Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.4
4.7
Journals
Foods
Special Issues
Application of Mass Spectrometry-Based Omics and Chemometrics in Food
share announcement

Application of Mass Spectrometry-Based Omics and Chemometrics in Food

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

Deadline for manuscript submissions: 28 February 2025 | Viewed by 1566

Special Issue Editors

Prof. Dr. Fernando Benavente

E-Mail Website
Guest Editor
Department of Chemical Engineering and Analytical Chemistry, Research Institute of Nutrition and Food Safety, University of Barcelona, Martí i Franquès 1-11, 08028 Barcelona, Spain
Interests: analytical chemistry; biomedicine; capillary electrophoresis; food; liquid chromatography; mass spectrometry; peptides and proteins; small molecules; proteomics; metabolomics
Special Issues, Collections and Topics in MDPI journals
Dr. Laura Pont

E-Mail Website
Guest Editor
1. Department of Chemical Engineering and Analytical Chemistry, Research Institute of Nutrition and Food Safety, University of Barcelona, Martí i Franquès 1-11, 08028 Barcelona, Spain
2. Serra Húnter Program, Generalitat de Catalunya, 08007 Barcelona, Spain
Interests: analytical chemistry; biomedicine; capillary electrophoresis; food; liquid chromatography; mass spectrometry; peptides and proteins; small molecules; proteomics; metabolomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mass spectrometry (MS)-based omics, which includes, among other fields of study, the areas of proteomics, metabolomics, and lipidomics, enables the simultaneous identification and quantification of diverse molecular components within food matrices. This comprehensive and detailed analytical approach sheds light on the complex composition of food, driving advancements in the field. It aids in accurately identifying biomarkers related to quality, safety, authenticity, processing or storage conditions, nutritional value, physicochemical properties, bioactivity, and more. To extract relevant chemical information from the extensive datasets generated in MS-based omics, the application of chemometrics becomes essential. This involves data pre-processing, deconvolution, peak peaking, feature identification, statistical analysis, multivariate data analysis, pattern recognition, classification, predictive modeling, etc., facilitating synergies with other artificial intelligence disciplines, such as machine learning. The great advancements made in MS-based omics and chemometrics in biomedical research in recent years have undoubtedly contribute to progress in foodomics. However, the singularity of the analyzed food matrices and molecular components, or the particular nature of the problems that need to be addressed, have required the development of specific experimental and chemometrics workflows for a successful application.

This Special Issue aims to summarize novel applications of MS-based omics and chemometrics in food science and technology, and welcomes both research articles and reviews.

Prof. Dr. Fernando Benavente
Dr. Laura Pont
Guest Editors

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

  • mass spectrometrym-based omics
  • proteomics
  • metabolomics
  • lipidomics
  • chemometrics
  • food science and technology

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

21 pages, 2935 KiB  
Article
Identifying Key Markers for Monofloral (Eucalyptus, Rosemary, and Orange Blossom) and Multifloral Honey Differentiation in the Spanish Market by UHPLC-Q-Orbitrap-High-Resolution Mass Spectrometry Fingerprinting and Chemometrics
by Araceli Rivera-Pérez, Alba María Navarro-Herrera and Antonia Garrido Frenich
Foods 2024, 13(17), 2755; https://doi.org/10.3390/foods13172755 - 29 Aug 2024
Viewed by 469
Abstract
Honey differentiation based on the botanical origin is crucial to guarantee product authenticity, especially considering the increasing number of fraud cases. This study assessed the metabolomic differences arising from various botanical origins in honey products sold in Spanish markets, focusing on two goals: [...] Read more.
Honey differentiation based on the botanical origin is crucial to guarantee product authenticity, especially considering the increasing number of fraud cases. This study assessed the metabolomic differences arising from various botanical origins in honey products sold in Spanish markets, focusing on two goals: (1) discrimination within monofloral samples (eucalyptus, rosemary, and orange blossom honey) and (2) differentiation between multifloral vs. monofloral honey samples. An omics strategy based on ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap-high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS) was applied for the reliable identification of specific honey markers selected by orthogonal partial least squares discriminant analysis (OPLS-DA) (R2Y = 0.929–0.981 and Q2 = 0.868–0.952), followed by the variable importance in projection (VIP) approach. Key amino acid, alkaloid, and trisaccharide markers were identified to distinguish between honey samples. Some Amadori compounds were highlighted as eucalyptus honey markers, suggesting their potential use for honey aging and botanical origin differentiation. L-phenylalanine and raffinose were markers of rosemary honey. Four markers (e.g., trigonelline, L-isoleucine, and N-(1-deoxy-1-fructosyl)isoleucine) were found in higher levels in multifloral samples, indicating a greater availability of amino acids, potentially increasing the Maillard reaction. This research is the first to address the botanical origin’s impact on honey by identifying novel markers not previously described. Full article
(This article belongs to the Special Issue Application of Mass Spectrometry-Based Omics and Chemometrics in Food)
►▼ Show Figures

Figure 1

22 pages, 2937 KiB  
Article
Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry Combined with Chemometrics for Protein Profiling and Classification of Boiled and Extruded Quinoa from Conventional and Organic Crops
by Rocío Galindo-Luján, Laura Pont, Fredy Quispe, Victoria Sanz-Nebot and Fernando Benavente
Foods 2024, 13(12), 1906; https://doi.org/10.3390/foods13121906 - 17 Jun 2024
Viewed by 762
Abstract
Quinoa is an Andean crop that stands out as a high-quality protein-rich and gluten-free food. However, its increasing popularity exposes quinoa products to the potential risk of adulteration with cheaper cereals. Consequently, there is a need for novel methodologies to accurately characterize the [...] Read more.
Quinoa is an Andean crop that stands out as a high-quality protein-rich and gluten-free food. However, its increasing popularity exposes quinoa products to the potential risk of adulteration with cheaper cereals. Consequently, there is a need for novel methodologies to accurately characterize the composition of quinoa, which is influenced not only by the variety type but also by the farming and processing conditions. In this study, we present a rapid and straightforward method based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to generate global fingerprints of quinoa proteins from white quinoa varieties, which were cultivated under conventional and organic farming and processed through boiling and extrusion. The mass spectra of the different protein extracts were processed using the MALDIquant software (version 1.19.3), detecting 49 proteins (with 31 tentatively identified). Intensity values from these proteins were then considered protein fingerprints for multivariate data analysis. Our results revealed reliable partial least squares-discriminant analysis (PLS-DA) classification models for distinguishing between farming and processing conditions, and the detected proteins that were critical for differentiation. They confirm the effectiveness of tracing the agricultural origins and technological treatments of quinoa grains through protein fingerprinting by MALDI-TOF-MS and chemometrics. This untargeted approach offers promising applications in food control and the food-processing industry. Full article
(This article belongs to the Special Issue Application of Mass Spectrometry-Based Omics and Chemometrics in Food)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop