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Applications of Spectroscopic Techniques in Food Sample Analysis
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Applications of Spectroscopic Techniques in Food Sample Analysis

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

Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 4750

Special Issue Editors

Dr. Raquel Sánchez Romero

E-Mail Website
Guest Editor
Department of Analytical Chemistry, Nutrition and Food Science, University of Alicante, Carretera San Vicente del Raspeig, S/N, 03690 San Vicente del Raspeig, Alicante, Spain
Interests: inductively coupled plasma; ICP-OES; ICP-MS; ICP-MS/MS; dispersive liquid–liquid extraction; environmental analysis; fuel analysis; biofuel analysis; food analysis; clinical analysis; certified reference material production; food disinfection
Dr. Stefano Dall'Acqua

E-Mail Website
Guest Editor
Pharmaceutical and Pharmacological Sciences, Universita degli Studi di Padova, Padua, Italy
Interests: bioactive natural products; terpenoids; phenolics; saponins; alkaloids; NMR; LC-MS; GC-MS
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Food products are very complex mixtures consisting of naturally occurring compounds and other substances that generally originate from technological processes, agrochemical treatments, or packaging materials. Spectroscopy is a key analytical technique in the analysis of food, enabling complex organic substances to be separated and identified.

This Special Issue, entitled “Applications of Spectroscopic Techniques in Food Sample Analysis”, calls for the latest innovative methodologies applied to food analysis. Works related to food components or food-contaminant detection methods for migrants (intentionally and non-intentionally added substances) are welcome, in addition to works related to liquid and/or gas chromatography, ICP techniques, mass spectrometry, and UV, IR, and Raman spectroscopy. Submissions may take the form of either reviews or research articles.

Dr. Raquel Sánchez Romero
Dr. Stefano Dall'Acqua
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 sample
  • food safety
  • mass spectrometry
  • spectroscopic techniques
  • Raman spectroscopy

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Published Papers (3 papers)

