Application of Spectroscopic Technology Coupled with Chemometrics in Food Analysis

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

Deadline for manuscript submissions: 22 August 2025 | Viewed by 7495

Special Issue Editors


E-Mail Website
Guest Editor
Department of Analytical Chemistry, Faculty of Sciences, University of Extremadura, Avenida de Elvas, s/n, 06006 Badajoz, Spain
Interests: analytical chemistry; spectroscopy; HPLC; NIRS; chemometrics; food

E-Mail Website
Guest Editor
Nutrición y Bromatología, Escuela de Ingenierías Agrarias, Universidad de Extremadura, Avd. Adolfo Suárez s/n, 06007 Badajoz, Spain
Interests: food quality; chemical composition; non-destructive analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The application of analytical methodologies to assess and ensure the quality of food products is of paramount importance. In this context, spectroscopic techniques play a crucial role, as they can provide an accurate fingerprint of a food product, offering a rapid, non-destructive and highly sensitive approach. These techniques generate signals that contain extensive information regarding the chemical composition of the product. However, the interpretation and analysis of such data can be challenging, necessitating the use of chemometric techniques to effectively process the spectroscopic data.

Therefore, this Special Issue is collecting papers focused on the use of spectroscopic techniques in conjunction with chemometrics to analyse, characterise or differentiate food products.

Dr. Elísabet Martín-Tornero
Prof. Dr. Santiago Ruiz-Moyano
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

  • foods
  • spectroscopy
  • fluorescence spectroscopy
  • NIRS
  • FTIR
  • raman spectroscopy
  • chemometrics
  • multivariate analysis

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 policies can be found here.

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Review

12 pages, 1858 KiB  
Article
Near-Infrared Spectroscopy Detection of Off-Flavor Compounds in Tench (Tinca tinca) After Depuration in Clean Water
by Daniel Martín-Vertedor, Juan Carlos Ramírez-López, Ricardo S. Aleman, Elisabet Martín-Tornero and Ismael Montero-Fernández
Foods 2025, 14(5), 739; https://doi.org/10.3390/foods14050739 - 21 Feb 2025
Viewed by 387
Abstract
Tench (Tinca tinca) is a warm-temperate, freshwater benthic fish with often unpleasant odors and flavors which result from its natural habitat. These characteristics may deter consumers; therefore, their removal would enhance the fish’s palatability and market appeal. Thus, tench were grown [...] Read more.
Tench (Tinca tinca) is a warm-temperate, freshwater benthic fish with often unpleasant odors and flavors which result from its natural habitat. These characteristics may deter consumers; therefore, their removal would enhance the fish’s palatability and market appeal. Thus, tench were grown in an aquaculture center and subjected to a clean water depuration system in which six sampling points were carried out at 0 h, 12 h, 24 h, 48 h, 72 h, and 96 h. An analysis was conducted using gas chromatography–mass spectrometry and near-infrared spectroscopy (NIRS), revealing acid derivatives as the predominant families of volatile organic compounds (VOCs). The main off-flavor VOCs were 3,5,5-trimethyl-1-hexene, dimethyl-8-hydronaphtalen, 1-octen-3-ol, diethyl phthalate, 2-methylisoborneol, and a-isomethylionone. Maximum concentrations were observed at 0 h, exceeding 300 μg/g for diethyl phthalate and being less than 55 μg/g for the remaining VOCs. The content progressively decreased from that point on. The spectra obtained by NIRS highlighted differences between the cleaning depuration treatments, exhibiting discrimination among the samples studied (PC1 = 77.8%; PC2 = 11.3%). Finally, dimethyl-8-hydronaphtalen and 2-methylisoborneol were linearly correlated with NIRS data, with RCV2  values of 0.94 and 0.96, respectively, and RMSECV values of 1.00 and 3.62 μg/g, respectively. Therefore, a clean water depuration system is appropriate to obtain fish with fewer off-flavor characteristics. Moreover, NIRS represents an accurate, inexpensive, and non-destructive technique to determine the optimal time for the water depuration of fish. Full article
Show Figures

