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Evaluating lignocellulosic biomass, its derivatives, and downstream products with Raman spectroscopy.

Lupoi JS, Gjersing E, Davis MF - Front Bioeng Biotechnol (2015)

Bottom Line: Hydrolysis and fermentation products, such as glucose and ethanol, can be quantified off-, at-, or on-line.Raman imaging has enabled researchers to develop a visual understanding of reactions, such as different pretreatment strategies, in real-time, while also providing integral chemical information.This review provides an overview of what Raman spectroscopy is, and how it has been applied to the analysis of whole lignocellulosic biomass, its derivatives, and downstream process monitoring.

View Article: PubMed Central - PubMed

Affiliation: Oak Ridge National Laboratory, BioEnergy Science Center , Oak Ridge, TN , USA ; National Renewable Energy Laboratory, National Bioenergy Center , Golden, CO , USA.

ABSTRACT
The creation of fuels, chemicals, and materials from plants can aid in replacing products fabricated from non-renewable energy sources. Before using biomass in downstream applications, it must be characterized to assess chemical traits, such as cellulose, lignin, or lignin monomer content, or the sugars released following an acid or enzymatic hydrolysis. The measurement of these traits allows researchers to gage the recalcitrance of the plants and develop efficient deconstruction strategies to maximize yields. Standard methods for assessing biomass phenotypes often have experimental protocols that limit their use for screening sizeable numbers of plant species. Raman spectroscopy, a non-destructive, non-invasive vibrational spectroscopy technique, is capable of providing qualitative, structural information and quantitative measurements. Applications of Raman spectroscopy have aided in alleviating the constraints of standard methods by coupling spectral data with multivariate analysis to construct models capable of predicting analytes. Hydrolysis and fermentation products, such as glucose and ethanol, can be quantified off-, at-, or on-line. Raman imaging has enabled researchers to develop a visual understanding of reactions, such as different pretreatment strategies, in real-time, while also providing integral chemical information. This review provides an overview of what Raman spectroscopy is, and how it has been applied to the analysis of whole lignocellulosic biomass, its derivatives, and downstream process monitoring.

No MeSH data available.


Multi-peak curve fitting results for (A) 100 mg/mL xylose; (B) 120 mg/mL glucose; and (C) a 60 mg/mL glucose and 50 mg/mL xylose mixture in a soaking in aqueous ammonia hydrolysis broth. The residual between the multi-peak fit and the experimental data is shown in the top panel. The residual is of the same order of magnitude as the spectral noise. The experimental spectra are shown in the middle panel (thicker line) and the fit results are shown in the bottom panel (thinner line) [reprinted with permission from Elsevier, Shih et al. (2011)].
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Figure 4: Multi-peak curve fitting results for (A) 100 mg/mL xylose; (B) 120 mg/mL glucose; and (C) a 60 mg/mL glucose and 50 mg/mL xylose mixture in a soaking in aqueous ammonia hydrolysis broth. The residual between the multi-peak fit and the experimental data is shown in the top panel. The residual is of the same order of magnitude as the spectral noise. The experimental spectra are shown in the middle panel (thicker line) and the fit results are shown in the bottom panel (thinner line) [reprinted with permission from Elsevier, Shih et al. (2011)].

Mentions: The quantitation of glucose, xylose, and ethanol in complex matrices illustrated other novel applications of NIR, dispersive Raman spectroscopy (Shih and Smith, 2009; Shih et al., 2011). Raman methods were juxtaposed to those obtained using UV/visible (UV/VIS) spectrophotometry and headspace-GCMS. The UV/VIS methods required longer sample preparation and incubation steps. The GCMS analysis required the samples to be preheated to promote ethanol into the headspace, and had an experimental run time over 10 min per sample. The Raman measurements required relatively no sample preparation, and the spectral data was obtained using a 200 s acquisition time for glucose and xylose, and 100 s for ethanol. Another interesting feature of this work was the demonstration of the ability to simultaneously quantify glucose and xylose in hydrolyzate liquor using a multi-peak curve fit, with detection limits of 3 ± 2 and 1 ± 1 mg mL−1 for glucose and xylose respectively (Figure 4). The authors also evaluated the effects of various biomass pretreatment strategies on the ability to measure glucose. Soaking the biomass in aqueous ammonia or extracting using an aqueous ethanol solution resulted in lower detection limits. An acid pretreatment did not lower the detection limit, indicating that it was likely lignin and/or extractives like non-lignin phenolics that caused the higher spectral background, and thus elevated detection limits. These results clearly demonstrate the competence of Raman spectroscopy to measure hydrolysis and fermentation products rapidly and accurately.


