文献类型：期刊文献

英文题名：At-line monitoring of key parameters of nisin fermentation by near infrared spectroscopy, chemometric modeling and model improvement

作者：Guo, Wei-Liang[1,2];Du, Yi-Ping[3];Zhou, Yong-Can[2];Yang, Shuang[1];Lu, Jia-Hui[1];Zhao, Hong-Yu[1];Wang, Yao[4];Teng, Li-Rong[1]

机构：[1]Jilin Univ, Coll Life Sci, Changchun 130021, Jilin, Peoples R China;[2]Hainan Univ, Coll Marine Sci, Haikou 570228, Hainan, Peoples R China;[3]E China Univ Sci & Technol, Ctr Anal & Test, Shanghai 200237, Peoples R China;[4]Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China

年份：2012

卷号：28

期号：3

起止页码：993

外文期刊名：WORLD JOURNAL OF MICROBIOLOGY & BIOTECHNOLOGY

收录：;EI(收录号：20120614758108);WOS:【SCI-EXPANDED(收录号:WOS:000300290400025)】；

语种：英文

外文关键词：Near infrared spectroscopy; Nisin fermentation; Monte Carlo partial least squares; At-line monitoring

摘要：An analytical procedure has been developed for at-line (fast off-line) monitoring of 4 key parameters including nisin titer (NT), the concentration of reducing sugars, cell concentration and pH during a nisin fermentation process. This procedure is based on near infrared (NIR) spectroscopy and Partial Least Squares (PLS). Samples without any preprocessing were collected at intervals of 1 h during fifteen batch of fermentations. These fermentation processes were implemented in 3 different 5 l fermentors at various conditions. NIR spectra of the samples were collected in 10 min. And then, PLS was used for modeling the relationship between NIR spectra and the key parameters which were determined by reference methods. Monte Carlo Partial Least Squares (MCPLS) was applied to identify the outliers and select the most efficacious methods for preprocessing spectra, wavelengths and the suitable number of latent variables (n (LV)). Then, the optimum models for determining NT, concentration of reducing sugars, cell concentration and pH were established. The correlation coefficients of calibration set (R (c)) were 0.8255, 0.9000, 0.9883 and 0.9581, respectively. These results demonstrated that this method can be successfully applied to at-line monitor of NT, concentration of reducing sugars, cell concentration and pH during nisin fermentation processes.