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Rapid Determination of Lignin Content of Straw Using Fourier Transform Mid-Infrared Spectroscopy

机译:傅里叶变换中红外光谱法快速测定稻草中木质素含量

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To determine lignin content in triticale and wheat straws, calibration models were built using Fourier transform mid-infrared spectroscopy combined with partial least-squares regression. The best model for triticale and wheat straws was built using averaged spectra with raw spectrum in spectrum format and constant in path length as spectral pretreatments. The values of r~2, root-mean-square error of prediction (RMSEP), and residual predictive deviation (RPD) for the triticale straw model were 0.935, 0.305, and 3.89, respectively. The r~2, RMSEP, and RPD values for the wheat straw model were 0.985, 0.163, and 8.50, respectively. Both models showed good predictive ability. A model built using both triticale and wheat straws indicated that the values of r~2, RMSEP, and RPD were 0.952, 0.27, and 4.63, respectively. This model also showed good predictive ability and could predict lignin contents in triticale and wheat straws with the same high accuracy.
机译:为了确定小黑麦和小麦秸秆中的木质素含量,使用傅里叶变换中红外光谱结合偏最小二乘回归建立了校准模型。小黑麦和小麦秸秆的最佳模型是使用平均光谱,原始光谱为光谱格式,路径长度恒定作为光谱预处理方法建立的。小黑麦秸秆模型的r〜2,预测的均方根误差(RMSEP)和残余预测偏差(RPD)分别为0.935、0.305和3.89。小麦秸秆模型的r〜2,RMSEP和RPD值分别为0.985、0.163和8.50。两种模型均显示出良好的预测能力。用黑小麦和小麦秸秆建立的模型表明,r〜2,RMSEP和RPD的值分别为0.952、0.27和4.63。该模型还显示出良好的预测能力,并且可以以相同的高精度预测黑小麦和小麦秸秆中的木质素含量。

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