| 基于傅里叶变换近红外光谱实时分析1,3-丙二醇发酵过程生物量的在线监测方法 |
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| 引用本文： | 王路,刘涛,陈洋,孙亚琴,修志龙.基于傅里叶变换近红外光谱实时分析1,3-丙二醇发酵过程生物量的在线监测方法[J].生物工程学报,2017,33(1):68-78. |
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| 作者姓名： | 王路 刘涛 陈洋 孙亚琴 修志龙 |
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| 作者单位： | 1 大连理工大学 控制科学与工程学院，辽宁 大连 116024,1 大连理工大学 控制科学与工程学院，辽宁 大连 116024,2 大连理工大学 生命科学与技术学院，辽宁 大连 116024,2 大连理工大学 生命科学与技术学院，辽宁 大连 116024,2 大连理工大学 生命科学与技术学院，辽宁 大连 116024 |
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| 基金项目： | 国家自然科学基金 (Nos. 61473054, 61633006, 21306021)，第三批国家青年千人计划，大连理工大学重点培育基金项目 (No. DUT15ZD108) 资助。 |
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| 摘 要： | 生物量是反映生物发酵过程进展的重要参数,对生物量进行实时监测可用于对发酵过程的调控优化。为克服目前主要采用的离线方法检测生物量时间滞后和人工测量误差较大等缺点,本研究针对1,3-丙二醇发酵过程设计了一个基于傅里叶变换近红外光谱实时分析技术的生物量在线监测实验平台,通过对实时采集光谱预处理以及敏感光谱段分析,应用偏最小二乘算法,建立了1,3-丙二醇发酵过程生物量变化的动态预测模型。以底物甘油浓度为60 g/L和40 g/L的发酵过程作为外部验证实验,分析得到模型的预测均方根误差分别为0.341 6和0.274 3,结果表明所建立的模型具有较好的实时预测能力,能够实现对1,3-丙二醇发酵过程中生物量的有效在线监测。
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| 关 键 词： | 近红外光谱分析技术，在线监测，1 3-丙二醇发酵过程，生物量，偏最小二乘算法 |
| 收稿时间： | 2016/6/29 0:00:00 |
On-line monitoring of biomass in 1, 3-propanediol fermentation by Fourier-transformed near-infrared spectra analysis |
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| Lu Wang,Tao Liu,Yang Chen,Yaqin Sun and Zhilong Xiu.On-line monitoring of biomass in 1, 3-propanediol fermentation by Fourier-transformed near-infrared spectra analysis[J].Chinese Journal of Biotechnology,2017,33(1):68-78. |
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| Authors: | Lu Wang Tao Liu Yang Chen Yaqin Sun and Zhilong Xiu |
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| Institution: | 1 School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China,1 School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China,2 School of Life Science and Biotechnology, Dalian University of Technology, Dalian 116024, Liaoning, China,2 School of Life Science and Biotechnology, Dalian University of Technology, Dalian 116024, Liaoning, China and 2 School of Life Science and Biotechnology, Dalian University of Technology, Dalian 116024, Liaoning, China |
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| Abstract: | Biomass is an important parameter reflecting the fermentation dynamics. Real-time monitoring of biomass can be used to control and optimize a fermentation process. To overcome the deficiencies of measurement delay and manual errors from offline measurement, we designed an experimental platform for online monitoring the biomass during a 1,3-propanediol fermentation process, based on using the fourier-transformed near-infrared (FT-NIR) spectra analysis. By pre-processing the real-time sampled spectra and analyzing the sensitive spectra bands, a partial least-squares algorithm was proposed to establish a dynamic prediction model for the biomass change during a 1,3-propanediol fermentation process. The established model gives good prediction and can be effectively used for on-line monitoring the biomass during a 1,3-propanediol fermentation process. |
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| Keywords: | near-infrared spectra analysis technology on-line monitoring 1 3-propanediol fermentation process biomass partial least-squares (PLS) algorithm |
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