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Research

16 pages, 3429 KiB  
Article
Beef Traceability Between China and Argentina Based on Various Machine Learning Models
by Xiaomeng Xiang, Chaomin Zhao, Runhe Zhang, Jing Zeng, Liangzi Wang, Shuran Zhang, Diego Cristos, Bing Liu, Siyan Xu and Xionghai Yi
Molecules 2025, 30(4), 880; https://doi.org/10.3390/molecules30040880 - 14 Feb 2025
Viewed by 577
Abstract
Beef, as a nutrient-rich food, is widely favored by consumers. The production region significantly influences the nutritional value and quality of beef. However, current methods for tracing the origin of beef are still under development, necessitating effective approaches to ensure food safety and [...] Read more.
Beef, as a nutrient-rich food, is widely favored by consumers. The production region significantly influences the nutritional value and quality of beef. However, current methods for tracing the origin of beef are still under development, necessitating effective approaches to ensure food safety and meet consumer demand for high-quality beef. This study aims to establish a classification model for beef origin prediction by analyzing elemental content and stable isotopes in beef samples from two countries. The concentrations of elements in beef were analyzed using ICP-MS and ICP-OES, while the stable carbon isotope ratio was determined using EA-IRMS. Machine learning algorithms were employed to construct classification prediction models. A total of 83 beef samples were analyzed for the concentrations of 52 elements and the stable carbon isotope ratio. The classification accuracy of the PLS-DA model built on these results was 98.8%, while the prediction accuracy was 94.12% for the convolutional neural network (CNN) and 82.35% for the Random Forest algorithm. The PLS-DA model demonstrated higher classification accuracy compared to CNN and Random Forest, with an explanatory power (R2) of 0.924 and predictive ability (Q2) of 0.787. Combining the analysis of 52 elements and the stable carbon isotope ratio with machine learning algorithms enables effective tracing and origin prediction of beef from different regions. Key factors influencing beef origin were identified as Fe, Cs, As, δ13C, Co, V, Sc, Rb, and Ru. Full article
(This article belongs to the Special Issue Applications of Spectroscopic Techniques in Food Sample Analysis)
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17 pages, 4999 KiB  
Article
A Comparison of the Impacts of Different Drying Methods on the Volatile Organic Compounds in Ginseng
by Yun Xiang, Manshu Zou, Feilin Ou, Lijun Zhu, Yingying Xu, Qingqing Zhou and Chang Lei
Molecules 2024, 29(22), 5235; https://doi.org/10.3390/molecules29225235 - 5 Nov 2024
Cited by 1 | Viewed by 1258
Abstract
Ginseng (Panax ginseng C. A. Meyer) is a valuable plant resource which has been used for centuries as both food and traditional Chinese medicine. It is popular in health research and markets globally. Fresh ginseng has a high moisture content and is [...] Read more.
Ginseng (Panax ginseng C. A. Meyer) is a valuable plant resource which has been used for centuries as both food and traditional Chinese medicine. It is popular in health research and markets globally. Fresh ginseng has a high moisture content and is prone to mold and rot, reducing its nutritional value without proper preservation. Drying treatments are effective for maintaining the beneficial properties of ginseng post-harvest. In this study, we investigated the effects of natural air drying (ND), hot-air drying (HAD), vacuum drying (VD), microwave vacuum drying (MVD), and vacuum freeze drying (VFD) on volatile organic compounds (VOCs) in ginseng. The results showed that the MVD time was the shortest, followed by the VFD, VD, and HAD times, whereas the ND time was the longest, but the VFD is the most beneficial to the appearance and color retention of ginseng. A total of 72 VOCs were obtained and 68 VOCs were identified using the five drying methods based on gas chromatography–ion mobility spectrometry (GC-IMS) technology, including 23 aldehydes, 19 alkenes, 10 alcohols, 10 ketones, 4 esters, 1 furan, and 1 pyrazine, and the ND method was the best for retaining VOCs. GC-IMS fingerprints, principal component analysis (PCA), Euclidean distance analysis, partial least squares discriminant analysis (PLS-DA), and cluster analysis (CA) can distinguish ginseng from different drying methods. A total of 29 VOCs can be used as the main characteristic markers of different drying methods in ginseng. Overall, our findings provide scientific theoretical guidance for optimizing ginseng’s drying methods, aromatic health effects, and flavor quality research. Full article
(This article belongs to the Special Issue Applications of Spectroscopic Techniques in Food Sample Analysis)
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21 pages, 5713 KiB  
Article
The Impact of Different Drying Methods on the Metabolomic and Lipidomic Profiles of Arthrospira platensis
by Marika Mróz, Karol Parchem, Joanna Jóźwik, M. Rosário Domingues and Barbara Kusznierewicz
Molecules 2024, 29(8), 1747; https://doi.org/10.3390/molecules29081747 - 12 Apr 2024
Cited by 3 | Viewed by 1921
Abstract
Drying is an inseparable part of industrial microalgae production. In this work, the impacts of eight different drying methods on the metabolome and lipidome of Arthrospira platensis were investigated. The studied drying methods were freeze drying (FD), sun drying (SD), air drying at [...] Read more.
Drying is an inseparable part of industrial microalgae production. In this work, the impacts of eight different drying methods on the metabolome and lipidome of Arthrospira platensis were investigated. The studied drying methods were freeze drying (FD), sun drying (SD), air drying at 40 and 75 °C (AD′ and AD″), infrared drying at 40 and 75 °C (IRD′ and IRD″), and vacuum drying at 40 and 75 °C (VD′ and VD″). Results gathered by reversed-phase liquid chromatography separation coupled with high-resolution tandem mass spectrometry with electrospray ionization (RP-LC-ESI-Orbitrap HRMS/MS) analysis allowed researchers to identify a total of 316 metabolites (including lipids) in aqueous and ethanolic extracts. The compounds identified in ethanolic extracts were mainly lipids, such as neutral and polar lipids, chlorophylls and carotenoids, while the compounds identified in the aqueous extracts were mainly amino acids and dipeptides. Among the identified compounds, products of enzymatic and chemical degradation, such as pyropheophytins, monoacylglycerols and lysophosphatidylcholines were also identified and their amounts depended on the drying method. The results showed that except for FD method, recognized as a control, the most protective method was AD′. Contrary to this, VD′ and VD″, under the conditions used, promoted the most intense degradation of valuable metabolites. Full article
(This article belongs to the Special Issue Applications of Spectroscopic Techniques in Food Sample Analysis)
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