Near-infrared spectroscopy: a non-invasive tool for quality evaluation of seafood

Sayari Chakrabarti, S. Chowdhury, Swarnadyuti Nath, P. Murmu and Deboshmita Dey

Department of Fish Processing Technology, Faculty of Fishery Sciences,

West Bengal University of Animal and Fishery Sciences, Kolkata, India

swarnadyutinath@gmail.com

Article History:  Received: Nov 20, 2020 / Revised: Dec 17, 2020/ Accepted: Dec 20, 2020

Abstract

 The present-day food supply chain is globalized, and this has led to an increase in awareness among consumers regarding seafood quality measures. For ensuring the quality parameters, although suitable preservation techniques are used, industries still face quality issues during production, storage, and distribution. However, traditional methods like sensory evaluation, biochemical and microbiological analysis are cumbersome, susceptible to variations in results, and time-consuming paving the way to explore alternative tools for quality assessment. Thus, non-destructive optical techniques involving visible and near-infrared wavelengths are now being applied for evaluating the quality of seafood on a real-time basis enabling online monitoring of all product samples. The infrared radiation of the electromagnetic spectrum is the invisible band between the visible and microwave region, having a wavelength range of 0.76 to 350 µm emitted out of substances whose temperature exceeds absolute zero, from the sun to electric heaters and gas-fired heaters. NIR techniques utilize the concept that molecules tend to absorb specific frequencies of light characterizing the corresponding structure of the molecules, enable rapid data acquisition, saves time, and determines multiple parameters. In Near-Infrared spectroscopy, the substance to be analyzed is illuminated with a broad-spectrum near-infrared source, by absorption, transmittance, reflectance, or scattering. This article reviews the application of Near-Infrared Spectroscopy for the seafood quality assessment, different modes of spectra measurement, and various instruments used in Near-Infrared Spectroscopy. Near-Infrared Spectroscopy coupled with chemometrics is a propitious tool useful in the prediction of several fish and seafood’s quality attributes and authentication of various fish-and-fishery products.

Keywords Seafood Quality Assessment, Spectroscopy, Near- Infrared Spectroscopy, NIR Mode of Operation, NIR Functionality

How to cite this article

Chakrabarti, S., Chowdhury, S.,  Nath, S., Murmu, P. and Dey, D. (2020).  Near-infrared spectroscopy: a non-invasive tool for quality evaluation of seafood. Science Archives, Vol. 1 (3), 132-141.

Crossref DOI

http://dx.doi.org/10.47587/SA.2020.1310

Copyright

This is an open-access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

References

Aboud, S. A., Altemimi, A. B., RS Al-HiIphy, A., Yi-Chen, L., & Cacciola, F. (2019). A comprehensive review on infrared heating applications in food  processing. Molecules, 24(22), 4125.

Alander, J. T., Bochko, V., Martinkauppi, B., Saranwong, S., &Mantere, T. (2013). A Review of Optical Nondestructive Visual and Near-Infrared Methods for Food Quality and Safety. International Journal of Spectroscopy, 2013, 1-36, Article ID 341402. http://dx.doi.org/10.1155/2013/341402.

André, J., & Lawler, I. R. (2003). Near infrared spectroscopy as a rapid and inexpensive means of dietary analysis for the marine herbivore, dugong Dugong dugon. Marine Ecology Progress Series, 257, 259-266.

Andrés, S., Murray, I., Navajas, E. A., Fisher, A. V., Lambe, N. R., & Bünger, L. (2007). Prediction of sensory characteristics of lamb meat samples by near infrared reflectance spectroscopy. Meat Science, 76(3), 509-516.

Bellato, S., Frate, V. D., Redaelli, R., Sgrulletta, D., Bucci, R., Magrì, A. D., & Marini, F. (2011). Use of near infrared reflectance and transmittance      coupled to robust calibration for the evaluation of nutritional value in naked oats. Journal of Agricultural and Food Chemistry, 59(9), 4349-4360.

Carlini, P., Massantini, R., & Mencarelli, F. (2000). Vis-NIR measurement of soluble solids in cherry and apricot by PLS regression and wavelength selection. Journal of Agricultural and Food Chemistry, 48(11), 5236-5242.

