Application of Non-invasive Spectral and Multi-spectral Sensors 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: closed (20 September 2024) | Viewed by 1245

Special Issue Editors


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Guest Editor
Université Clermont Auvergne, INRAE, VetAgro Sup, UMR sur le Fromage, UMRF, 63370 Lempdes, France
Interests: fluorescence spectroscopy; chemometrics; dairy products; infrared and fluorescence spectrometry; analytical chemistry; image analysis
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Guest Editor
AgriFoodtech Innovation & Research (SAFIR), F-62000 Arras, France
Interests: food sustainability; food waste valorization; food Industry 4.0 technologies; emerging food trends; food processing and analytical techniques
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Food products must be safe and authentic when delivered to consumers a goal that requires the development of reliable and robust methods for the measurement of food quality, safety, and authenticity. In general, it is time-consuming, destructive, and challenging to investigate the stability of food components using traditional analytical techniques such as chemistry- and biochemistry-based approaches. Therefore, various types of sensors that can identify food components and determine the changes that took place during processing and storage have been developed over the last few years. Among the proposed promising solutions, spectroscopy-based analytical sensors have shown good potential, enabling noninvasive, quick, and easy measurements in a variety of spectral wavelength regions, including visible/ultraviolet, mid-infrared, near-infrared, Raman, and fluorescence. Each spectral range is associated with specific physical and chemical information, making it possible to monitor the quality of the food product during processing and/or storage, and to predict its final quality. Moreover, the combination of different spectral ranges can enhance the accuracy and robustness of sensors, leading to better precision in process monitoring and quality control.

The aim of this Special Issue is to gather together the latest research, trends, and developments in spectroscopy and multi-spectroscopy sensors combined with chemometrics, particularly artificial intelligence and other advanced data analysis techniques, to authenticate food, monitor food processing, and predict quality changes during storage as well as final product quality.

In this Special Issue, original papers and review articles are welcomed.

Prof. Dr. Abderrahmane Aït-Kaddour
Dr. Abdo Hassoun
Guest Editors

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Keywords

  • sensors
  • spectroscopy
  • hyperspectral imaging
  • multispectral imaging
  • food products
  • food quality
  • food processing
  • advanced data analysis techniques

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Published Papers (1 paper)

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12 pages, 3680 KiB  
Technical Note
Simultaneous Determination of Ethanol and Methanol in Wines Using FTIR and PLS Regression
by Vasiliki Thanasi, Ilda Caldeira, Luís Santos, Jorge M. Ricardo-da-Silva and Sofia Catarino
Foods 2024, 13(18), 2975; https://doi.org/10.3390/foods13182975 - 19 Sep 2024
Viewed by 882
Abstract
Accurate quantification of ethanol and methanol is essential for regulatory compliance and product quality assurance. Fourier Transform Infrared Spectroscopy (FTIR) offers rapid, non-destructive analysis with minimal sample preparation, making it a promising tool for wine analysis. In this exploratory study, the use of [...] Read more.
Accurate quantification of ethanol and methanol is essential for regulatory compliance and product quality assurance. Fourier Transform Infrared Spectroscopy (FTIR) offers rapid, non-destructive analysis with minimal sample preparation, making it a promising tool for wine analysis. In this exploratory study, the use of FTIR and PLS regression for the simultaneous quantification of ethanol and methanol in wine samples of 11 different Portuguese mono-varietal wines and different vintages deriving from the same winery in Lisbon was investigated. A model was developed, demonstrating the feasibility of FTIR and PLS regression for the simultaneous quantification of ethanol and methanol in wine samples through dedicated models; it showed good prediction capacity for ethanol determination but poorer performance for methanol quantification. The model could be reliable enough for quality control in wine production, but to improve its performance should be enhanced in the future with more samples from different origins, wine types, and a wider concentration range in the case of methanol. Full article
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