结合拉曼成像与多变量分析以可视化植物细胞壁中的木质素、纤维素和半纤维素。
Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall.
作者信息
Zhang Xun, Chen Sheng, Xu Feng
机构信息
Beijing Key Laboratory of Lignocellulosic Chemistry, Beijing Forestry University.
Beijing Key Laboratory of Lignocellulosic Chemistry, Beijing Forestry University;
出版信息
J Vis Exp. 2017 Jun 10(124):55910. doi: 10.3791/55910.
The application of Raman imaging to plant biomass is increasing because it can offer spatial and compositional information on aqueous solutions. The analysis does not usually require extensive sample preparation; structural and chemical information can be obtained without labeling. However, each Raman image contains thousands of spectra; this raises difficulties when extracting hidden information, especially for components with similar chemical structures. This work introduces a multivariate analysis to address this issue. The protocol establishes a general method to visualize the main components, including lignin, cellulose, and hemicellulose within the plant cell wall. In this protocol, procedures for sample preparation, spectral acquisition, and data processing are described. It is highly dependent upon operator skill at sample preparation and data analysis. By using this approach, a Raman investigation can be performed by a non-specialist user to acquire high-quality data and meaningful results for plant cell wall analysis.
拉曼成像在植物生物质领域的应用日益广泛，因为它能够提供关于水溶液的空间和成分信息。该分析通常不需要进行大量的样品制备；无需标记即可获得结构和化学信息。然而，每张拉曼图像都包含数千个光谱；在提取隐藏信息时会遇到困难，尤其是对于具有相似化学结构的成分。这项工作引入了多变量分析来解决这一问题。该方案建立了一种通用方法，用于可视化植物细胞壁内的主要成分，包括木质素、纤维素和半纤维素。在本方案中，描述了样品制备、光谱采集和数据处理的步骤。它高度依赖于操作人员在样品制备和数据分析方面的技能。通过使用这种方法，非专业用户也可以进行拉曼研究，以获取用于植物细胞壁分析的高质量数据和有意义的结果。
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