Castro, P., Padrón, J. C. P., Cansino, M. J. C., Velázquez, E. S., & De Larriva, R. M. (2006). Total volatile base nitrogen and its use to assess freshness in European sea bass stored in ice. Food Control, 17(4), 245-248.

Cen, H., He, Y., & Huang, M. (2006). Measurement of soluble solids contents and pH in orange juice using chemometrics and vis− NIRS. Journal of Agricultural and Food Chemistry, 54(20), 7437-7443.

Coppes-Petricorena, Z. (2010). Texture measurements in fish and fish products. Handbook of seafood quality, safety and health applications, Eds. Alasalvar, C., Miyashita, K., Shahidi, F., &Wanasundara, U., John Wiley and Sons Ltd., Chichester, 130-138.

Cozzolino, D., Chree, A., Scaife, J. R., & Murray, I. (2005). Usefulness of near-infrared reflectance (NIR) spectroscopy and chemometrics to discriminate fishmeal batches made with different fish species. Journal of Agricultural and Food Chemistry, 53(11), 4459-4463.

Dambergs, R. G., Kambouris, A., Francis, I. L., &Gishen, M. (2002). Rapid analysis of methanol in grape-derived distillation products using near-infrared transmission spectroscopy. Journal of Agricultural and Food Chemistry, 50(11), 3079-3084.

Davies, T. (1998). The history of near infrared spectroscopic analysis: Past, present and future” From sleeping technique to the morning star of spectroscopy”. Analusis, 26(4),17.19.http://dx.doi.org/10.1051/analusis:199826040017.

ElMasry, G., & Wold, J. P. (2008). High-speed assessment of fat and water content distribution in fish fillets using online imaging spectroscopy. Journal of Agricultural and Food Chemistry, 56(17), 7672-7677.

Fluckiger, M., Brown, M. R., Ward, L. R., & Moltschaniwskyj, N. A. (2011). Predicting glycogen concentration in the foot muscle of abalone using near infrared reflectance spectroscopy (NIRS). Food Chemistry, 126(4), 1817-1820.

Foley, W. J., McIlwee, A., Lawler, I., Aragones, L., Woolnough, A. P., & Berding, N. (1998). Ecological applications of near infrared reflectance spectroscopy–a tool for rapid, cost-effective prediction of the composition of plant and animal tissues and aspects of animal performance. Oecologia, 116(3), 293-305.

Font, R., Del Río-Celestino, M., Vélez, D., De Haro-Bailón, A., & Montoro, R. (2004). Visible and Near-Infrared Spectroscopy as a Technique for Screening the Inorganic Arsenic Content in the Red Crayfish (Procambarusclarkii Girard). Analytical Chemistry, 76(14), 3893-3898.

García-Rey, R. M., García-Olmo, J., De Pedro, E., Quiles-Zafra, R., & de Castro, M. L. (2005). Prediction of texture and colour of dry-cured ham by visible and near infrared spectroscopy using a fibre optic probe. Meat Science, 70(2), 357-363.

Gayo, J., & Hale, S. A. (2007). Detection and quantification of species authenticity and adulteration in crabmeat using visible and near-infrared spectroscopy. Journal of Agricultural and Food Chemistry, 55(3), 585-592.

González-Sáiz, J. M., Pizarro, C., Esteban-Díez, I., Ramírez, O., González-Navarro, C. J., Sáiz-Abajo, M. J., & Itoiz, R. (2007). Monitoring of alcoholic fermentation of onion juice by NIR spectroscopy: valorization of worthless onions. Journal of Agricultural and Food Chemistry, 55(8), 2930-2936.

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

Horváth, K., Seregely, Z., Andrássy, É., Dalmadi, I., & Farkas, J. (2008). A preliminary study using near infrared spectroscopy to evaluate freshness and detect spoilage in sliced pork meat. Acta Alimentaria, 37(1), 93-102.

Karoui, R., Downey, G., & Blecker, C. (2010). Mid-infrared spectroscopy coupled with chemometrics: a tool for the analysis of intact food systems and the exploration of their molecular structure− quality relationships− a review. Chemical Reviews, 110(10), 6144-6168.

