FT-NIR and Raman Spectroscopic Methods Enhance Food Quality Control

Hazelnuts displayed near an oil bottle of hazelnut oil ©OBSIMAGES AI - stock.adobe.com

In the fast-paced food industry, ensuring the quality of raw materials is crucial, particularly for products like hazelnuts (Corylus avellana L.), which are key ingredients in many confectionery items. Hazelnuts often undergo long-term storage, making them vulnerable to defects such as rancidity and microorganism growth. Traditional methods for assessing quality during incoming inspections can be slow and require extensive sample preparation and analysis. However, a new study conducted by researchers from the Hamburg School of Food Science and the University of Hamburg (Germany) highlights a faster, more efficient alternative using advanced spectroscopy techniques (1).

The Research and Findings

The research, published in the journal Food Analytical Methods, was led by Henri Lösel and a team of scientists including Navid Shakiba, René Bachmann, Soeren Wenck, Phat Le Tan, Marina Creydt, Stephan Seifert, Thomas Hackl, and Markus Fischer. The study assessed the ability of two cutting-edge spectroscopic methods—Fourier transform near-infrared (FT-NIR) spectroscopy and spatially offset Raman spectroscopy (SORS)—to detect storage-related defects in hazelnuts. The team analyzed six batches of hazelnuts stored under varying conditions of temperature, humidity, and storage duration to determine how these factors affected the nuts’ quality. These analytical techniques have proven useful for hazelnut and other food quality assessments (1–3).

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FT-NIR Spectroscopy

FT-NIR spectroscopy emerged as a particularly valuable tool for identifying defects in hazelnuts, especially under extreme storage conditions such as high temperature and humidity. One of the advantages of this technique is its ability to detect differences between hazelnut batches without the need for freeze-drying—a time-consuming step required in other analytical methods (1–3).

According to the study, FT-NIR spectroscopy was able to discern storage-induced changes in the metabolome and proteome of hazelnuts, even in non-freeze-dried samples, thus making it a faster option for real-time quality inspections (1).

The technique works by measuring how the hazelnuts absorb near-infrared light, which varies depending on their internal composition. The most significant differences between pre- and post-stored samples were related to water content changes. Interestingly, the researchers found that FT-NIR spectroscopy was effective even when only one of the storage parameters, such as temperature or humidity, was altered (1).

SORS Analysis

While FT-NIR spectroscopy showed promise for detecting defects across a range of storage conditions, the study revealed that SORS had limitations in some scenarios. Specifically, when only one storage parameter was changed (for example, just temperature or just humidity), SORS was less effective in distinguishing between fresh and stored hazelnuts. However, the researchers highlighted that SORS could still play a complementary role in quality control (1).

SORS, which separates the laser and detector to measure samples through packaging, is particularly useful for inline inspections where opening packaging is not feasible. In certain storage conditions, particularly under long-term low-temperature storage, SORS offered valuable insights when used in conjunction with FT-NIR spectroscopy. The two techniques provided complementary data, leading to more accurate classification of hazelnut samples, especially after freeze-drying (1).

Read More: SORS Technique

The Benefits of Combining Methods

The study also explored the benefits of combining FT-NIR and SORS data through a process known as low-level data fusion. This approach improved the accuracy of defect detection, particularly for hazelnuts stored under moderate conditions. For example, samples stored at 10°C and 19 °C showed better classification when both spectroscopic techniques were used together. This suggests that, while FT-NIR may be the go-to method for rapid inspections, adding SORS to the process can further enhance the precision of the analysis (1).

This research provides a promising new approach for the food industry, where the rapid and reliable detection of raw material defects is crucial. By demonstrating the effectiveness of FT-NIR spectroscopy and the complementary role of SORS, the study lays the groundwork for faster, more accurate hazelnut inspections. This could help manufacturers ensure higher quality products while reducing reliance on slower, more complex methods such as mass spectrometry (MS) or nuclear magnetic resonance (NMR) spectroscopy (1).

With further development, these technologies could transform quality control—not only for hazelnuts, but for a wide range of food products susceptible to storage-related defects (1–3).

References

(1) Lösel, H.; Shakiba, N.; Bachmann, R.; et al. Rapid Testing in the Food Industry: the Potential of Fourier Transform Near-Infrared (FT-NIR) Spectroscopy and Spatially Offset Raman Spectroscopy (SORS) to Detect Raw Material Defects in Hazelnuts (Corylus avellana L.). Food Anal. Methods 2024, 17, 486–497. DOI: 10.1007/s12161-024-02578-w

(2) Vega-Castellote, M.; Sánchez, M. T.; Torres-Rodríguez, I.; Entrenas, J. A.; Pérez-Marín, D. NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review. Foods 2024, 13 (11), 612. DOI: 10.3390/foods13111612

(3) Özdemir, İ. S.; Firat, E. Ö.; Özturk, T.; Zomp, G.; Arici, M. Geographical Origin Determination of the PDO Hazelnut (cv. Giresun Tombul) by Chemometric Analysis of FT‐NIR and Raman Spectra Acquired From Shell and Kernel. J. Food Sci. 2024, 89 (8), 4806–4822. DOI: 10.1111/1750-3841.17214