No abstract

Process analytical technology aims at process knowledge and process improvement, efficiency, and sustainability. A prerequisite is process monitoring. The combination of microreaction systems and spectroscopy proved suitable due to dimension and compound reduction and real-time monitoring capabilities. Compact 1H NMR, NIR, and Raman spectroscopy were used to monitor the biocatalyzed hydrolysis and esterification of acetic anhydride to isoamyl acetate using immobilized Candida antarctica lipase B (CALB) in a microreaction system in real-time. To facilitate the identification of signals suitable for the extraction of concentration-time (c-t) graphs, 2D heterocorrelation spectra were generated through covariance transformations applied to 1D Raman, NIR, and NMR data. By means of this purely mathematical statistical procedure, the relevant signals of the process media were assigned to educts and products and thus made applicable for univariate data evaluation. The data obtained were interpreted in terms of a first-order kinetic model, and corresponding reaction rate constants were extracted. An alternative, elegant, and fit-for-automation approach for the kinetic analysis of the spectra was demonstrated in using multivariate curve resolution (MCR). The results of the univariate and multivariate approaches were comparable with regard to reaction rates and concentrations. While the manual integration of the 1H NMR spectra followed by univariate analysis allowed to establish a concentration profile of the final product isoamyl acetate hence revealing more details, multivariate analysis was found more suitable for process automation.

A handheld Raman spectrometer was used to determine the ripeness of peppers. Raman spectra were recorded non-invasively on the fruit surface. The spectroscopic data were transformed into a classification scheme referred to as the maturity index which allowed for attribution of the fruit stadium to four levels from immature to fully mature. Hot pepper and tomato ripening includes pectic polysaccharide depolymerization, chlorophyll degradation and carotenoid formation, among others. The latter were followed non-invasively by Raman spectroscopy. Two portable systems and one benchtop system were compared for their applicability and robustness to establish a suitable maturity index. Spectral acquisition, data treatment and multivariate data analysis were automated using a Matlab script on a laptop computer. The automated workflow provided a graphic visualization of the relevant parameters and results on-site in real time. In terms of reliability and applicability, the chemometric model to determine the maturity of fruits was compared to a univariate procedure based on the average intensity and ratio of three characteristic signals. Portable Raman spectrometers in combination with the maturity index or a chemometric model should be suitable to assess the stage of maturing for carotenoid-containing fruits and thus to determine ripeness on-site or during a sorting process in an automated manner.