Previously, we reported on the development of MagMet, a tool capable of automatically processing and quantifying 1D 1H NMR spectra of complex chemical mixtures, including biofluids such as human serum or plasma and, more recently, beverages such as wine. In this article, we present an extension of MagMet, called MagMet-B, for the automated profiling of 1D 1H NMR spectra of beer. We curated a comprehensive 1D 1H NMR spectral library comprising 81 more abundant metabolites commonly found in beer samples and optimized the MagMet algorithm to accurately fit these compounds. A comparison with manual profiling using the Chenomx NMR Suite (Version 8.3) showed a strong correlation between the manually measured and automated MagMet metabolite concentrations, with a mean absolute percent error of 13% and a median absolute percent error of 9%. Time-to-process comparisons show that MagMet-B is up to 45× faster than manual analysis. The MagMet-B Web server, which is specifically tailored for profiling beer NMR spectra at 700 MHz, is now accessible at https://magmet.ca.

Brian L. Lee

Fatemeh Shahin

Alyaa Selim

Mark Berjanskii

Claudia Torres-Calzada

Prashanthi Kovur

Rupasri Mandal

David S. Wishart

ACS Food Science & Technology

ACS Food Science and Technology

Automated Beer Analysis by NMR Spectroscopy

基于核磁共振光谱的啤酒自动化分析

Automated Beer Analysis by NMR Spectroscopy

ivySCI AI Smartly Parses PDF, Answers Researchers' Questions, and Helps You Understand Papers in Seconds

Journal Info

Category	Quartile
FOOD SCIENCE & TECHNOLOGY	2