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The application of near infrared spectroscopy in process monitoring of solid-state fermentation of sweet sorghum stalks

机译:近红外光谱在甜高粱秆固态发酵过程监测中的应用

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Multiple samples (117) of sweet sorghum stalk particles were analysed qualitatively and quantitatively during solid-state fermentation using near infrared spectroscopy and chemometrics methods. The study indicated that the samples could be identified to the lag phase, exponential phase or stationary phase of the ethanol fermentation process by discriminant analysis of a principal component analysis (PCA) model. The first principal component score of PCA could be used to predict the extent of reaction, regardless of the value of parameters, such as pH value and sugar, ethanol and water content. The r(2) values of multivariate regression models for mass fractions of sugar, alcohol and water, and pH were 0.93, 0.94, 0.87 and 0.95, respectively. The root mean standard errors of prediction for mass fractions of sugar, alcohol and water, and pH were 0.013, 0.006, 0.008 w w(-1) and 0.15, respectively. The partial least squares regression of the value of pH had the best fit of the four parameters. Near infrared spectroscopy could be used successfully in process monitoring of solid-state fermentation of sweet sorghum stalks.
机译:使用近红外光谱和化学计量学方法,在固态发酵过程中定性和定量地分析了甜高粱茎杆颗粒的多个样品(117)。研究表明,通过主成分分析(PCA)模型的判别分析,可以将样品鉴定为乙醇发酵过程的滞后阶段,指数阶段或固定阶段。 PCA的第一主成分评分可用于预测反应程度,而与pH值以及糖,乙醇和水含量等参数的值无关。糖,酒精和水的质量分数和pH的多元回归模型的r(2)值分别为0.93、0.94、0.87和0.95。糖,酒精和水的质量分数和pH值的预测均方根标准误分别为0.013、0.006、0.008 w w(-1)和0.15。 pH值的偏最小二乘回归具有四个参数的最佳拟合。近红外光谱技术可成功用于甜高粱茎秆固态发酵的过程监测。

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