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Spectroscopic Methods in Food Chemistry
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Spectroscopic Methods in Food Chemistry

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Food Chemistry".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 7719

Special Issue Editors

Dr. Michelangelo Pascale

E-Mail Website
Guest Editor
Institute of Food Sciences, National Research Council, 83100 Avellino, Italy
Interests: food quality; food safety; food authenticity; rapid methods; chromatographic methods; methods validation
Special Issues, Collections and Topics in MDPI journals
Dr. Annalisa De Girolamo

E-Mail Website
Guest Editor
Institute of Sciences of Food Production, National Research Council, 70126 Bari, Italy
Interests: food quality; food safety; food authenticity; infrared spectroscopy; rapid methods; chromatographic methods; methods validation; chemometric analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Food chemistry aims to characterize food products by analyzing their chemical composition and the properties of their constituents. It also studies the chemical modifications that food constituents undergo after processing, reveals adulterations, and identifies the presence of xenobiotic substances potentially harmful to human health.

The molecular composition of a food product is generally very complex and depends on several factors, including genetic and geographical origin, environmental/climatological conditions, types of farming, breeding and processing practices, as well as the addition of adulterants or presence of contaminants such as mycotoxins, pesticides, heavy metals, acrylamide, and biogenic amines.

Food chemicals can be analyzed through a number of different analytical methods, including spectroscopic ones. The most common types of spectroscopy used for chemical analysis include near- and mid-infrared spectroscopy, Raman spectroscopy, Fluorescence spectroscopy, hyperspectral imaging, ultraviolet and visible spectroscopy, atomic spectroscopy, nuclear magnetic resonance, and X-ray. These methods are mainly classified depending on the type of radiation, the nature of the interaction between the energy and the material, and the kind of material.

We invite specialists and researchers working in this area to submit to this Special Issue of Molecules high-quality original contributions, short communications, or reviews on the application of spectroscopic methods to the analysis of foods for quantitative, qualitative, and authenticity purposes. The description of emerging applications using spectroscopic methods in combination with chemometrics data processing approaches is also welcome.

Dr. Michelangelo Pascale
Dr. Annalisa De Girolamo
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. Molecules 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 2700 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

  • food analysis
  • food contaminants
  • food quality
  • food adulteration
  • infrared spectroscopy
  • raman spectroscopy and hyperspectral imaging
  • atomic spectroscopy
  • ultraviolet and visible spectroscopy
  • fluorescence spectroscopy
  • nuclear magnetic resonance spectroscopy
  • spectroscopic radiation
  • x-ray
  • chemometrics

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Published Papers (5 papers)