Khodabux, K., L’Omelette, M. S. S., Jhaumeer-Laulloo, S., Ramasami, P., & Rondeau, P. (2007). Chemical and near-infrared determination of moisture, fat and protein in tuna fishes. Food Chemistry, 102(3), 669-675.

Lebot, V., Champagne, A., Malapa, R., & Shiley, D. (2009). NIR determination of major constituents in tropical root and tuber crop flours. Journal of Agricultural and Food Chemistry, 57(22), 10539-10547.

Li, X., Li, J., Zhu, J., Wang, Y., Fu, L., & Xuan, W. (2011). Postmortem changes in yellow grouper (Epinephelusawoara) fillets stored under vacuum packaging at 0^OC. Food Chemistry, 126(3), 896-901.

Lin, M., Mousavi, M., Al‐Holy, M., Cavinato, A. G., & Rasco, B. A. (2006). Rapid near infrared spectroscopic method for the detection of spoilage in rainbow trout (Oncorhynchus mykiss) fillet. Journal of Food Science, 71(1), S18-S23.

Liu, D., Zeng, X. A., & Sun, D. W. (2013). NIR spectroscopy and imaging techniques for evaluation of fish quality—a review. Applied Spectroscopy Reviews, 48(8), 609-628.

Lomiwes, D., Reis, M. M., Wiklund, E., Young, O. A., & North, M. (2010). Near infrared spectroscopy as an on-line method to quantitatively determine glycogen and predict ultimate pH in pre rigor bovine M. longissimus dorsi. Meat science, 86(4), 999-1004.

Lucas, A., Andueza, D., Rock, E., & Martin, B. (2008). Prediction of dry matter, fat, pH, vitamins, minerals, carotenoids, total antioxidant capacity, and colour in fresh and freeze-dried cheeses by visible-near-infrared reflectance spectroscopy. Journal of Agricultural and Food Chemistry, 56(16), 6801-6808.

Madigan, T., Kiermeier, A., Carragher, J., de Barros Lopes, M., & Cozzolino, D. (2013). The use of rapid instrumental methods to assess freshness of half shell Pacific oysters, Crassostrea gigas: A feasibility study. Innovative Food Science & Emerging Technologies, 19, 204-209.

Masoum, S., Alishahi, A. R., Farahmand, H., Shekarchi, M., & Prieto, N. (2012). Determination of protein and moisture in fishmeal by near-infrared reflectance spectroscopy and multivariate regression based on partial least squares. Iranian Journal of Chemistry and Chemical Engineering (IJCCE), 31(3), 51-59.

Mehinagic, E., Royer, G., Bertrand, D., Symoneaux, R., Laurens, F., & Jourjon, F. (2003). Relationship between sensory analysis, penetrometry and visible–NIR spectroscopy of apples belonging to different cultivars. Food Quality and Preference, 14(5-6), 473-484.

Nilsen, H. A., &Heia, K. (2009). VIS/NIR spectroscopy. Fishery Products: Quality, Safety and Authenticity, Eds. Rehbein, H., &Oehlenschl€ager, J., Wiley-Blackwell, Oxford, 89-104.

Nilsen, H., Esaiassen, M., Heia, K., &Sigernes, F. (2002). Visible/near‐infrared spectroscopy: a new tool for the evaluation of fish freshness? Journal of Food Science, 67(5), 1821-1826.

Norris, K. H., & Hart, J. R. (1996). 4. Direct spectrophotometric determination of moisture content of grain and seeds. Journal of Near Infrared Spectroscopy, 4(1), 23-30.

O’Brien, N., Hulse, C. A., Pfeifer, F., &Siesler, H. W. (2013). Near infrared spectroscopic authentication of seafood. Journal of Near Infrared Spectroscopy, 21(4), 299-305. DOI: 10.1255/jnirs.1063.

Oehlenschläger, J. (2005). The intellectronfischtester VI: an almost forgotten but powerful tool for freshness and spoilage determination of fish at the inspection level.Fifth World Fish Inspection and Quality Control Congress, Eds. Ryder, J., &Ababouch, L., FAO, Rome, 116–122.

Oehlenschläger, J. (2014). Seafood quality assessment. Seafood Processing: Technology, Quality and Safety, Eds. Boziaris, I. S., John Wiley & Sons Ltd., Chichester, 361-386.

