Spectroscopic Techniques in Food Quality Assessment

Spectroscopic methods have become indispensable tools for rapid, non-destructive evaluation of food composition, safety and authenticity. Techniques spanning the ultraviolet, visible, near-infrared and mid-infrared regions interrogate molecular bonds characteristic of moisture, lipids, proteins, carbohydrates and pigments. Raman spectroscopy provides complementary vibrational information, while mass‐based approaches yield detailed lipidomic and elemental fingerprints. Hyperspectral imaging integrates spatial and spectral data to map quality heterogeneity across samples. Advances in portable and miniaturised instrumentation have enabled in-field or at-line deployment, reducing reliance on laboratory infrastructure. Central to these developments are chemometric and multivariate algorithms, which extract meaningful patterns from high-dimensional data, supporting the detection of adulteration, geographic origin, maturation state and spoilage. The global food sector benefits from these methods in traceability, supply-chain integrity and quality assurance, with applications ranging from grain and fruit grading to meat provenance and dairy authentication.

Research from Nature Portfolio

Recent studies have applied mid-level data fusion of complementary mass spectrometric platforms, combining rapid evaporative ionization mass spectrometry with inductively coupled plasma mass spectrometry to determine provenance and production methods. By integrating lipidomic and elemental profiles through multivariate classification, investigators achieved complete discrimination of salmon samples by geographic origin and farming practice, uncovering a robust panel of molecular markers. This work demonstrates that multi-platform fusion greatly enhances the accuracy and reliability of food authenticity assessments and paves the way for broader implementation across diverse commodities.

Spectroscopic Techniques in Food Quality Assessment publication trend

The graph below shows the total number of articles in spectroscopic techniques in food quality assessment across all publications each year (not limited to Nature Index journals).

Technical terms

Data fusion: Integration of datasets from multiple analytical platforms to improve classification accuracy and robustness.

Chemometrics: Application of mathematical and statistical techniques to extract relevant information from complex chemical or spectral data.

Hyperspectral imaging: Acquisition of images across numerous contiguous spectral bands, providing both spatial and compositional information.

Rapid Evaporative Ionization Mass Spectrometry (REIMS): An ambient ionization approach that generates ions by rapid heating of biological samples for real-time mass spectrometric analysis.

Inductively Coupled Plasma Mass Spectrometry (ICP-MS): A technique using a high-temperature plasma to atomize and ionize samples, enabling sensitive detection of elemental composition.

References

1. Data fusion and multivariate analysis for food authenticity analysis. Nature Communications (2023).
2. Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials. Chemical Society Reviews (2014).
3. Visible-NIR ‘point’ spectroscopy in postharvest fruit and vegetable assessment: The science behind three decades of commercial use. Postharvest Biology and Technology (2020).
4. Principles and Applications of Miniaturized Near‐Infrared (NIR) Spectrometers. Chemistry - A European Journal (2020).
5. Recent Developments in Hyperspectral Imaging for Assessment of Food Quality and Safety. Sensors (2014).
6. Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis – moving out of the laboratory and into the food supply chain. Analytical Methods (2015).