Assessment of Lignocellulosic Biomass Using Analytical Spectroscopy: an Evolution to High-Throughput Techniques

Abstract

Lignocellulosic biomass has been proposed as an option for reducing global dependence on nonrenewable energy sources, such as oil. Selection and development of biomass feedstocks that efficiently yield the maximum fuel or biomaterial requires the availability of reliable methods for compositional and structural characterization of plant material. Many standard methods for biomass analysis are laborious and slow, and employ a variety of harsh reagents requiring some degree of remediation. The use of simpler and more rapid spectroscopic methods has proved invaluable in analyzing biomass. In the twenty-first century, researchers have employed techniques such as Raman, mid-infrared, and near-infrared spectroscopy for a wide range of applications in endeavors to further understand biofuel feedstocks. While many methods remain time consuming and expensive, a growing interest in high-throughput spectroscopic techniques has provided faster and larger scale feedstock screening for desirable traits. This review seeks to provide an overview of both high-throughput techniques and those requiring longer analysis times but still providing abundant qualitative and quantitative data. While applications of these instrumental methods have been researched for decades, more recent developments will be discussed here.

Comprehensive Characterization of Napier Grass as a Feedstock for Thermochemical Conversion

“…The remaining components, mainly hemicellulose, lignin and extractives in the material are approximated to belong to the amorphous phase since no larger crystals are formed by these components [20,24]. The value of crystallinity index obtained using Equation (1) can be attributed to different hydroxyl group (alcohol/phenol) stretching vibrations [25][26][27][28]. The band at 2937 cm could be a result of aliphatic saturated C-H stretching vibrations (asymmetric and symmetric methyl and methylene stretching groups) from extractives and lignin components of the biomass since fatty acid methyl esters and phenolic acid methyl esters, have methyl and methylene groups [29][30][31][32].…”

“…The band at 2937 cm could be a result of aliphatic saturated C-H stretching vibrations (asymmetric and symmetric methyl and methylene stretching groups) from extractives and lignin components of the biomass since fatty acid methyl esters and phenolic acid methyl esters, have methyl and methylene groups [29][30][31][32]. In the fingerprint region, the band at 1600 cm −1 may be due to the ring-conjugated C=C bonds of lignin while the band observed at 1200 cm −1 may be an indication of O-H bending in the cellulose and hemicellulose components of the biomass [5,25,26,28,[33][34][35][36]. The frequency at 1,050 cm −1 may be ascribed to C-O, and C=C, and C-C-O stretching in cellulose, hemicelluloses and lignin [25,28,34,36] while the bands between 800 and 600 cm −1 may be attributed to aromatic C-H bending vibrations from the lignin in the samples [5,35,36].…”

“…In the fingerprint region, the band at 1600 cm −1 may be due to the ring-conjugated C=C bonds of lignin while the band observed at 1200 cm −1 may be an indication of O-H bending in the cellulose and hemicellulose components of the biomass [5,25,26,28,[33][34][35][36]. The frequency at 1,050 cm −1 may be ascribed to C-O, and C=C, and C-C-O stretching in cellulose, hemicelluloses and lignin [25,28,34,36] while the bands between 800 and 600 cm −1 may be attributed to aromatic C-H bending vibrations from the lignin in the samples [5,35,36]. Thermogravimetric analysis revealed thermal decomposition of various structural components of NGS, NGT and NGL (Figure 3).…”

High-Throughput Profiling of the Fiber and Sugar Composition of Sugarcane Biomass

“…In fiber characterization, a high-throughput method to assess and screen a large number of lignocellulosic feedstocks is required to replace the expensive, time-consuming, and tedious chemical composition analysis techniques. To date, there are a range of available methods for assessment of lignocellulosic biomass reviewed in [13]. Among the available platforms, near-infrared (NIR) spectroscopy-based methods have been used widely for assessing biomass since they offer nondestructive analysis (reducing hazardous risks and allowing samples to be re-used for other purposes), a relatively low cost per sample and require minimal technical skill reviewed in [13][14][15].…”

“…To date, there are a range of available methods for assessment of lignocellulosic biomass reviewed in [13]. Among the available platforms, near-infrared (NIR) spectroscopy-based methods have been used widely for assessing biomass since they offer nondestructive analysis (reducing hazardous risks and allowing samples to be re-used for other purposes), a relatively low cost per sample and require minimal technical skill reviewed in [13][14][15]. To develop NIR spectroscopic models, paired spectra and reference values (obtained through traditional analytical methods) are combined using chemometric technique partial least squares (PLS) regression.…”