| Title: | Development of an Automated Complex Mixture Analysis qNMR Method within Mestrelab Mnova: Application to Aloe vera Raw Material Analysis and the Beer Brewing Process |
| Authors: | John C. Edwards, Adam J. Dicaprio, Michael A. Bernstein |
| Date: | 2014/02/03 |
| Reference: | PANIC 2014, Charlotte, North Carolina, February 3 – 5, 2014 |
| PDF: | http://mestrelab.com/pdf/posters/panic-2014/panic-2014-pna-mnova-aloe-beer-final.pdf |
Poster presented by Mike Bersntein in collaboration with John Edwards and Adam DiCaprio at PANIC 2014
An automated approach to complexAloe vera containing products utilizingmixturenicotinamide1H qNMR was developed foras the internal concentration standardthe Mnova platform and small molecule quantitation was performed on a series of.
The analysis automatically generates a comprehensive report of Aloe thevera three active components, degradation products, additives, and adulterants of commercial Aloe vera. Individual species are quantified using areas derived from Global Spectrum Deconvolution (GSD) analysis, which is insensitive to peak overlap and poor baseline.
The known area for a mixture component can be flexibly converted into the desired concentration units using a flexible formula editor. The workflow is automated to facilitate high-throughput analysis, but still allows visual inspection and editing of each sample to account for peak movements. The quantitative values derived from this rapid, straight-forward automated analysis allows decisions to be made on the purchase of materials by end users as well as implementation of controlled process changes in the manufacture of the materials.
A complete NMR analysis of a number of beer varieties was also performed with a special emphasis on sour beers produced by wild fermentation. In this analysis the same cast of small molecules was analyzed with the Mnova qNMR analysis performed to provide ethanol, butandiol, ethyl acetate, lactic, acetic, succinic, citric, and malic acids concentrations along with glucose. The spectra and the qNMR results are used as the basis for principal component analysis that will allow targeted and non-targeted identification of beer types and variations of intermediates in the brewing process.
