Trends on vibrational spectroscopy tools in the agri-food sector
Candela Melendreras1, Jesús Montero2, José M Costa-Fernández2
1Department of Physical and Analytical Chemistry, University of Oviedo, Avda. Julián Clavería 8, 33006, Oviedo, Spain. melendrerascandela@uniovi.es.
Analytical and Bioanalytical Chemistry
|October 18, 2025
Summary
Non-destructive spectroscopic sensors (NDSS) offer rapid, in-situ food analysis. Advanced AI and machine learning enhance these vibrational spectroscopy methods for real-time quality control across the food supply chain.
Area of Science:
- Food Science and Technology
- Analytical Chemistry
- Spectroscopy
Background:
- Increasing global demand and regulatory pressures necessitate enhanced food safety and quality assurance.
- Traditional analytical methods often lack the speed, selectivity, or non-destructive capabilities required for modern food supply chains.
- Non-destructive spectroscopic sensors (NDSS) are emerging as critical tools for addressing these analytical challenges.
Purpose of the Study:
- To review the potential of non-destructive spectroscopic sensors (NDSS) for food safety and quality control.
- To highlight advancements in instrumentation, including miniaturization and portability.
- To discuss the role of advanced data analysis techniques, such as chemometrics and artificial intelligence (AI), in spectral data interpretation.
Main Methods:
- Utilizing vibrational spectroscopy, specifically near-infrared (NIR) and Raman spectroscopy, for non-destructive sample analysis.
- Developing miniaturized and cost-effective spectroscopic instrumentation for portable, real-time applications.
- Applying advanced chemometric techniques and machine learning algorithms for spectral data processing and predictive modeling.
Main Results:
- NDSS, particularly NIR and Raman spectroscopy, show significant promise for rapid, in-situ analysis of food matrices without sample degradation.
- Miniaturization efforts are leading to portable devices for real-time food monitoring throughout the supply chain.
- AI and machine learning are revolutionizing spectral data interpretation, improving model calibration, transferability, and reliability.
Conclusions:
- Advanced vibrational spectroscopy, coupled with AI, offers intelligent, real-time decision-making systems for food production and distribution.
- These technologies are poised to redefine food quality control standards in modern agri-food systems.
- The integration of NDSS supports sustainable, efficient, and safe food production.
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