Temporally segmented modelling:a route to improved bioprocess monitoring using near infrared spectroscopy?

摘要

Near infrared spectroscopy(NIRS)was used to onitor an industrial bioprocess for theproduction of the antibiotic,tylosin,using a segmented modelling approach.Models were built over the entire time course of the fermentation fro 0 to 150h,and also in two distinct pases or segments of the bioprocess from 50 to 100h(synthetic phase)and from 100 to 150 h(stationary phase).All models were validated externally and the performance of the full range and segmented models compared.The standard error ofprediction(SEP) of the segmented models was less in both 50-100 h and 100-150 h an dthecorrelation highest in the 50-100 h range.This would suggest that data segmentation is potentially a useful method ofaccommodating the impact of thepronounced amtrix changes which occur in some bioprocesses in NIRS models for key analytes.While there are many reports on bioprocess monitorig using NIRS,there have been no previous studies on the use of segmented NIR models within a bioprocess as a means of accommodatig matrix change.