High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis [electronic resource] : A comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

• Ngôn ngữ: eng
• Ký hiệu phân loại: 666.9 Masonry adhesives
• Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Science ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2014
• Mô tả vật lý: Size: Article No. 93 : , digital, PDF file.
• Bộ sưu tập: Metadata
• ID: 263811
• Chủ đề: 1. 09 biomass fuels; 2. 37 inorganic, organic, physical, and analytical chemistry; 3. 59 basic biological sciences; 4. Biomass; 5. Raman spectroscopy

Tóm tắt

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 Background: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and <
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 Acacia<
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  trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). <
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 Results: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. <
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 Conclusion: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of <
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 Eucalyptus<
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  and <
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 Corymbia<
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 , in addition to various species of <
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 Acacia<
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 , it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks. <
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