Lomborg Carina J, Holm-Nielsen Jens Bo, Oleskowicz-Popiel Piotr, Esbensen Kim H
Aalborg University, Esbjerg, Denmark.
Bioresour Technol. 2009 Mar;100(5):1711-9. doi: 10.1016/j.biortech.2008.09.043. Epub 2008 Nov 8.
In this study, two process analytical technologies, near infrared spectroscopy and acoustic chemometrics, were investigated as means of monitoring a maize silage spiked biogas process. A reactor recirculation loop which enables sampling concomitant with on-line near infrared characterisation was applied. Near infrared models resulted in multivariate models for total and volatile solids with ratio of standard error of performance to standard deviation (RPD) values of 5 and 5.1, indicating good on-line monitoring prospects. The volatile fatty acid models had slopes between 0.83 and 0.92 (good accuracy) and RPD between 2.8 and 3.6 (acceptable precision). A second experiment employed at-line monitoring with both near infrared spectroscopy and acoustic chemometrics. A larger calibration span was obtained for total solids by spiking. Both process analytical modalities were validated with respect to the total solids prediction. The near infrared model had an RPD equal to 5.7, while the acoustic chemometrics model resulted in a RPD of 2.6.
在本研究中,对两种过程分析技术——近红外光谱法和声学化学计量学进行了研究,以作为监测添加了玉米青贮饲料的沼气过程的手段。采用了一个能够在进行在线近红外表征的同时进行采样的反应器循环回路。近红外模型得出了总固体和挥发性固体的多变量模型,其性能标准误差与标准偏差之比(RPD)值分别为5和5.1,表明具有良好的在线监测前景。挥发性脂肪酸模型的斜率在0.83至0.92之间(准确度良好),RPD在2.8至3.6之间(精度可接受)。第二个实验采用近红外光谱法和声学化学计量学进行离线监测。通过加标获得了更大的总固体校准范围。两种过程分析方法均针对总固体预测进行了验证。近红外模型的RPD等于5.7,而声学化学计量学模型的RPD为2.6。