用近红外光谱法实时监测蛹虫草发酵中胞内多糖的质量浓度

应用近红外光谱(NIR)结合偏最小二乘法(PLS)建立一种实时监测蛹虫草发酵中胞内多糖质量浓度的新方法.对39个批次的蛹虫草在3个不同条件的5L发酵罐中进行蛹虫草深层发酵,发酵过程中间隔一定时间取样,采集样品的近红外光谱,并按常规方法测定样品中胞内多糖质量浓度,再采用PLS法建立样品的近红外光谱与胞内多糖质量浓度间的模型,所建模型经过选择最适光谱预处理方法和最适隐变量数进行优化,其留一交互验证预测值与化学测定参考值间的相关系数R=0.8750,交互验证均方根误差RMSECV=0.3052.采用最优PLS模型对样品中胞内多糖质量浓度进行预测,校正集预测均方根误差RMSEC=0.1670,预测集预测均方根误差RMSEP=0.3650,表明模型的稳健性和预测性能较好。

Near Infrared Spectroscopy Real-Time Monitoring of Intracellular Polysaccharide Concentration during Fermentation of Cordyceps militaris

Near infrared spectroscopy (NIR) combined with partial least square (PLS) was used to develop a new method for the real
time monitoring of the intracellular polysaccharide concentration during the Cordyceps militaris fermentation. 39 batches of Cordyceps militaris fermentation were implemented under various fermentation conditions in 5 L at three kinds of different conditions. The samples were collected at intervals of some hours after the fermentations running into the exponential growth phase. The NIR spectra of the samples were recorded and the intracellular polysaccharide mass concentrations of the samples were determined at the same time via the reference method. PLS method was used to model the relationship between the NIR and the intracellular polysaccharide mass concentration. The developed model was optimized by selecting the suitable spectral preprocessing method and the suitable number of latent variables. The relation coefficient of the predictive values obtained by leave one out cross validation method and the reference values (R) was 0875 0 and the root mean square error of cross validation (RMSECV) was 0.305 2. Using this model for predictingthe intracellular polysaccharide concentration in samples, the root mean squareerror of calibration samples (RMSEC) was 0.167 0 and the root mean square error
of prediction samples (RMSEP) was 0.365 0. These results demonstrate that the stability and the predictive capability of this model were satisfied and this method should be popular in fermentation monitoring processing.