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Article

Parameter Visualization of Benchtop Nuclear Magnetic Resonance Spectra toward Food Process Monitoring

1
Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Kanagawa, Japan
2
RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Kanagawa, Japan
3
Department of Information Systems, Niigata University of International and Information Studies, 3-1-1 Mizukino, Nishi-ku, Niigata-shi 950-2292, Niigata, Japan
4
Graduate School of Bioagricultural Sciences, Nagoya University, 1 Furo-cho, Chikusa-ku, Nagoya 464-0810, Aichi, Japan
*
Author to whom correspondence should be addressed.
Processes 2022, 10(7), 1264; https://doi.org/10.3390/pr10071264
Submission received: 15 June 2022 / Accepted: 23 June 2022 / Published: 27 June 2022

Abstract

Low-cost and user-friendly benchtop low-field nuclear magnetic resonance (NMR) spectrometers are typically used to monitor food processes in the food industry. Because of excessive spectral overlap, it is difficult to characterize food mixtures using low-field NMR spectroscopy. In addition, for standard compounds, low-field benchtop NMR data are typically unavailable compared to high-field NMR data, which have been accumulated and are reusable in public databases. This work focused on NMR parameter visualization of the chemical structure and mobility of mixtures and the use of high-field NMR data to analyze benchtop NMR data to characterize food process samples. We developed a tool to easily process benchtop NMR data and obtain chemical shifts and T2 relaxation times of peaks, as well as transform high-field NMR data into low-field NMR data. Line broadening and time–frequency analysis methods were adopted for data processing. This tool can visualize NMR parameters to characterize changes in the components and mobilities of food process samples using benchtop NMR data. In addition, assignment errors were smaller when the spectra of standard compounds were identified by transferring the high-field NMR data to low-field NMR data rather than directly using experimentally obtained low-field NMR spectra.
Keywords: food process monitoring; agriculture; fishery; livestock; benchtop NMR; short-time Fourier transform; fitting; transfer simulation; composition; physical properties food process monitoring; agriculture; fishery; livestock; benchtop NMR; short-time Fourier transform; fitting; transfer simulation; composition; physical properties
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MDPI and ACS Style

Hara, K.; Yamada, S.; Chikayama, E.; Kikuchi, J. Parameter Visualization of Benchtop Nuclear Magnetic Resonance Spectra toward Food Process Monitoring. Processes 2022, 10, 1264. https://doi.org/10.3390/pr10071264

AMA Style

Hara K, Yamada S, Chikayama E, Kikuchi J. Parameter Visualization of Benchtop Nuclear Magnetic Resonance Spectra toward Food Process Monitoring. Processes. 2022; 10(7):1264. https://doi.org/10.3390/pr10071264

Chicago/Turabian Style

Hara, Koki, Shunji Yamada, Eisuke Chikayama, and Jun Kikuchi. 2022. "Parameter Visualization of Benchtop Nuclear Magnetic Resonance Spectra toward Food Process Monitoring" Processes 10, no. 7: 1264. https://doi.org/10.3390/pr10071264

APA Style

Hara, K., Yamada, S., Chikayama, E., & Kikuchi, J. (2022). Parameter Visualization of Benchtop Nuclear Magnetic Resonance Spectra toward Food Process Monitoring. Processes, 10(7), 1264. https://doi.org/10.3390/pr10071264

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