NREL turns to NIR spectroscopy for biomass analysis

The US National Renewable Energy Laboratory (NREL) in Colorado has developed a host of analytical procedures for determining the composition of biomass and the amount of carbohydrates likely to be released when it is broken down. Such analysis is important when assessing different plant species and strains as potential biofuel feedstocks.

Plant biomass consists mainly of the carbohydrates cellulose and hemicellulose and the tough polymer lignin, which holds the cellulose and hemicellulose in place. Researchers are mainly looking for plants that contain high concentrations of cellulose, which can be released by exposing the biomass to strong acid. Enzymes are then added to convert this cellulose into glucose, which is fermented by microbes such as yeast to produce ethanol. The hemicellulose is not as important, because it is converted by the enzymes into a sugar known as xylose that the microbes can’t ferment as well. But researchers would also like plants that contain low levels of lignin, allowing the cellulose to be released more easily.

The current analytical procedures for determining biomass composition and carbohydrate release utilize techniques such as liquid chromatography that are accurate but expensive and rather slow. Now, two researchers from NREL, Courtney Payne and Edward Wolfrum, have shown that NIR spectroscopy offers an attractive alternative, being just as accurate while significantly faster and cheaper.

Although several research groups have already used NIR spectroscopy to produce models for determining the composition of specific plant species, Payne and Wolfrum wanted to develop a more flexible model that could determine the composition of various different species and strains. So they used NREL’s conventional analytical procedures to determine the concentration of glucose, xylose, lignin and ash in various different types of biomass, including corn stover, sorghum, switchgrass and perennial cool season grasses. They also exposed samples of these different types of biomass to strong acids and enzymes, and then measured how much glucose and xylose was released.

Next, they analysed these biomass samples with NIR spectroscopy and then used partial least squares multivariate analysis to develop models relating the spectral data to both the measured composition and the glucose and xylose yields. As they report in Biotechnology for Biofuels, these models turned out to be highly accurate. When fed spectral data, they were able to determine the proportion of glucose, xylose, lignin and ash in the different types of biomass and the yield of glucose and xylose with accuracies of over 80%. This means NREL may soon need to update its list of approved procedures for analysing biomass.

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