How Ocean University of China Uses Light to Safeguard Our Seafood
At Ocean University of China, researchers are using near-infrared spectroscopy to reveal secrets hidden within marine products—revolutionizing how we understand and protect ocean resources.
Have you ever wondered how scientists can tell if the fish at your supermarket is fresh without even touching it? Or how they can determine the nutritional value of oysters without complicated chemical tests? At Ocean University of China (OUC), researchers are doing exactly this—and more—with a remarkable technology that uses invisible light to reveal secrets hidden within marine products. This technology, called near-infrared spectroscopy (NIRS), is revolutionizing how we understand and protect ocean resources.
Imagine pointing a specialized flashlight at a piece of fish and within seconds knowing exactly how fresh it is, what it contains, and even where it came from. This isn't science fiction—it's the cutting-edge work being done by OUC's Near Infrared Spectroscopy Information and Technology Group. Their research doesn't just ensure the safety and quality of the seafood we eat; it also helps protect marine ecosystems and supports sustainable aquaculture practices.
Using invisible light to decode the molecular fingerprints of marine products
Near-infrared spectroscopy might sound complex, but the basic concept is surprisingly straightforward. Think about what happens when you shine a light through a glass of red wine—the light that passes through takes on a reddish color because certain colors are absorbed while others pass through. NIRS works on a similar principle, but instead of visible light, it uses near-infrared light—invisible to our eyes but packed with information about what it passes through.
When near-infrared light is directed at a sample—whether it's a piece of fish, an oyster, or a krill—the light interacts with chemical bonds in the material, particularly those involving hydrogen (like C-H, O-H, and N-H bonds). Different bonds absorb different wavelengths of near-infrared light, creating a unique "molecular fingerprint" that reveals the sample's composition .
The raw data from NIRS looks like a complex graph with many peaks and valleys. To make sense of this information, OUC researchers use sophisticated data analysis techniques called chemometrics. By applying mathematical models and machine learning algorithms, they can extract meaningful patterns from what appears to be a chaotic jumble of lines .
Marine products are collected and prepared for analysis without any destructive processing.
Near-infrared light is directed at the sample, and the absorption spectrum is recorded.
Chemometric algorithms process the spectral data to extract meaningful patterns.
Machine learning models predict freshness, composition, and other quality parameters.
How OUC researchers combined multiple spectroscopic techniques to evaluate shrimp quality
Shrimp is one of the world's most popular seafoods, but its quality declines rapidly after harvesting. Traditional methods for assessing shrimp freshness are slow, require destructive sampling, and can't be used for continuous monitoring. Researchers at OUC tackled this challenge by developing an innovative approach that combines multiple spectroscopic techniques to evaluate shrimp freshness rapidly and non-destructively 2 .
The key indicator they focused on was Total Volatile Basic Nitrogen (TVB-N)—compounds like ammonia and trimethylamine that accumulate as seafood spoils. While TVB-N is a well-established freshness marker, conventional detection methods are cumbersome, time-intensive, and destructive to the sample 2 .
The research team designed a comprehensive experiment using Pacific white shrimp (Litopenaeus vannamei), one of the most commercially important shrimp species worldwide.
| Method | R²p (Prediction Accuracy) | RMSEP (Error Value) | Performance |
|---|---|---|---|
| NIR alone | 0.864 | Not specified |
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| Raman alone | 0.784 | Not specified |
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| Mid-level data fusion with ELM | 0.986 | 0.677 mg/100 g |
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The fused model not only achieved remarkable accuracy but also demonstrated the complementary nature of the two spectroscopic techniques 2 .
This research demonstrates that portable spectroscopic instruments could be used for non-destructive, real-time freshness monitoring in actual production and retail environments—a significant advancement over traditional laboratory methods.
Instruments, computational methods, and analytical techniques powering OUC's NIRS research
| Item | Function | Application Example |
|---|---|---|
| Fourier Transform NIR Spectrometer | Measures absorption of near-infrared light by samples | Analyzing nutrient composition in Pacific oysters 8 |
| Raman Spectrometer | Provides detailed molecular fingerprint information | Assessing texture changes in large yellow croaker 3 |
| Portable NIR Devices | Enables field analysis with compact, battery-operated units | Discriminating fresh from frozen-thawed mackerel 3 |
| Chemometric Software (PLS, SVM, CNN) | Mathematical methods to extract information from spectral data | TVB-N prediction in shrimp using machine learning 2 |
| Reference Chemical Analysis Kits | Provide benchmark measurements for model calibration | Measuring TVB-N, glycogen, protein content 4 8 |
Combining NIR and Raman for comprehensive analysis
Applying AI algorithms for pattern recognition
Enabling real-time analysis in field conditions
Expanding NIRS technology to diverse marine science challenges
For sea bass, a high-value fish species, OUC researchers have identified three critical quality indicators: protein content, skin color measurement (b* value), and condition factor. Using NIRS combined with chemometrics, they've developed models to rapidly classify sea bass according to geographical origin and predict key quality attributes 5 .
In the case of Antarctic krill, a promising sustainable protein source, OUC scientists have created innovative methods to predict frozen storage time using NIRS combined with the Light Gradient Boosting Machine (LightGBM) algorithm. Their model achieved astonishing accuracy (R² = 0.9882) in determining how long krill had been stored 4 .
OUC's spectroscopic expertise extends beyond food quality to environmental protection. A research team led by Qingsheng Xue developed a novel system combining fluorescence labeling with confocal Raman spectroscopy to enhance microplastic analysis in seawater. This method enables precise identification of microplastics as small as 60 μm—helping scientists better understand and address the growing problem of plastic pollution in our oceans 6 .
The expanding potential of NIRS technology in marine research and conservation
The work being done by the Near Infrared Spectroscopy Information and Technology Group at Ocean University of China represents a perfect marriage of advanced physics, computational power, and marine science. By harnessing the power of invisible light, these researchers are solving practical problems in our seafood supply chain while also contributing to broader environmental monitoring efforts.
This research exemplifies how cutting-edge technology can help us build a more sustainable, transparent, and efficient relationship with our ocean resources—ensuring that we can enjoy the benefits of seafood while protecting marine ecosystems for generations to come.
The next time you enjoy a delicious shrimp dinner or purchase fresh fish from the market, remember that there's an excellent chance that invisible light has helped ensure its quality and safety—thanks to the pioneering work of scientists at Ocean University of China.