Olsen, S. H., Sørensen, N. K., Larsen, R., Elvevoll, E. O., & Nilsen, H. (2008). Impact of pre-slaughter stress on residual blood in fillet portions of farmed Atlantic cod (Gadus morhua)—measured chemically and by visible and near-infrared spectroscopy. Aquaculture, 284(1-4), 90-97.

Önal, A., Tekkeli, S. E. K., & Önal, C. (2013). A review of the liquid chromatographic methods for the determination of biogenic amines in foods. Food Chemistry, 138(1), 509-515.

Osborne, B. G. (2006). Near‐infrared spectroscopy in food analysis. Encyclopedia of analytical chemistry: applications, theory and instrumentation, JohnWiley& Sons. DOI: 10.1002/9780470027318.a1018.

Ottavian, M., Facco, P., Fasolato, L., Novelli, E., Mirisola, M., Perini, M., & Barolo, M. (2012). Use of near-infrared spectroscopy for fast fraud detection in seafood: application to the authentication of wild European sea bass (Dicentrarchuslabrax). Journal of Agricultural and Food Chemistry, 60(2), 639-648.

Prieto, N., Dugan, M. E. R., López-Campos, O., McAllister, T. A., Aalhus, J. L., & Uttaro, B. (2012). Near infrared reflectance spectroscopy predicts the content of polyunsaturated fatty acids and biohydrogenation products in the subcutaneous fat of beef cows fed flaxseed. Meat Science, 90(1), 43-51.

Sant’Ana, L. S., Soares, S., & Vaz-Pires, P. (2011). Development of a quality index method (QIM) sensory scheme and study of shelf-life of ice-stored blackspot seabream (Pagellusbogaraveo). LWT-Food Science and Technology, 44(10), 2253-2259.

Shackelford, S. D., Wheeler, T. L., & Koohmaraie, M. (2005). On-line classification of US Select beef carcasses for longissimus tenderness using visible and near-infrared reflectance spectroscopy. Meat Science, 69(3), 409-415.

Shimamoto, J., Hasegawa, K., Hattori, S., Hattori, Y., & Mizuno, T. (2003). Non‐destructive determination of the fat content in glazed bigeye tuna by portable near infrared spectrophotometer. Fisheries Science, 69(6), 1247-1256.

Tito, N. B., Rodemann, T., & Powell, S. M. (2012). Use of near infrared spectroscopy to predict microbial numbers on Atlantic salmon. Food Microbiology, 32(2), 431-436.

Uddin, M., Okazaki, E., Turza, S., Yumiko, Y., Tanaka, M., & Fukuda, Y. (2005). Non‐destructive visible/NIR spectroscopy for differentiation of fresh and frozen‐thawed fish. Journal of Food Science, 70(8), c506-c510.

Walsh, K. B., Guthrie, J. A., & Burney, J. W. (2000). Application of commercially available, low-cost, miniaturised NIR spectrometers to the assessment of the sugar content of intact fruit. Functional Plant Biology, 27(12), 1175-1186.

Weichselbaum, E., Coe, S., Buttriss, J., & Stanner, S. (2013). Fish in the diet: A review. Nutrition Bulletin, 38(2), 128-177.

Williams, P., & Norris, K. (1987). Near-infrared technology in the agricultural and food industries. American Association of Cereal Chemists Inc., St. Paul, Minnesota, USA, 330.

Ying, Y., & Liu, Y. (2008). Non-destructive measurement of internal quality in pear using genetic algorithms and FT-NIR spectroscopy. Journal of Food Engineering, 84(2), 206-213.

Zhang, A., & Cheng, F. (2013). Identification of fresh shrimp and frozen-thawed shrimp by Vis/NIR spectroscopy. International Proceedings of Chemical, Biological and Environmental Engineering (IPCBEE), 53, 60-65. DOI: 10.7763/IPCBEE.

Zhang, S., Zhao, Y., Guo, W., Hao, Q., Zhang, H., Zhao, H., & Yin, L. (2012). Robust model of fresh jujube soluble solids content with near-infrared (NIR) spectroscopy. African Journal of Biotechnology, 11(32), 8133-8140.

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