Department of Applied Science and Technology, Polytechnic of Turin, Corso Duca degli Abruzzi 24, I-10129 Turin, Italy.
Chemometrics and Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark.
Molecules. 2021 Mar 8;26(5):1472. doi: 10.3390/molecules26051472.
The consumers' interest towards beer consumption has been on the rise during the past decade: new approaches and ingredients get tested, expanding the traditional recipe for brewing beer. As a consequence, the field of "beeromics" has also been constantly growing, as well as the demand for quick and exhaustive analytical methods. In this study, we propose a combination of nuclear magnetic resonance (NMR) spectroscopy and chemometrics to characterize beer. H-NMR spectra were collected and then analyzed using chemometric tools. An interval-based approach was applied to extract chemical features from the spectra to build a dataset of resolved relative concentrations. One aim of this work was to compare the results obtained using the full spectrum and the resolved approach: with a reasonable amount of time needed to obtain the resolved dataset, we show that the resolved information is comparable with the full spectrum information, but interpretability is greatly improved.
在过去的十年中，消费者对啤酒消费的兴趣一直在上升：新的方法和成分得到了测试，扩大了酿造啤酒的传统配方。因此，“啤酒学”领域也在不断发展，对快速和详尽的分析方法的需求也在增加。在这项研究中，我们提出了将核磁共振（NMR）光谱和化学计量学相结合来表征啤酒。收集了 H-NMR 光谱，然后使用化学计量学工具进行分析。应用基于区间的方法从光谱中提取化学特征，构建解析相对浓度数据集。这项工作的目的之一是比较使用全谱和解析方法获得的结果：使用获得解析数据集所需的合理时间，我们表明解析信息与全谱信息相当，但可解释性大大提高。