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Research

16 pages, 2215 KiB  
Article
Benchtop NMR Coupled with Chemometrics: A Workflow for Unveiling Hidden Drug Ingredients in Honey-Based Supplements
by Camille Pujol, Saïda Danoun, Ghislaine Biasini, Emmanuel Retailleau, Jessica Masson, Stéphane Balayssac and Véronique Gilard
Molecules 2024, 29(9), 2086; https://doi.org/10.3390/molecules29092086 - 1 May 2024
Viewed by 1093
Abstract
Recently, benchtop nuclear magnetic resonance (NMR) spectrometers utilizing permanent magnets have emerged as versatile tools with applications across various fields, including food and pharmaceuticals. Their efficacy is further enhanced when coupled with chemometric methods. This study presents an innovative approach to leveraging a [...] Read more.
Recently, benchtop nuclear magnetic resonance (NMR) spectrometers utilizing permanent magnets have emerged as versatile tools with applications across various fields, including food and pharmaceuticals. Their efficacy is further enhanced when coupled with chemometric methods. This study presents an innovative approach to leveraging a compact benchtop NMR spectrometer coupled with chemometrics for screening honey-based food supplements adulterated with active pharmaceutical ingredients. Initially, fifty samples seized by French customs were analyzed using a 60 MHz benchtop spectrometer. The investigation unveiled the presence of tadalafil in 37 samples, sildenafil in 5 samples, and a combination of flibanserin with tadalafil in 1 sample. After conducting comprehensive qualitative and quantitative characterization of the samples, we propose a chemometric workflow to provide an efficient screening of honey samples using the NMR dataset. This pipeline, utilizing partial least squares discriminant analysis (PLS-DA) models, enables the classification of samples as either adulterated or non-adulterated, as well as the identification of the presence of tadalafil or sildenafil. Additionally, PLS regression models are employed to predict the quantitative content of these adulterants. Through blind analysis, this workflow allows for the detection and quantification of adulterants in these honey supplements. Full article
(This article belongs to the Special Issue Spectroscopic Methods in Food Chemistry)
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13 pages, 1870 KiB  
Article
Low-Cost Pocket Fluorometer and Chemometric Tools for Green and Rapid Screening of Deoxynivalenol in Durum Wheat Bran
by Leonardo Ciaccheri, Annalisa De Girolamo, Salvatore Cervellieri, Vincenzo Lippolis, Andrea Azelio Mencaglia, Michelangelo Pascale and Anna Grazia Mignani
Molecules 2023, 28(23), 7808; https://doi.org/10.3390/molecules28237808 - 27 Nov 2023
Viewed by 1099
Abstract
Cereal crops are frequently contaminated by deoxynivalenol (DON), a harmful type of mycotoxin produced by several Fusarium species fungi. The early detection of mycotoxin contamination is crucial for ensuring safety and quality of food and feed products, for preventing health risks and for [...] Read more.
Cereal crops are frequently contaminated by deoxynivalenol (DON), a harmful type of mycotoxin produced by several Fusarium species fungi. The early detection of mycotoxin contamination is crucial for ensuring safety and quality of food and feed products, for preventing health risks and for avoiding economic losses because of product rejection or costly mycotoxin removal. A LED-based pocket-size fluorometer is presented that allows a rapid and low-cost screening of DON-contaminated durum wheat bran samples, without using chemicals or product handling. Forty-two samples with DON contamination in the 40–1650 µg/kg range were considered. A chemometric processing of spectroscopic data allowed distinguishing of samples based on their DON content using a cut-off level set at 400 µg/kg DON. Although much lower than the EU limit of 750 µg/kg for wheat bran, this cut-off limit was considered useful whether accepting the sample as safe or implying further inspection by means of more accurate but also more expensive standard analytical techniques. Chemometric data processing using Principal Component Analysis and Quadratic Discriminant Analysis demonstrated a classification rate of 79% in cross-validation. To the best of our knowledge, this is the first time that a pocket-size fluorometer was used for DON screening of wheat bran. Full article
(This article belongs to the Special Issue Spectroscopic Methods in Food Chemistry)
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20 pages, 8540 KiB  
Article
On-Site Evaluation of Constituent Content and Functionality of Perilla frutescens var. crispa Using Fluorescence Spectra
by Hidemichi Sano, Satoru Kawaguchi, Toshifumi Iimori, Masahiro Kuragano, Kiyotaka Tokuraku and Koji Uwai
Molecules 2023, 28(20), 7199; https://doi.org/10.3390/molecules28207199 - 20 Oct 2023
Viewed by 1502
Abstract
Perilla frutescens leaves are hypothesized to possess antioxidant and amyloid-β (Aβ) aggregation inhibitory properties primarily due to their polyphenol-type compounds. While these bioactivities fluctuate daily, the traditional methods for quantifying constituent contents and functional properties are both laborious and impractical for immediate field [...] Read more.
