Single compound data supplementation to enhance transferability of fermentation specific Raman spectroscopy models.

ABSTRACT: Raman spectroscopy is a valuable analytical tool for real-time analyte quantification in fermentation processes. Quantification is performed with chemometric models that translate Raman spectra into concentration values, which are typically calibrated with process data from multiple comparable fermentations. However, process-specific models underperform for minor process variation(s) or different operation modes due to the integration of cross-correlations, resulting in low target analyte specificity. Thus, model transferability is poor and labor-intensive (re-)calibration of models is required for related processes. In this work, partial least-squares models for glucose, ethanol, and biomass were calibrated with Saccharomyces cerevisiae batch fermentation data and subsequently transferred

SUBMITTER: Klaverdijk M 

PROVIDER: S-EPMC11914363 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature