The demand for fish has increased significantly in recent years due to consumers' desire for healthier food. The market has responded by producing a wide variety of fresh and processed fish products. As a result, the fraudulent substitution of lower-grade fish for higher-grade fish has become an enormous issue in the fishing industry.
(Reference 1).
The substitution of lower-value commercial fish can be voluntary or the result of mistaken substitution, as the species look very similar to each other. Verifying the quality of fish and seafood products and ensuring that the information on the label is accurate (as to quality and origin) is very important.
NIR spectroscopy is the most versatile method for this type of testing because of its sensitivity to organic molecules, ease of use, and cost-effectiveness. Recent technological developments in spectroscopic instrumentation and the availability of miniaturized, handheld spectrometers on the market will help with this identity verification task in the food sector. It should also be noted that there are other competing techniques, such as Nuclear Magnetic Resonance (NMR) (Reference 1), Hyperspectral imaging (Reference 1,2), and fluorescence spectroscopy (Reference 1), that can detect fraud in the fishing industry. Sometimes, these techniques can be used in collaboration with one another. However, the article focuses on the role of near-IR spectroscopy for this task. Analytical approaches such as chemometrics play a vital role in falsification detection because they can identify similarities and differences in spectra that can be used to distinguish fraudulent substitutions in the fish industry.
When it comes to the authenticity issues in the fish industry, four categories can be named (Reference 1), which are:
• Species substitution
• Production method and farming system misrepresentation
• Geographic origin falsification
• Fresh for frozen/thawed product substitution
This article discusses fraudulent activities and their detection using NIR spectroscopy. Monitoring of fish products for these fraudulent activities is impeded by the growing prevalence of highly processed products, for which fraud can be easily concealed. There are also external factors that can be used to identify fish in each category. For example, higher levels of heavy metals or residues of antibiotics and pesticides are more likely to be found in farmed products than in wild products. The article will next examine each fraudulent activity.
Species Substitution
Substituting higher-quality fish for lower-quality or counterfeit fish is a common problem that is growing by the day. A scientific in-situ test that could quickly confirm the contents of the fish as mentioned on the label is highly in demand. Figure 1 shows a depiction of species substitution.
Figure 1: Fraudulent substitution of fish
As an example of the use of NIR for identifying fraudulent fish substitution, one can cite research on discriminating between two species of low-value and high-value mullet, cod, and trout. The research used a Near-IR spectrometer (906-1048 nm) to measure the whole body and fillet of each species, and chemometric analysis, such as PCA and SIMCA, was performed to distinguish between them (Reference 3). Both methods are classified under multivariate analysis. It was found that although PCA could distinguish between low- and high-quality whole mullet, it failed in all other categories. However, SIMCA successfully distinguished between low- and high-quality mullet, cod, and trout in both whole fish and fillet forms. The usefulness of near-IR spectroscopy was also explored in the identification of different species of fish used to make fish meal under industrial conditions (Reference 4). Fishmeal is generally used in products intended for animal feed and not for human consumption. Near-IR measurements in the range 1100-2500 nm were performed for salmon, blue whiting, and mackerel. The second derivatives of the spectra were subjected to PCA and PLS-DA chemometric methods, and the three species were differentiated with classification accuracies greater than 80%.
Production Method and Farming System Substitution
Figure 2 shows a fresh and a farmed salmon, and the difference in appearance between the two
Figure 2: Difference between fresh and farmed salmon
Over the last few years, the production of farmed-raised fish has been steadily increasing compared to wild fish supplies. There are differences in the nutritional values of the two. Wild fish contain higher levels of muscle protein and also higher levels of saturated and polyunsaturated fatty acids. However, farmed fish contain more monounsaturated fatty acids and lipids. The colors are different, too, as depicted in Figure 2. Farmed salmon has a paler pink color compared to reddish wild salmon. As an example of the use of NIR spectroscopy to distinguish between farmed and wild fish, correct classification was performed using near IR measurements and a PLS-DA chemometrics method to differentiate between concrete tank sea cultured seabass and sea-cage cultured seabass with an 87% rate of success (Reference 5).
Geographical Method Falsification
Figure 3 is a depiction of the geographical origin of salmon from different geographical areas.
Figure 3: The Geographical origin of any type of fish, such as salmon, could be different (Reference 6)
Proving the geographical origin of a particular type of fish is quite tricky because modelling the total variability of NIR spectra and attributing it to geographic origin involves a sum of many intrinsic or extrinsic factors, such as genetic, growth patterns, muscular activity, water temperature, etc. (Reference 1). Near-IR spectroscopy has been used less frequently for this distinction and usually multi-disciplinary methods are used for this purpose. These multi-disciplinary methods take into account the environmental factors and genetic information that affect the final characteristics of the fish.