Perilla frutescens leaves are hypothesized to possess antioxidant and amyloid-β (Aβ) aggregation inhibitory properties primarily due to their polyphenol-type compounds. While these bioactivities fluctuate daily, the traditional methods for quantifying constituent contents and functional properties are both laborious and impractical for immediate field assessments. To address this limitation, the present study introduces an expedient approach for on-site analysis, employing fluorescence spectra obtained through excitation light irradiation of perilla leaves. Standard analytical techniques were employed to evaluate various constituent contents (chlorophyl (Chl), total polyphenol content (TPC), total flavonoid content (TFC), and rosmarinic acid (RA)) and functional attributes (DPPH radical scavenging activity, ferric reducing antioxidant power (FRAP), oxygen radical absorbance capacity (ORAC), and Aβ aggregation inhibitory activity). Correlations between the fluorescence spectra and these parameters were examined using normalized difference spectral index (NDSI), ratio spectral index (RSI), and difference spectral index (DSI) analyses. The resulting predictive model exhibited a high coefficient of determination, with R2 values equal to or greater than 0.57 for constituent contents and 0.49 for functional properties. This approach facilitates the convenient, simultaneous, and nondestructive monitoring of both the chemical constituents and the functional capabilities of perilla leaves, thereby simplifying the determination of optimal harvest times. The model derived from this method holds promise for real-time assessments, indicating its potential for the simultaneous evaluation of both constituents and functionalities in perilla leaves. Full article
(This article belongs to the Special Issue Spectroscopic Methods in Food Chemistry)
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15 pages, 4007 KiB  
Article
Evaluation of the Quality of Selected White and Red Wines Produced from Moravia Region of Czech Republic Using Physicochemical Analysis, FTIR Infrared Spectroscopy and Chemometric Techniques
by Iwona Budziak-Wieczorek, Vladimír Mašán, Klaudia Rząd, Bożena Gładyszewska, Dariusz Karcz, Patrik Burg, Alice Čížková, Mariusz Gagoś and Arkadiusz Matwijczuk
Molecules 2023, 28(17), 6326; https://doi.org/10.3390/molecules28176326 - 29 Aug 2023
Cited by 2 | Viewed by 1825
Abstract
The FTIR-ATR method coupled with the multivariate analysis of specific spectral areas of samples was developed to characterize two white grape varieties (Sauvignon Blanc and Hibernal) and two blue grape varieties (André and Cabernet Moravia) of wine planted and harvested in the Moravia [...] Read more.
The FTIR-ATR method coupled with the multivariate analysis of specific spectral areas of samples was developed to characterize two white grape varieties (Sauvignon Blanc and Hibernal) and two blue grape varieties (André and Cabernet Moravia) of wine planted and harvested in the Moravia region, Czech Republic. Principal component analysis and hierarchical cluster analysis were performed using fingerprint regions of FTIR spectra for all wines. The results obtained by principal component analysis in combination with linear discriminant analysis (PCA-LDA) scores yielded clear separation between the four classes of samples and showed very good discrimination between the wine samples, with a 91.7% overall classification rate for the samples. The conducted FTIR spectroscopy studies coupled with chemometrics allowed for the swift analysis of multiple wine components with minimal sample preparation. These methods can be used in research to improve specific properties of these wines, which will undoubtedly enhance the quality of the final wine samples obtained. Full article
(This article belongs to the Special Issue Spectroscopic Methods in Food Chemistry)
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14 pages, 4674 KiB  
Article
Rapid and Low-Cost Quantification of Adulteration Content in Camellia Oil Utilizing UV-Vis-NIR Spectroscopy Combined with Feature Selection Methods
by Qiang Liu, Zhongliang Gong, Dapeng Li, Tao Wen, Jinwei Guan and Wenfeng Zheng
Molecules 2023, 28(16), 5943; https://doi.org/10.3390/molecules28165943 - 8 Aug 2023
Cited by 6 | Viewed by 1489
Abstract
This study aims to explore the potential use of low-cost ultraviolet-visible-near infrared (UV-Vis-NIR) spectroscopy to quantify adulteration content of soybean, rapeseed, corn and peanut oils in Camellia oil. To attain this aim, test oil samples were firstly prepared with different adulterant ratios ranging [...] Read more.
This study aims to explore the potential use of low-cost ultraviolet-visible-near infrared (UV-Vis-NIR) spectroscopy to quantify adulteration content of soybean, rapeseed, corn and peanut oils in Camellia oil. To attain this aim, test oil samples were firstly prepared with different adulterant ratios ranging from 1% to 90% at varying intervals, and their spectra were collected by an in-house built experimental platform. Next, the spectra were preprocessed using Savitzky–Golay (SG)–Continuous Wavelet Transform (CWT) and the feature wavelengths were extracted using four different algorithms. Finally, Support Vector Regression (SVR) and Random Forest (RF) models were developed to rapidly predict adulteration content. The results indicated that SG–CWT with decomposition scale of 25 and the Iterative Variable Subset Optimization (IVSO) algorithm can effectively improve the accuracy of the models. Furthermore, the SVR model performed best for predicting adulteration of camellia oil with soybean oil, while the RF models were optimal for camellia oil adulterated with rapeseed, corn, or peanut oil. Additionally, we verified the models’ robustness by examining the correlation between the absorbance and adulteration content at certain feature wavelengths screened by IVSO. This study demonstrates the feasibility of using low-cost UV-Vis-NIR spectroscopy for the authentication of Camellia oil. Full article
(This article belongs to the Special Issue Spectroscopic Methods in Food Chemistry)
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