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Rapid Analysis of Alcohol Content During the Green Jujube Wine Fermentation by FT-NIR

机译:FT-NIR快速分析青枣酒发酵过程中的酒精含量

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The near-infrared (NIR) spectroscopy combined with partial least square regression (PLS) were applied for the prediction of the alcohol content of jujube wine. The NIR spectroscopy was used to collect the spectral data of the jujube wine samples during fermentation and the data were used to establish the quantitative model of alcohol content to achieve rapid on-line detection. The NIR spectroscopy in the range of 950 to 1650 nm from jujube wine were collected and pre-treated by MSC (Multiplicative Scatter Correction) and FD (First Derivative). The alcohol content was measured with alcohol meter. Spectral wavelength selection and latent variables were optimized for the lowest root mean square errors. The results show that the FD - PLS model, which yielded R~(2)of 0.9246 and RMSEC of 0.6572, is superior to the MSC- PLS model. Results confirmed that NIR spectroscopy is a promising technique for routine assessment of alcohol content of jujube wine and is a viable and advantageous alternative to the chemical procedures involving laborious extractions. The feasibility of the method was thus verified.
机译:近红外(NIR)光谱与偏最小二乘回归(PLS)结合用于预测枣酒的酒精含量。利用近红外光谱技术收集了枣酒发酵过程中的光谱数据,并利用该数据建立了酒精含量的定量模型,以实现快速在线检测。收集来自枣酒的950至1650 nm范围内的NIR光谱,并通过MSC(乘积散射校正)和FD(一阶导数)进行预处理。用酒精计测量酒精含量。优化了光谱波长选择和潜在变量,以实现最低的均方根误差。结果表明,FD-PLS模型优于MSC-PLS模型,其R〜(2)为0.9246,RMSEC为0.6572。结果证实,近红外光谱法是一种常规评估枣酒酒精含量的有前途的技术,并且是涉及费力提取的化学程序的可行且有利的替代方法。因此验证了该方法的可行性。

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