Literature DB >> 32659075

NMR-Based Analysis of Pomegranate Juice Using Untargeted Metabolomics Coupled with Nested and Quantitative Approaches.

Fenfen Tang1, Emmanuel Hatzakis1,2.   

Abstract

Pomegranate juice is a complex mixture of structurally diverse compounds appearing in various concentrations. The composition of the final product depends on several factors, such as the fruit variety and the addition of adulterants. Its diverse composition makes pomegranate juice an excellent system for assessing the potential of an analytical method for targeted and untargeted analysis. Here, we tested the ability of 1D and 2D NMR spectroscopy techniques for the targeted and untargeted metabolite analysis of pomegranate juice. The NMR spectra assignment was performed using the novel NOAH sequences and spiking with model compounds. Several metabolites, including sugars, organic acids, and amino acids, were identified and quantified in a rapid and simultaneous manner. Five internal standards were tested, with potassium hydrogen phthalate and dimethylmalonic acid found to be the most appropriate, based on their shorter T1 relaxation times and spectral simplicity, while MnCl2 was successfully applied as a relaxation agent for the reduction of the experimental time. Among the pulse sequences that were tested for their quantitative potential, the Carr-Purcell-Meiboom-Gill gave the best results. The quantitative, QEC-HSQC experiment was also found to be very promising for mixture analysis. Additionally, the potential of 1D/2D NMR-based untargeted analysis was successfully tested on two cases, namely, differentiation between cultivars and detection of adulteration with apple juice. This study demonstrates the proof of concept for 1D and 2D NMR methods in the targeted and untargeted analysis of pomegranate juice and can be extended to other complex matrices.

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Year:  2020        PMID: 32659075     DOI: 10.1021/acs.analchem.0c01553

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  2 in total

1.  Rapid Detection and Quantification of Adulterants in Fruit Juices Using Machine Learning Tools and Spectroscopy Data.

Authors:  José Luis P Calle; Marta Barea-Sepúlveda; Ana Ruiz-Rodríguez; José Ángel Álvarez; Marta Ferreiro-González; Miguel Palma
Journal:  Sensors (Basel)       Date:  2022-05-19       Impact factor: 3.847

2.  Evaluation of Fumaric Acid and Maleic Acid as Internal Standards for NMR Analysis of Protein Precipitated Plasma, Serum, and Whole Blood.

Authors:  G A Nagana Gowda; Natalie N Hong; Daniel Raftery
Journal:  Anal Chem       Date:  2021-02-04       Impact factor: 6.986

  2 in total

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