Analytica Chimica Acta 428 (2001) 41–59 Deconvolution of near-infrared spectral information for monitoring mycelial biomass and other key analytes in a submerged fungal bioprocess Seetharaman Vaidyanathan ∗ , Linda M. Harvey, Brian McNeil Strathclyde Fermentation Centre, Department of Bioscience and Biotechnology, University of Strathclyde, Glasgow G1 1XW, Scotland, UK Received 27 March 2000; received in revised form 28 August 2000; accepted 20 September 2000 Abstract Near-infrared spectroscopy is a promising technique for the rapid monitoring of submerged culture bioprocesses. However, despite the key role of mycelial (filamentous fungal and bacterial) micro-organisms in the manufacture of antibiotics and other valuable therapeutics, there is little information on the application of the technique to monitor mycelial bioprocesses. In part, this is due to the complex and spectroscopically challenging matrices, which result from the growth of these micro-organisms. Moreover, there is a particular lack of any detailed mechanistic information on how models for the prediction of the con- centration of key analytes (e.g. biomass, substrates, product) can be constructed, evaluated and improved using the spectral data arising from such complex matrices. We investigated the near-infrared spectra of culture fluid from a submerged fungal bioprocess, for monitoring the concentrations of mycelial biomass and other key analytes. Several empirical models were developed for predicting the concentration of the analytes, using multivariate statistical techniques. Despite the filamentous nature of the biomass and the resulting complexity of the spectral variations, empirical models could be developed for the prediction of this analyte, using biomass ‘specific’ information. SEP values of <1 g/l could be achieved on external validation, for models developed in the concentration range of 0–20 g/l. The concentrations of the substrates, total sugars (as glucose equivalents) and ammonium, could also be predicted, simultaneously. However, the product (penicillin) and by product (ex- tracellular proteins) levels had to be monitored on the cell free culture fluid, due to their relatively low concentration. Here we report upon how the spectral information can be deconvoluted for predicting the levels of the analytes and upon how the ‘analyte specific’ information in the spectral data can be used to inform and assist the modelling process, in order to increase confidence in exactly what is being modelled. © 2001 Elsevier Science B.V. All rights reserved. Keywords: Fermentation; Penicillium chrysogenum; Spectroscopy; Mycelial biomass; Multivariate calibration 1. Introduction Near-infrared spectroscopy (NIRS) is an optical technique that has features attractive for cost effective ∗ Corresponding author. Present address: Institute of Biological Sciences, Cledwyn building, University of Wales, Aberystwyth, Ceredigion SY23 3DD, Wales, UK. E-mail address: ssv@aber.ac.uk (S. Vaidyanathan). real-time bioprocess monitoring [1] and it is increas- ingly being investigated for that purpose [2–11]. The spectral information in NIRS is secondary in nature and is characterised by low absorbances, making it ideally suited for taking measurements directly on culture fluids. However, the absorption bands in NIRS are typically broad and overlap with each other. More- over, bioprocess culture fluids often exhibit highly complex matrices. Therefore, the spectral information 0003-2670/01/$ – see front matter © 2001 Elsevier Science B.V. All rights reserved. PII:S0003-2670(00)01205-8