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The Potential of Raman Spectroscopy as a Rapid Method for Monitoring Shelf Life and Freshness of Refrigerated Rainbow Trout Fillet

https://doi.org/10.36107/spfp.2025.1.627

Abstract

Background: Rainbow trout (Oncorhynchus mykiss) is among the most commercially important freshwater fish species worldwide. Rainbow trout fillets are recognized for their high nutritional value and beneficial biological properties. However, fresh fish is a highly perishable food with a limited shelf life. Ensuring consistent quality and safety of fresh fish products remains a critical challenge for processors and suppliers. Among non-destructive quality evaluation techniques, Raman spectroscopy emerges as a promising approach for quality and safety monitoring in the food industry. Despite its proven effectiveness, Raman spectroscopy remains significantly understudied for assessing freshness and shelf-life in fish products. This research gap was addressed by providing novel insights into the application of Raman spectroscopy for fish freshness monitoring.

Purpose: To investigate the potential of Raman spectroscopy for assessing the shelf life and freshness of refrigerated rainbow trout fillets, and to determine key spectral characteristics that enable monitoring of product quality changes during storage.

Materials and Methods: The study object was refrigerated rainbow trout (Oncorhynchus mykiss) fillets stored at +2±2 °C. The shelf-life assessment, freshness evaluation and quality monitoring were performed using a Nanoscope NS100 series Raman spectrometer with 785 nm excitation wavelength and 100-3200 cm⁻¹ spectral range. Measurements were conducted during 16 days of refrigerated storage.

Results: The Raman spectral analysis demonstrated distinct variations in the spectra of rainbow trout samples and corresponding to different storage durations, revealing lipid oxidation levels. The lowest intensity was observed in fresh samples stored for 0–3 days, enabling clear differentiation from other groups. Sample fluorescence was detected during the analysis, introducing additional noise to the spectra. The 3D mathematical model demonstrated the highest percentage of total variance (92%) for chilled rainbow trout.

Conclusion: The obtained results demonstrate the potential of Raman spectroscopy as a rapid-assessment and non-destructive monitoring techniques for fish quality and shelf-life evaluation. This method holds practical significance for food safety regulatory authorities and consumers. Successful implementation of the technique requires minimization of fluorescence background interference, including the application of chemometric approaches, which would improve the accuracy of predictive models.

About the Authors

Daria Dmitrievna Vilkova
Cherepovets State University
Russian Federation


Maria Alexeevna Belova
Cherepovets State University
Russian Federation


Mikhail Nikolaevich Kutuzov
Cherepovets State University
Russian Federation


Olga Victorovna Novichenko
Astrakhan State University name of V.N. Tatishchev, Cherepovets State University
Russian Federation


Konstantin Vladimirovich Shter
Cherepovets State University
Russian Federation


Igor Alexeevich Nikitin
Plekhanov Russian University of Economics
Russian Federation


References

1. Chen, Z., Wu, T., Xiang, C., Xu, X., & Tian, X. (2019). Rapid identification of rainbow trout adulteration in Atlantic salmon by Raman spectroscopy combined with machine learning. Molecules, 24(15), 2851. https://doi.org/10.3390/molecules24152851

2. Cheng, J., Dai, Q., Sun, D., Zeng, X., Liu, D., & Pu, H. (2013). Applications of non-destructive spectroscopic techniques for fish quality and safety evaluation and inspection. Trends in Food Science & Technology, 34(1), 18–31. https://doi.org/10.1016/j.tifs.2013.08.005

3. Chytiri, S., Chouliara, I., Savvaidis, I. N., & Kontominas, M. G. (2004). Microbiological, chemical and sensory assessment of iced whole and filleted aquacultured rainbow trout. Food Microbiology, 21(2), 157–165. https://doi.org/10.1016/S0740-0020(03)00059-5

4. Czamara, K., Majzner, K., Pacia, M.Z., Kochan, K., Kaczor, A., & Baranska, M. (2015). Raman spectroscopy of lipids: A review. Journal of Raman Spectroscopy, 46(1), 4–20. https://doi.org/10.1002/jrs.4607

5. Hassoun, A., & Karoui, R. (2017). Quality evaluation of fish and other seafood by traditional and nondestructive instrumental methods: Advantages and limitations. Critical Reviews in Food Science and Nutrition, 57(9), 1976–1998. https://doi.org/10.1080/10408398.2015.1047926

6. Hassoun, A., Sahar, A., Lakhal, L., & Aït-Kaddour, A. (2019). Fluorescence spectroscopy as a rapid and non-destructive method for monitoring quality and authenticity of fish and meat products: Impact of different preservation conditions. LWT, 103, 279–292. https://doi.org/10.1016/j.lwt.2019.01.021

7. Hernández, M. D., López, M. B., Álvarez, A., Ferrandini, E., García, B. G., & Garrido, M. D. (2009). Sensory, physical, chemical and microbiological changes in aquacultured meagre (Argyrosomus regius) fillets during ice storage. Food Chemistry, 114(1), 237–245. https://doi.org/10.1016/j.foodchem.2008.09.045

8. Herrero, A. (2008). Raman spectroscopy a promising technique for quality assessment of meat and fish: A review. Food Chemistry, 107, 1642-1651. https://doi.org/10.1016/j.foodchem.2007.10.014

9. Jaafreh, S., Breuch, R., Günther, K. et al. (2018). Rapid poultry spoilage evaluation using portable fiber-optic Raman spectrometer. Food Analytical Methods, 11, 2320–2328. https://doi.org/10.1007/s12161-018-1223-0

