Spectroscopy and Chemometrics Applied in Food Authentication and Quality Evaluation

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Analytical Methods".

Deadline for manuscript submissions: 15 November 2024 | Viewed by 2250

Special Issue Editors


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Guest Editor
Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Modena, Italy
Interests: food authenticity; food traceability; VOCs; heavy isotopes; data analysis; chemometrics; analytical chemistry
Special Issues, Collections and Topics in MDPI journals

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Guest Editor Assistant
Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Modena, Italy
Interests: food process monitoring; VOCs; chemometrics; process analytical technology (PAT); sensing techniques; multivariate statistical process control (MSPC)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, the importance of analytical tools that can objectively guarantee the quality and authenticity of food products cannot be underestimated. In this context, the use of chemometrics and spectroscopy plays a fundamental role. While spectroscopic techniques allow for obtaining signals rich in information on the chemical composition of a food product, and therefore related to its quality, they also provide a real digital fingerprint, which can be used to univocally identify a sample. However, the use of chemometrics in processing spectroscopic data cannot be overlooked. Indeed, handling, fusing, and interpreting data is difficult, as it is not possible to rapidly extract useful information from spectra without proper statistical tools. Furthermore, authenticity models require optimized analytical methodologies, significant sampling, and validation of the built model. All these aspects can only be correctly handled with the use of chemometrics techniques.

We are pleased to invite you to contribute your valuable work to this Special Issue on “Spectroscopy and Chemometrics Applied in Food Authentication and Quality Evaluation”.

This Special Issue aims to collect papers focused on developing novel analytical methodologies able to guarantee the quality and authenticity of food. In this context, the synergistic use of the spectroscopic characterization of food and chemometrics analysis could provide significant support for the development of these methodologies, given the multivariate nature of spectroscopic fingerprints. In this Special Issue, original research articles and reviews are welcome. In the field of food analysis, research areas may include spectroscopy, chemometrics, experimental design, hyphenated methods, food quality, fraud detection, authentication/characterization, and deep learning.

We look forward to receiving your contributions.

Dr. Caterina Durante
Guest Editor

Dr. Lorenzo Strani
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • spectroscopy
  • chemometrics
  • experimental design
  • hyphenated methods
  • food quality
  • fraud detection
  • authentication/characterization
  • deep learning

Published Papers (2 papers)

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Research

22 pages, 3668 KiB  
Article
The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
by Isabel Revilla, Miriam Hernández Jiménez, Iván Martínez-Martín, Patricia Valderrama, Marta Rodríguez-Fernández and Ana M. Vivar-Quintana
Foods 2024, 13(3), 450; https://doi.org/10.3390/foods13030450 - 31 Jan 2024
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Abstract
The following study analyzed the potential of Near Infrared Spectroscopy (NIRS) to predict the metal composition (Al, Pb, As, Hg and Cu) of tea and for establishing discriminant models for pure teas (green, red, and black) and their different blends. A total of [...] Read more.
The following study analyzed the potential of Near Infrared Spectroscopy (NIRS) to predict the metal composition (Al, Pb, As, Hg and Cu) of tea and for establishing discriminant models for pure teas (green, red, and black) and their different blends. A total of 322 samples of pure black, red, and green teas and binary blends were analyzed. The results showed that pure red teas had the highest content of As and Pb, green teas were the only ones containing Hg, and black teas showed higher levels of Cu. NIRS allowed to predict the content of Al, Pb, As, Hg, and Cu with ratio performance deviation values > 3 for all of them. Additionally, it was possible to discriminate pure samples from their respective blends with an accuracy of 98.3% in calibration and 92.3% in validation. However, when the samples were discriminated according to the percentage of blending (>95%, 95–85%, 85–75%, or 75–50% of pure tea) 100% of the samples of 10 out of 12 groups were correctly classified in calibration, but only the groups with a level of pure tea of >95% showed 100% of the samples as being correctly classified as to validation. Full article
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15 pages, 1826 KiB  
Article
Varietal Authenticity Assessment of QTMJ Tea Using Non-Targeted Metabolomics and Multi-Elemental Analysis with Chemometrics
by Huahong Liu, Yuxin Wu, Ziwei Zhao, Zhi Liu, Renjun Liu, Yuelan Pang, Chun Yang, Yun Zhang and Jinfang Nie
Foods 2023, 12(22), 4114; https://doi.org/10.3390/foods12224114 - 13 Nov 2023
Viewed by 1067
Abstract
In this paper, a combination of non-targeted metabolomics and multi-element analysis was used to investigate the impact of five different cultivars on the sensory quality of QTMJ tea and identify candidate markers for varietal authenticity assessment. With chemometric analysis, a total of 54 [...] Read more.
In this paper, a combination of non-targeted metabolomics and multi-element analysis was used to investigate the impact of five different cultivars on the sensory quality of QTMJ tea and identify candidate markers for varietal authenticity assessment. With chemometric analysis, a total of 54 differential metabolites were screened, with the abundances significantly varied in the tea cultivars. By contrast, the QTMJ tea from the Yaoshan Xiulv (XL) monovariety presents a much better sensory quality as result of the relatively more abundant anthocyanin glycosides and the lower levels of 2′-o-methyladenosine, denudatine, kynurenic acid and L-pipecolic acid. In addition, multi-elemental analysis found 14 significantly differential elements among the cultivars (VIP > 1 and p < 0.05). The differences and correlations of metabolites and elemental signatures of QTMJ tea between five cultivars were discussed using a Pearson correlation analysis. Element characteristics can be used as the best discriminant index for different cultivars of QTMJT, with a predictive accuracy of 100%. Full article
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