Evaluating lignocellulosic biomass, its derivatives, and downstream products with Raman spectroscopy.

Lupoi JS, Gjersing E, Davis MF - Front Bioeng Biotechnol (2015)

Multi-peak curve fitting results for (A) 100 mg/mL xylose; (B) 120 mg/mL glucose; and (C) a 60 mg/mL glucose and 50 mg/mL xylose mixture in a soaking in aqueous ammonia hydrolysis broth. The residual between the multi-peak fit and the experimental data is shown in the top panel. The residual is of the same order of magnitude as the spectral noise. The experimental spectra are shown in the middle panel (thicker line) and the fit results are shown in the bottom panel (thinner line) [reprinted with permission from Elsevier, Shih et al. (2011)].
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4403602&req=5

Figure 4: Multi-peak curve fitting results for (A) 100 mg/mL xylose; (B) 120 mg/mL glucose; and (C) a 60 mg/mL glucose and 50 mg/mL xylose mixture in a soaking in aqueous ammonia hydrolysis broth. The residual between the multi-peak fit and the experimental data is shown in the top panel. The residual is of the same order of magnitude as the spectral noise. The experimental spectra are shown in the middle panel (thicker line) and the fit results are shown in the bottom panel (thinner line) [reprinted with permission from Elsevier, Shih et al. (2011)].
Mentions: The quantitation of glucose, xylose, and ethanol in complex matrices illustrated other novel applications of NIR, dispersive Raman spectroscopy (Shih and Smith, 2009; Shih et al., 2011). Raman methods were juxtaposed to those obtained using UV/visible (UV/VIS) spectrophotometry and headspace-GCMS. The UV/VIS methods required longer sample preparation and incubation steps. The GCMS analysis required the samples to be preheated to promote ethanol into the headspace, and had an experimental run time over 10 min per sample. The Raman measurements required relatively no sample preparation, and the spectral data was obtained using a 200 s acquisition time for glucose and xylose, and 100 s for ethanol. Another interesting feature of this work was the demonstration of the ability to simultaneously quantify glucose and xylose in hydrolyzate liquor using a multi-peak curve fit, with detection limits of 3 ± 2 and 1 ± 1 mg mL−1 for glucose and xylose respectively (Figure 4). The authors also evaluated the effects of various biomass pretreatment strategies on the ability to measure glucose. Soaking the biomass in aqueous ammonia or extracting using an aqueous ethanol solution resulted in lower detection limits. An acid pretreatment did not lower the detection limit, indicating that it was likely lignin and/or extractives like non-lignin phenolics that caused the higher spectral background, and thus elevated detection limits. These results clearly demonstrate the competence of Raman spectroscopy to measure hydrolysis and fermentation products rapidly and accurately.

Bottom Line: Hydrolysis and fermentation products, such as glucose and ethanol, can be quantified off-, at-, or on-line.Raman imaging has enabled researchers to develop a visual understanding of reactions, such as different pretreatment strategies, in real-time, while also providing integral chemical information.This review provides an overview of what Raman spectroscopy is, and how it has been applied to the analysis of whole lignocellulosic biomass, its derivatives, and downstream process monitoring.

View Article: PubMed Central - PubMed

Affiliation: Oak Ridge National Laboratory, BioEnergy Science Center , Oak Ridge, TN , USA ; National Renewable Energy Laboratory, National Bioenergy Center , Golden, CO , USA.

ABSTRACT
The creation of fuels, chemicals, and materials from plants can aid in replacing products fabricated from non-renewable energy sources. Before using biomass in downstream applications, it must be characterized to assess chemical traits, such as cellulose, lignin, or lignin monomer content, or the sugars released following an acid or enzymatic hydrolysis. The measurement of these traits allows researchers to gage the recalcitrance of the plants and develop efficient deconstruction strategies to maximize yields. Standard methods for assessing biomass phenotypes often have experimental protocols that limit their use for screening sizeable numbers of plant species. Raman spectroscopy, a non-destructive, non-invasive vibrational spectroscopy technique, is capable of providing qualitative, structural information and quantitative measurements. Applications of Raman spectroscopy have aided in alleviating the constraints of standard methods by coupling spectral data with multivariate analysis to construct models capable of predicting analytes. Hydrolysis and fermentation products, such as glucose and ethanol, can be quantified off-, at-, or on-line. Raman imaging has enabled researchers to develop a visual understanding of reactions, such as different pretreatment strategies, in real-time, while also providing integral chemical information. This review provides an overview of what Raman spectroscopy is, and how it has been applied to the analysis of whole lignocellulosic biomass, its derivatives, and downstream process monitoring.

No MeSH data available.