分析化学2017，Vol.45Issue(8)：1137-1142,6.DOI:10.11895/j.issn.0253-3820.170349
近红外光谱法定性描述酵母菌的生长过程
Qualitative Prediction of Yeast Growth Process Based on Near Infrared Spectroscopy
摘要
Abstract
To improve the yield of industrial fermentation, a method based on near infrared spectroscopy was presented to predict the growth of yeast.The spectral data of fermentation sample were measured by Fourier-transform near-infrared (FT-NIR) spectrometer in the process of yeast culture.Each spectrum was acquired over the range of 10000-4000 cm1.Meanwhile, the optical density (OD) of fermentation sample was determined with photoelectric turbidity method.After that, a method based on competitive adaptive reweighted sampling (CARS) was used to select characteristic wavelength variables of NIR data, and then extreme learning machine (ELM) algorithm was employed to develop the categorization model about the four growth processes of yeast.Experimental result showed that, only 30 characteristic wavelength variables of NIR data were selected by CRAS algorithms, and the prediction accuracies of training set and test set of the CARS-ELM model were 98.68% and 97.37%, respectively.The research showed that the near infrared spectrum analysis technology was feasible to predict the growth process of yeast.关键词
酵母菌/近红外光谱/竞争性自适应重加权采样法/极限学习机Key words
Near infrared spectroscopy/Growth of yeast/Competitive adaptive reweighted sampling/Extreme learning machine引用本文复制引用
王玮,江辉,刘国海,梅从立,吉奕..近红外光谱法定性描述酵母菌的生长过程[J].分析化学,2017,45(8):1137-1142,6.基金项目
本文系江苏省自然科学基金项目(No.BK20140538)、中国博士后科学基金(No.2016M600381)、江苏省高校自然科学研究面上项目(No.16KJB210003)和江苏省高校研究生实践创新计划项目(No.SJZZ16_0193)资助 （No.BK20140538）
