cellulose, and hemicellulose. These correlations follow piecewise linear relationships with high determination coefficients ( R 2 ) of 0.9728 and 0.9809 for lignin, 0.9592 and 0.9810 for cellulose, and 0.9004 and 0.9901 for hemicellulose. The CS-based method consistently outperforms the conventional characteristic peak intensity approach. In particular, it resolves the difficulty of accurately quantifying hemicellulose, a task where single-band methods typically underperform ( R 2 in situ simultaneous quantification of lignin, cellulose, and hemicellulose contents in rice stem cell walls during ASC pretreatment. Thus, the CRM-CS algorithm enables simultaneous in situ quantification in Gramineous cell walls, offering a valuable approach for crop breeding and the high-value utilization of lignocellulosic biomass.

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