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Vibrational Spectroscopic Sensing Technologies and Applications for the Evaluation of Food Quality and Authenticity

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 2807

Special Issue Editors


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Guest Editor
Department of Electrical and Electronic Engineering, University of Oviedo, Gijón, Spain
Interests: smart instrumentation; optical measurements; near-infrared spectroscopy; chemometrics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Physical and Analytical Chemistry, University of Oviedo, 33006 Oviedo, Spain
Interests: analytical chemistry; agrofood; near-infrared spectroscopy; chemometrics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Food may be inadvertently or intentionally contaminated with chemicals or other physical substances that are considered unacceptable by law or for other reasons.

Despite the potential of vibrational spectroscopic techniques for assessing food quality and authenticity, modern food inspection methods still require the further development of measurement equipment and dynamic chemometric analytical techniques.

This Special Issue will focus on the application of vibrational spectroscopic techniques, including near-infrared, mid-infrared, Raman spectroscopy, and hyperspectral imaging, to the evaluation of food quality and authenticity analysis.

The characteristics and applications of these techniques, along with an analysis of their major limitations, will be discussed, with an emphasis on the treatment of spectral data using chemometrics.

Researchers in the field of food will be able to present their latest findings in this Special Issue.

Dr. Francisco Ferrero
Dr. Ana Soldado
Guest Editors

Manuscript Submission Information

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Keywords

  • near-infrared spectroscopy
  • chemometrics
  • instrumentation
  • machine learning
  • food quality applications
  • food authenticity applications
 

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Published Papers (4 papers)

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Research

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15 pages, 1121 KB  
Article
Detection and Quantification of Corn Starch and Wheat Flour as Adulterants in Milk Powder by Raman Spectroscopy Coupled with Chemometric Routines
by Edwin R. Caballero-Agosto, Louang D. Cruz-Dorta, Samuel P. Hernandez-Rivera, Leonardo C. Pacheco-Londoño and Ricardo Infante-Castillo
Sensors 2026, 26(4), 1304; https://doi.org/10.3390/s26041304 - 18 Feb 2026
Viewed by 386
Abstract
Adulteration of milk powder (MP) is performed, especially in underdeveloped countries, by adding corn starch (CS) or wheat flour (WF) without mentioning it. Multiple techniques have been established to reduce these deceptive methods. Most of these techniques require samples to be sent to [...] Read more.
Adulteration of milk powder (MP) is performed, especially in underdeveloped countries, by adding corn starch (CS) or wheat flour (WF) without mentioning it. Multiple techniques have been established to reduce these deceptive methods. Most of these techniques require samples to be sent to the laboratory for results through a time-consuming, expert-requiring, and destructive procedure. Raman spectroscopy (RS) has seen application due to the availability of portable modalities and its non-destructive, water-insensitive nature. Using principal component analysis (PCA), the differences and similarities between MP and the adulterants (CS and WF) have been evaluated. To quantify the percentages of CS and WF binary mixtures independently with MP, partial least squares regression (PLSR) has been employed. A total of 70 MP samples independently adulterated with CS and WF were prepared. Thirteen chemometric modes were developed by combining the first and second derivatives with Standard Normal Variate (SNV) and Multiplicative Scatter Correction (MSC) to quantify adulteration. The results obtained for CS and WF mixtures show errors of 0.76 and 0.77 %w/w, respectively, with the optimized math pretreatment. These results demonstrate that the portable RS modality can be used as an effective technique for detecting adulterants in milk powder. Full article
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11 pages, 1823 KB  
Article
Comparison of Benchtop and Portable Near-Infrared Instruments to Predict the Type of Microplastic Added to High-Moisture Food Samples
by Adam Kolobaric, Shanmugam Alagappan, Jana Čaloudová, Louwrens C. Hoffman, James Chapman and Daniel Cozzolino
Sensors 2026, 26(1), 210; https://doi.org/10.3390/s26010210 - 29 Dec 2025
Viewed by 547
Abstract
Near-infrared (NIR) spectroscopy is a rapid, non-destructive analytical tool widely used in the food and agricultural sectors. In this study, two NIR instruments were compared for classifying the addition of microplastics (MPs) to high-moisture-content samples such as vegetables and fruit. Polyethylene (PE), polypropylene [...] Read more.
Near-infrared (NIR) spectroscopy is a rapid, non-destructive analytical tool widely used in the food and agricultural sectors. In this study, two NIR instruments were compared for classifying the addition of microplastics (MPs) to high-moisture-content samples such as vegetables and fruit. Polyethylene (PE), polypropylene (PP), and a mix of polymers (PE + PP) MP were added to mixtures of spinach and banana and scanned using benchtop (Bruker Tango) and portable (MicroNIR) instruments. Both principal component analysis (PCA) and partial least squares (PLS) were used to analyze and interpret the spectra of the samples. Quantitative models were developed to predict the addition of Mix, PP, or PE to spinach and banana samples using PLS regression. The R2 CV and the SECV obtained were 0.88 and 0.44 for the benchtop samples, and 0.54 and 0.67 for the portable instruments, respectively. Two wavenumber regions were also evaluated: 11,520–7500 cm−1 (short to medium wavelengths), and 7500–4200 cm−1 (long wavelengths). The R2 CV and the SECV obtained were 0.88 and 0.46, 0.86 and 0.49, respectively, for the prediction of addition in samples analyzed on the benchtop instrument using short and long wavenumbers, respectively. This study provides new insights into the comparison of two instruments for detecting the addition of MPs in high-moisture samples. The results of this study will ensure that NIR can be utilized not only to measure the quality of these samples but also to monitor MPs. Full article
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Review

