Abstract
The compositional analysis of numerous cellulosic biomass for genetic screening and process development needs an efficient, rapid, and low-cost method. Near-infrared spectroscopy as well as chemometric analysis was successfully used for compositional analysis of sorghum biomass in this study. Model development was performed with hundreds of sorghum accessions with a diverse composition distribution. Both structural polysaccharides and soluble sugars were investigated as sorghum contains a significant amount of soluble sugars. Model evaluation suggested that the coefficients of determination (r 2) for soluble sugars were greater than or equal to 0.90 and showed excellent prediction performance. For structural polysaccharides, the glucan model is able to provide reliable prediction with r 2 of 0.87 and ratio of standard deviation of calculated set to root mean square error of prediction (RPD) of 3.13, whereas the xylan model could be used for approximate screening with r 2 of 0.78 and RPD of 2.82.
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Acknowledgments
This work was supported by Agriculture and Food Research Initiative Competitive Grant 2011–03587 from the US Department of Agriculture National Institute of Food and Agriculture. This is contribution number 14-257-J from the Kansas Agricultural Experiment Station. We thank Mrs. Kristen Hale for NIR measurement. Chromatin Inc. provided the sorghum biomass samples for this research.
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Xu, F., Zhou, L., Zhang, K. et al. Rapid Determination of Both Structural Polysaccharides and Soluble Sugars in Sorghum Biomass Using Near-Infrared Spectroscopy. Bioenerg. Res. 8, 130–136 (2015). https://doi.org/10.1007/s12155-014-9511-z
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DOI: https://doi.org/10.1007/s12155-014-9511-z