As an example of using NIR spectroscopy to determine geographical origin, one can refer to a study in which Chinese Tilapia fillets from 3 provinces in China (Guangdong, Hainan, and Fujian) were analyzed using NIR spectroscopy (Reference 7). In the study, near-IR spectra of the fish were collected over 1000-2500 nm, and a chemometric method called SIMCA achieved an 80% success rate in distinguishing the different geographical origins. As another example, European seabass from the western, central, and eastern Mediterranean sea provenances were studied using NEAR-IR spectroscopy and a PLS-DA chemometric method, which managed to classify 100% eastern, 88% central, and 85% western provenances correctly (Reference 8). Figure 4 shows a typical pre-processed spectrum from sea bass samples and the grouping based on a score plot after PCA, where CM, EM, and WM refer to the Central, Eastern, and Western Mediterranean, respectively.
Figure 4: Preprocessed spectra of sea bass and score plot grouping based on geographical location (Reference 8)
Discrimination Between Fresh And Frozen/Thawed Seafood
Figure 5 compares fresh and frozen salmon.
Figure 5: Fresh and frozen salmon
Fish is usually frozen to preserve it for longer periods. However, the quality of frozen fish is much lower than fresh fish. That’s why fraudulent practices often try to substitute frozen or thawed fish for fresh fish. When a fish is frozen, some chemical and physical variations are imperceptible by sensory organs, and NIR spectroscopy is one way to detect these tiny changes. As an example of the use of NIR spectroscopy to differentiate between fresh and frozen/thawed fish, one can refer to a study in which swordfish was assessed for freshness or frozen/thawed quality using NIR spectra in the range 1100-2500 nm (Reference 9). After applying the chemometric method PLS-DA, 93% successful classification was achieved.
Hyperspectral Imaging
Hyperspectral imaging uses cameras with a large number of pixels and obtains a spectral image for each pixel in the image of a scene that can also bebe used to detect falsification of fish. In one study involving fresh and frozen/thawed halibut, hyperspectral cameras were used in the range 380-1030 nm and after applying a chemometric method, a classification success rate of nearly 92% was obtained (Reference 10).
Allied Scientific Pro’s NIR Spectrometer
Allied Scientific Pro offers the Nirvascan spectrometer, which uses Texas Instruments Digital Light Processing (DLP) technology. There are two available ranges: 900-1700 nm and 1350-2150 nm. The spectrometer suitable for fish impurity detection is a reflective, portable model. The NIR spectrum can be recorded in a few seconds by the press of a button. The following link has more information about this spectrometer.
https://www.alliedscientificpro.com/nirvascan
References:
1-Approaching authenticity issues in fish and seafood products by qualitative spectroscopy and chemometrics, S. Ghidini et.al, Molecules, 2019, 24, 1812
2-Quality evaluation of fish by hyperspectral imaging, chapter 8 of Hyperspectral imaging for food quality analysis and control, edited by Da-Wen Sun, December 2010.
3-Near Infrared spectroscopic authentication of seafood, N. O’Brien et al, Journal of Near Infrared Spectroscopy, 2013, 21.
4-Usefulness of Near-infrared reflectance (NIR) spectroscopy and chemometrics to discriminate fishmeal batches made with different fish species, D. Cozzolino et.al, Journal of Agric.Food. Chem, 2005, 53.
5-Application of non-invasive techniques to differentiate sea bass quality cultured under different conditions, C. Costa et.al, Aquac. Int. 2011, 19.
6-https://fishingbooker.com/blog/types-of-salmon/
7-Prediction of chemical composition and geographical origin traceability of Chinese export tilapia fillets products by near infrared reflectance spectroscopy, Y. Liu et.al, LWT-food Sci. Technology, 2015, 60.
8-Rapid authentication of European sea bass according to production method, farming system, and geographical origin by near infrared spectroscopy coupled with chemometric, S.Ghidini et.al, Food Chem, 2019, 280.
9-Comparison of visible and near infrared reflectance spectroscopy to authenticate fresh and frozen-thawed sword fish, L. Fasolato et al, J.Aquat. Food. Prod,. Technol. 2012, 21.
10-Application of visible and near infrared hyperspectral imaging to differentiate between fresh and frozen-thawed fish fillets, F. Zhu et al, Food Bioprocess Technol, 2013,6.