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24 pages, 1913 KB  
Review
Trends in Vibrational Spectroscopy: NIRS and Raman Techniques for Health and Food Safety Control
by Candela Melendreras, Jesús Montero, José M. Costa-Fernández, Ana Soldado, Francisco Ferrero, Francisco Fernández Linera, Marta Valledor and Juan Carlos Campo
Sensors 2026, 26(3), 989; https://doi.org/10.3390/s26030989 - 3 Feb 2026
Viewed by 597
Abstract
There is an increasing need to establish reliable safety controls in the food industry and to protect public health. Consequently, there are numerous efforts to develop sensitive, robust, and selective analytical strategies. As regulatory requirements for food and the concentration for target biomarkers [...] Read more.
There is an increasing need to establish reliable safety controls in the food industry and to protect public health. Consequently, there are numerous efforts to develop sensitive, robust, and selective analytical strategies. As regulatory requirements for food and the concentration for target biomarkers in clinical analysis evolve, the food and health sectors are showing a growing interest in developing non-destructive, rapid, on-site, and environmentally safe methodologies. One alternative that meets the conditions is non-destructive spectroscopic sensors, such as those based on vibrational spectroscopy (Raman, surface-enhanced Raman—SERS, mid- and near-infrared spectroscopy, and hyperspectral imaging built on those techniques). The use of vibrational spectroscopy in food safety and health applications is expanding rapidly, moving beyond the laboratory bench to include on-the-go and in-line deployment. The dominant trends include the following: (1) the miniaturisation and portability of instruments; (2) surface-enhanced Raman spectroscopy (SERS) and nanostructured substrates for the detection of trace contaminants; (3) hyperspectral imaging (HSI) and deep learning for the spatial screening of quality and contamination; (4) the stronger integration of chemometrics and machine learning for robust classification and quantification; (5) growing attention to calibration transfer, validation, and regulatory readiness. These advances will bring together a variety of tools to create a real-time decision-making system that will address the issue in question. This article review aims to highlight the trends in vibrational spectroscopy tools for health and food safety control, with a particular focus on handheld and miniaturised instruments. Full article
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14 pages, 257 KB  
Review
New Developments and Future Challenges of Non-Destructive Near-Infrared Spectroscopy Sensors in the Cheese Industry
by Maria Tarapoulouzi, Wenyang Jia and Anastasios Koidis
Sensors 2026, 26(2), 556; https://doi.org/10.3390/s26020556 - 14 Jan 2026
Cited by 1 | Viewed by 679
Abstract
Near-infrared (NIR) spectroscopy has emerged as a pivotal non-destructive analytical technique within the cheese industry, offering rapid and precise insights into the chemical composition and quality attributes of various cheese types. This review explores the evolution of NIR spectral sensors, highlighting key technological [...] Read more.
Near-infrared (NIR) spectroscopy has emerged as a pivotal non-destructive analytical technique within the cheese industry, offering rapid and precise insights into the chemical composition and quality attributes of various cheese types. This review explores the evolution of NIR spectral sensors, highlighting key technological advancements and their integration into cheese production processes as well as final products already in markets. In addition, the review discusses challenges such as calibration complexities, the influence of sample heterogeneity and the need for robust data and interpretation models through spectroscopy coupled with AI methods. The future potential of NIR spectral sensors, including real-time in-line monitoring and the development of portable devices for on-site analysis, is also examined. This review aims to provide a critical assessment of current NIR spectral sensors and their impact on the cheese industry, offering insights for researchers and industry professionals aiming to enhance quality control and innovation in cheese production, as well as authenticity and fraud studies. The review concludes that the integration of advanced NIR spectroscopy with AI represents a transformative approach for the cheese industry, enabling more accurate, efficient and sustainable quality assessment practices that can strengthen both production consistency and consumer trust. Full article
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