10. Kashani Zadeh, H., Hardy, M., Sueker, M., Li, Y., Tzouchas, A., MacKinnon, N., Bearman, G., Haughey, S. A., Akhbardeh, A., Baek, I., Hwang, C., Qin, J., Tabb, A. M., Hellberg, R. S., Ismail, S., Reza, H., Vasefi, F., Kim, M., Tavakolian, K., & Elliott, C. T. (2023). Rapid assessment of fish freshness for multiple supply-chain nodes using multi-mode spectroscopy and fusion-based Artificial Intelligence. Sensors, 23(11), 5149. https://doi.org/10.3390/s23115149

11. Landry, J.D., Torley, P.J., & Blanch, E.W. (2020). Detection of biomarkers relating to quality and differentiation of some commercially significant whole fish using spatially off-set Raman spectroscopy. Molecules, 25, 3776. https://doi.org/10.3390/molecules25173776

12. Ocaño-Higuera, V. M., Maeda-Martínez, A. N., Marquez-Ríos, E., Canizales-Rodríguez, D. F., Castillo-Yáñez, F. J., Ruíz-Bustos, E., Graciano-Verdugo, A. Z., & Plascencia-Jatomea, M. (2011). Freshness assessment of ray fish stored in ice by biochemical, chemical and physical methods. Food Chemistry, 125(1), 49–54. https://doi.org/10.1016/j.foodchem.2010.08.034

13. Poli, B. M., Messini, A., Parisi, G., Scappini, F., Vigiani, V., Giorgi, G., & Vincenzini, M. (2006). Sensory, physical, chemical and microbiological changes in European sea bass (Dicentrarchus labrax) fillets packed under modified atmosphere/air or prepared from whole fish stored in ice. International Journal of Food Science and Technology, 41(4), 444–454. https://doi.org/10.1111/j.1365-2621.2005.01094.x

14. Raskovic, B., Heinke, R., Roesch, P., & Popp, J. (2016). The Potential of Raman Spectroscopy for the Classification of Fish Fillets. Food Analytical Methods, 9, 1301-1306. https://doi.org/10.1007/s12161-015-0312-6

15. Rødbotten, M., Lea, P., & Øydis U. (2009). Quality of raw salmon fillet as a predictor of cooked salmon quality. Food Quality and Preference, 20, 13–23. https://doi.org/10.1016/j.foodqual.2008.06.004

16. Sowoidnich, K., Schmidt, H., Kronfeldt, H., & Schwägele, F. (2012). A Portable 671 nm Raman Sensor System for Rapid Meat Spoilage Identification. Vibrational Spectroscopy, 62, 70-76. https://doi.org/10.1016/j.vibspec.2012.04.002

17. Sui, Y., Zhang L., Lu, S., Yang, D., & Zhu, C. (2020). Research on the shrimp quality of different storage conditions based on Raman spectroscopy and prediction model. Spectroscopy and Spectral Analysis, 40, 5, 1607-1613. https://doi.org/10.3964/j.issn.1000-0593(2020)05-1607-07

18. Sun, Y., Tang, H., Zou, X., Meng, G., & Wu, N. (2022). Raman spectroscopy for food quality assurance and safety monitoring: A review. Current Opinion in Food Science, 47, 100910. https://doi.org/10.1016/j.cofs.2022.100910

19. Velioğlu, H., Temiz, T., & Boyacı, I. (2015). Differentiation of fresh and frozen-thawed fish samples using Raman spectroscopy coupled with chemometric analysis. Food Chemistry, 172, 283–290. https://doi.org/10.1016/j.foodchem.2014.09.073

20. Vilkova, D., Chene, C., Kondratenko, E., & Karoui, R. (2021). A comprehensive review on the assessment of the quality and authenticity of the sturgeon species by different analytical techniques. Food Control, 133, 108648. https://doi.org/10.1016/j.foodcont.2021.108648

21. Wu, L. & Pu, H., & Sun, D. (2018). Novel techniques for evaluating freshness quality attributes of fish: A review of recent developments. Trends in Food Science & Technology, 83. https://doi.org/10.1016/j.tifs.2018.12.002

22. Xu, K., Yi, Y., Deng, J., Wang, Y., Zhao, B., Sun, Q., Gong, C., Yang, Z., Wan, H., He, R., Wu, X., Yao, B., Zhang, M., & Tang, Y. (2022). Evaluation of the freshness of rainbow trout (Oncorhynchus mykiss) fillets by the NIR, E-nose and SPME-GC-MS. RSC Advances, 12(19), 11591-11603. https://doi.org/10.1039/d2ra00038e

23. Yao, J., Yue, Z., Lin, H., Wang, L., Wang, K., & Li, J. (2023). Non-destructive monitoring the freshness of sea bass fillets using Raman spectroscopy with orthogonal signal correction and multivariate analysis. Microchemical Journal, 191, 108859. https://doi.org/10.1016/j.microc.2023.108859

24. Zhong, N., Li, Y., Li, X., Guo, C., & Wu, T. (2021). Accurate prediction of salmon storage time using improved Raman spectroscopy. Journal of Food Engineering, 293, 110378. https://doi.org/10.1016/j.jfoodeng.2020.110378


Review

For citations:


Vilkova D.D., Belova M.A., Kutuzov M.N., Novichenko O.V., Shter K.V., Nikitin I.A. The Potential of Raman Spectroscopy as a Rapid Method for Monitoring Shelf Life and Freshness of Refrigerated Rainbow Trout Fillet. Storage and Processing of Farm Products. 2025;33(1):161-171. (In Russ.) https://doi.org/10.36107/spfp.2025.1.627

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ISSN 2072-9669 (Print)
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