APECS Group, Leibniz Institute for Agricultural Engineering (ATB), Max-Eyth-Allee 100, Potsdam 14469, Germany.
Energetische Systeme, Fraunhofer Institut für Chemische Technologie (Fh-ICT), Joseph-von-Fraunhoferstr. 7, Pfinztal 76327, Germany.
Bioresour Technol. 2014 Jun;161:91-101. doi: 10.1016/j.biortech.2014.03.008. Epub 2014 Mar 13.
Near-infrared (NIR) spectroscopy was evaluated as a rapid method of predicting fiber components (hemicellulose, cellulose, lignin, and ash) and selective compounds of hydrochar and corresponding process liquor produced by hydrothermal carbonization (HTC) of maize silage. Several HTC reaction times and temperatures were applied and NIR spectra of both HTC solids and liquids were obtained and correlated with concentration determined from van-Soest fiber analysis, IC, and UHPLC. Partial least-squares regression was applied to calculate models for the prediction of selective substances. The model developed with the spectra had the best performance in 3-7 factors with a correlation coefficient, which varied between 0.9275-0.9880 and 0.9364-0.9957 for compounds in solid and liquid, respectively. Calculated root mean square errors of prediction (RMSEP) were 0.42-5.06mg/kg. The preliminary results indicate that NIR, a widely applied technique, might be applied to determine chemical compounds in HTC solid and liquid.
近红外(NIR)光谱法被评估为一种快速预测纤维成分(半纤维素、纤维素、木质素和灰分)以及通过水热碳化(HTC)玉米青贮生产的水热炭和相应工艺液中选择性化合物的方法。应用了几种 HTC 反应时间和温度,获得了 HTC 固体和液体的 NIR 光谱,并与从范-索斯特纤维分析、IC 和 UHPLC 确定的浓度进行了相关联。偏最小二乘回归用于计算预测选择性物质的模型。在 3-7 个因子下,用光谱开发的模型具有最佳性能,其相关系数分别为 0.9275-0.9880 和 0.9364-0.9957,用于固体和液体中的化合物。预测的均方根误差(RMSEP)为 0.42-5.06mg/kg。初步结果表明,近红外光谱法作为一种广泛应用的技术,可能适用于确定 HTC 固体和液体中的化学化合物。