Lignin content and distribution in alkali pretreated corn straw based on Fourier transform infrared microspectroscopic imaging

Abstract: Lignin is one of the major components of plant cell wall, and it can provide sufficient strength and hardness to plant cells while avoiding biological damage and water erosion. In recent years, studies on the lignification process and delignification of plant tissues have received extensive attention from scholars. A large number of studies have been carried out to determine the removal of lignin after pretreatment by conventional wet chemical analysis. The lignin content and distribution of biomass resources such as crop straw directly affect its conversion and utilization efficiency. It's meaningful to develop multi-scale and in situ analysis to identify lignin distribution and quantification on delignified plant cell wall for bio-resource commercial utilization. In this paper, we studied an in situ analysis method to visualize changing of lignin distribution in the alkali pretreated corn straw internodal transverse section based on Fourier transform infrared (FTIR) microspectroscopic imaging, with a fast non-negativity-constrained least squares (fast NNLS) fitting. We collected the middle of the 6th node of fresh jointing stage corn straw. Corn straws were pretreated for series of times (0 , 5 , 30, 60 min) by 2% NaOH solution at 100℃. A paraffin embedding method was used to produce 18 μm-thick transverse sections for each sample. Then, the sections were transferred onto ZnS windows for FTIR microspectroscopic imaging. We acquired FTIR spectra of major components of corn straw for fast NNLS fitting. We also milled whole straws to 0.069 mm and pretreated in the same condition as sections to determine structure carbohydrate. The data of FTIR microspectroscopic images and FTIR spectra were processed by Savizky?Golay smoothing within 5 points, SNV, and automatic Whittaker filter baseline to correct baseline and offset. K-means cluster algorithm was used to distinguish various tissues including epidermis, vascular bundles and parenchyma cells. Fast NNLS fitting was carried out to calculate the lignin concentrations in pixels. For comparison between different pretreated times, lignin concentration in pixels was calibrated according to the sum of content of all components based on laboratory analysis. The lignin content by laboratory analysis decreased with the increasing of the pretreated time, and the lignin degradation rate was larger at the initial stage of the reaction. The lignin content in the epidermis, vascular bundle and parenchyma cells of the samples showed a decreasing trend with the increasing of pretreatment time, and the trends of lignin changing in the three tissues were consistent with the trend of laboratory analysis. By comparing laboratory analysis with fast NNLS fitting results, the results show that the FTIR microspectroscopic imaging combined with fast NNLS could locate and quantify the distribution of lignin in various tissues, and the trend of lignin changing calculated by fast NNLS fitting is the same as the laboratory chemical analysis results. The study demonstrated that FTIR microspectroscopic imaging combined with fast NNLS fitting could be successfully applied to in situ visualize lignin distribution within corn straw pretreatment. The characterization method provides reference for the lignin research of corn stover pretreatment and the study of lignin degradation during straw pretreatment.