Figure 1

17 pages, 7642 KiB  
Article
Prediction of the Quality of Anxi Tieguanyin Based on Hyperspectral Detection Technology
by Tao Wang, Yongkuai Chen, Yuyan Huang, Chengxu Zheng, Shuilan Liao, Liangde Xiao and Jian Zhao
Foods 2024, 13(24), 4126; https://doi.org/10.3390/foods13244126 - 20 Dec 2024
Cited by 2 | Viewed by 732
Abstract
Anxi Tieguanyin belongs to the oolong tea category and is one of the top ten most famous teas in China. In this study, hyperspectral imaging (HSI) technology was combined with chemometric methods to achieve the rapid determination of free amino acid and tea [...] Read more.
Anxi Tieguanyin belongs to the oolong tea category and is one of the top ten most famous teas in China. In this study, hyperspectral imaging (HSI) technology was combined with chemometric methods to achieve the rapid determination of free amino acid and tea polyphenol contents in Tieguanyin tea. Here, the spectral data of Tieguanyin tea samples of four quality grades were obtained via visible near-infrared hyperspectroscopy in the range of 400–1000 nm, and the free amino acid and tea polyphenol contents of the samples were detected. First derivative (1D), normalization (Nor), and Savitzky–Golay (SG) smoothing were utilized to preprocess the original spectrum. The characteristic wavelengths were extracted via principal component analysis (PCA), competitive adaptive reweighted sampling (CARS), and the successive projection algorithm (SPA). The contents of free amino acid and tea polyphenol in Tieguanyin tea were predicted by the back propagation (BP) neural network, partial least squares regression (PLSR), random forest (RF), and support vector machine (SVM). The results revealed that the free amino acid content of the clear-flavoured Tieguanyin was greater than that of the strong-flavoured type, that the tea polyphenol content of the strong-flavoured Tieguanyin was greater than that of the clear-flavoured type, and that the content of the first-grade product was greater than that of the second-grade product. The 1D preprocessing improved the resolution and sensitivity of the spectra. When using CARS, the number of wavelengths for free amino acids and tea polyphenols was reduced to 50 and 70, respectively. The combination of 1D and CARS is conducive to improving the accuracy of late modelling. The 1D-CARS-RF model had the highest accuracy in predicting the free amino acid (RP2 = 0.940, RMSEP = 0.032, and RPD = 4.446) and tea polyphenol contents (RP2 = 0.938, RMSEP = 0.334, and RPD = 4.474). The use of hyperspectral imaging combined with multiple algorithms can be used to achieve the fast and non-destructive prediction of free amino acid and tea polyphenol contents in Tieguanyin tea. Full article
Show Figures

Figure 1

Review

Jump to: Research

132 pages, 3867 KiB  
Review
The Role of Near-Infrared Spectroscopy in Food Quality Assurance: A Review of the Past Two Decades
by Marietta Fodor, Anna Matkovits, Eszter Luca Benes and Zsuzsa Jókai
Foods 2024, 13(21), 3501; https://doi.org/10.3390/foods13213501 - 31 Oct 2024
Cited by 8 | Viewed by 5854
Abstract
During food quality control, NIR technology enables the rapid and non-destructive determination of the typical quality characteristics of food categories, their origin, and the detection of potential counterfeits. Over the past 20 years, the NIR results for a variety of food groups—including meat [...] Read more.
During food quality control, NIR technology enables the rapid and non-destructive determination of the typical quality characteristics of food categories, their origin, and the detection of potential counterfeits. Over the past 20 years, the NIR results for a variety of food groups—including meat and meat products, milk and milk products, baked goods, pasta, honey, vegetables, fruits, and luxury items like coffee, tea, and chocolate—have been compiled. This review aims to give a broad overview of the NIRS processes that have been used thus far to assist researchers employing non-destructive techniques in comparing their findings with earlier data and determining new research directions. Full article
Show Figures

Graphical abstract

Back to TopTop