Fluorescence-based soft-sensor for monitoring β-lactoglobulin and α-lactalbumin solubility during thermal aggregation
✍ Scribed by Rand Elshereef; Hector Budman; Christine Moresoli; Raymond L. Legge
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 457 KB
- Volume
- 99
- Category
- Article
- ISSN
- 0006-3592
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✦ Synopsis
Abstract
A soft‐sensor for monitoring solubility of native‐like α‐lactalbumin (α‐LA) and β‐lactoglobulin (β‐LG) and their aggregation behavior following heat treatment of mixtures under different treatment conditions was developed using fluorescence spectroscopy data regressed with a multivariate Partial Least Squares (PLS) regression algorithm. PLS regression was used to correlate the concentrations of α‐LA and β‐LG to the fluorescence spectra obtained for their mixtures. Data for the calibration and validation of the soft sensor was derived from fluorescence spectra. The process of thermal induced aggregation of β‐LG and α‐LA protein in mixtures, which involves the disappearance of native‐like proteins, was studied under various treatment conditions including different temperatures, pH, total initial protein concentration and proportions of α‐LA and β‐LG. It was demonstrated that the multivariate regression models used could effectively deconvolute multi‐wavelength fluorescence spectra collected under a variety of process conditions and provide a fairly accurate quantification of respective native‐like proteins despite the significant overlapping between their emission profiles. It was also demonstrated that a PLS model can be used as a black‐box prediction tool for estimating protein aggregation when combined with simple mass balances. Bioeng. 2008;99: 567–577. © 2007 Wiley Periodicals, Inc.