Comparison of Regular, Pure Shift, and Fast 2D NMR Experiments for Determination of the Geographical Origin of Walnuts

Stephanie Watermann,Caroline Schmitt,Tobias Schneider,Thomas Hackl

doi:10.3390/metabo11010039

Stephanie Watermann, Caroline Schmitt + Show 2 more

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https://doi.org/10.3390/metabo11010039

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Journal: Metabolites	Publication Date: Jan 8, 2021
Citations: 11	License type: CC BY 4.0

Affiliation: Universität Hamburg, Medical School Hamburg

Abstract

1H NMR spectroscopy, in combination with chemometric methods, was used to analyze the methanol/acetonitrile (1:1) extract of walnut (Juglans Regia L.) regarding the geographical origin of 128 authentic samples from different countries (France, Germany, China) and harvest years (2016–2019). Due to the large number of different metabolites within the acetonitrile/methanol extract, the one-dimensional (1D) 1H NOESY (nuclear Overhauser effect spectroscopy) spectra suffer from strongly overlapping signals. The identification of specific metabolites and statistical analysis are complicated. The use of pure shift 1H NMR spectra such as PSYCHE (pure shift yielded by chirp excitation) or two-dimensional ASAP-HSQC (acceleration by sharing adjacent polarization-heteronuclear single quantum correlation) spectra for multivariate analysis to determine the geographical origin of foods may be a promising method. Different types of NMR spectra (1D 1H NOESY, PSYCHE, and ASAP-HSQC) were acquired for each of the 128 walnut samples and the results of the statistical analysis were compared. A support vector machine classifier was applied for differentiation of samples from Germany/China, France/Germany, and France/China. The models obtained by conduction of a repeated nested cross-validation showed accuracies from 58.9% (±1.3%) to 95.9% (±0.8%). The potential of the 1H-13C HSQC as a 2D NMR experiment for metabolomics studies was shown.

Highlights

The field of metabolomics is becoming increasingly important, especially with regard to the discrimination or classification of samples [1]
Since the aim was to obtain a high dispersion in the chemical shift of nuclear magnetic resonance spectroscopy (NMR) signals, the non-polar extract was unsuitable because the fatty acid fingerprint contains only a few characteristic signals
This study demonstrates the utility of different NMR experiments (1D 1H NOESY, PSYCHE, and 1H-13C ASAP-HSQC) regarding the classification of walnut samples of different geographical origin (France, China, and Germany) in an untargeted metabolomics approach using the mid-polar acetonitrile/methanol (1:1) extract

Summary

Introduction

The field of metabolomics is becoming increasingly important, especially with regard to the discrimination or classification of samples [1]. Food fingerprinting is a metabolomicsbased approach that focuses on the recognition of specific patterns that enable the differentiation of several groups [1,2] Regarding food samples, this differentiation can be based on the geographical origin, varieties, different growing conditions, adulterations, or harvest times [3,4,5,6,7]. NMR spectroscopy requires minimal sample preparation and is a highly automatable technique, which allows a high throughput of samples [8]. It enables structure elucidation, and it is a highly reproducible, nondestructive, and quantifiable method [8,9,10,12]. MS is much more sensitive compared to NMR spectroscopy, but signals in mass spectra are not directly quantifiable, since the ionization efficiency is not the same for different metabolites [8,9]

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