Optical coherence tomography (OCT), an advanced, non-destructive imaging technology, is commonly used for assessing food quality and safety. It provides high-resolution cross-sectional images of food products, allowing the detection of internal defects, contamination, and structural changes without damaging the sample. This technique is increasingly applied to evaluate freshness and ensure product integrity.1-4
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Nondestructive Woody Breast (WB) Myopathy
Globally, the prevalence of WB myopathy in chicken breast fillets is rising due to changes in chicken breeding and raising practices aimed at higher meat production. WB fillets have a pale color, hemorrhages in lesion areas, and hard tissue, which negatively affect chicken meat quality, leading to economic losses, reduced nutritional content, and reduced consumer satisfaction.1
Traditionally, methods such as transmission electron microscopy and standard light microscopy are used to evaluate food product safety and quality, including chicken meat, by characterizing its microstructure for WB disorder. Yet, these methods are time-consuming, destructive, expensive, and analyze only small sample areas.1
Additionally, the WB area distribution is heterogeneous in chicken muscle. Varying degrees of WB areas are present along the chicken fillet in severe and moderate cases. Thus, developing large-scale, rapid, and effective noninvasive methods is crucial for WB condition characterization by measuring the entire fillet’s sub-surface cross-sections at a high resolution.1
OCT for WB Myopathy Assessment
A paper published in Food and Bioprocess Technology employed OCT to image the chicken muscle tissue’s sub-surface microstructure with a micrometer resolution along the entire fillet.1
OCT captures depth and spatial information down to a few millimeters beneath the food sample surface with micrometer resolution. Moreover, it provides 29,000 axial A-scans per second, with ultrahigh-speed OCT exceeding 300,000 scans per second, which is a big advantage compared to other imaging methods.1
In the work, the crucial microstructural features identified in the OCT images were subsequently analyzed using machine learning models to classify WB severity in chicken fillets.1
The objective of the study was to predict and evaluate WB severity in fillets using OCT cross-sectional imaging, machine learning techniques, and image processing, and to categorize fillets into two or three classes depending on WB condition.1
Results showed that the combined approach based on OCT imaging, image processing, and machine learning algorithms was highly effective in distinguishing between WB and normal fillets, with a maximum accuracy of 85%, 95%, 93.3%, and 100% for the moderate vs. severe WB, normal vs. moderate WB, normal vs. WB, and normal vs. severe WB cases, respectively.1
Thus, the proposed approach demonstrated the potential of OCT as a non-invasive, rapid subsurface imaging tool for segmenting and quantifying the top layers of the skinless chicken breast throughout the entire fillet. This enables improved product selection and efficient quality control measures through OCT-based poultry inspection and quality assessment.1
Frozen Meat Storage Duration Detection
Most countries in the world have standardized the storage time for their state reserve meat. For instance, the average pork storage time is about 4 months. However, once the frozen meat’s storage duration exceeds the average storage time, potential bio-safety issues can arise that affect food safety.2
Meat’s chemical and physical properties change over time during frozen storage, posing a potential risk to food safety. For instance, the total plate counts of beef and pork refrigerated at 0 °C~4 °C for two weeks increase, and these increases are closely correlated with the D-glucose and volatile base nitrogen content.2
Thus, predicting the duration of frozen meat storage, particularly for long-expired meat that exceeds the state reserve time multiple times, is crucial.2
OCT-based Storage Duration Prediction
Optical imaging approaches have been used to estimate the freshness and quality of frozen meat. OCT with better tomography capabilities than other imaging allows successful high-resolution tomography and real-time detection, making it suitable for frozen meat safety inspection. For instance, OCT has been used to estimate intramuscular fat content.2,3
A paper published in Photonics reported an optical detection method using swept-source OCT (SS-OCT) under a low-frequency electric field to predict the storage duration of frozen meat, which may have exceeded the state reserve time by two or three times.2
The meat sample’s internal electro-kinetic response was visualized, and the parameter average normalized cross-correlation (ANCC) was developed and later confirmed to be sensitive to various frozen storage durations.2
Researchers observed a steadily increasing relationship between the frozen storage duration and ANCC. The ANCC growth rate was analyzed in detail, and the maximum duration of frozen storage was determined. Eventually, researchers established the ANCC inversion law for various storage durations.2
Both samples exceeding (by two and three times) and samples within the state reserve time were investigated. Results showed that the absolute errors were less than 10 days for all samples, and the relative errors were under 5.71%, validating the feasibility of SS-OCT for predicting frozen meat storage durations.2
Fish Freshness and Safety Assessment
A paper published in Optik investigated the evaluation of fish freshness using high-resolution OCT for real-time, non-invasive monitoring. Researchers focused on Indian Anchovies (Stolephorus indicus) and used microstructural changes in the skin and eyes as key indicators of freshness during refrigerated storage.4
OCT observations revealed progressive decreases in internal scattering, boundary weakening, loss of clarity, and overall structural degradation in both tissues. Quantitative image features, including variance intensity, energy, entropy, and edge density, effectively captured internal tissue disruption over storage time owing to oxidative damage, protein denaturation, and fluid imbalance.4
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Results demonstrated that OCT strongly correlates with microbiological and biochemical spoilage processes, enabling early detection of subtle structural deterioration. This approach provides an objective, rapid, and non-invasive method for assessing fish freshness, supporting improved supply chain management and post-harvest seafood quality control.4
Importance of OCT
OCT enables high-resolution, real-time visualization of internal structures in food products such as meat and fish without damaging the sample. It effectively detects microstructural changes, spoilage, and defects in chicken, frozen meat, and fish.
Studies have proven its effectiveness in applications such as WB myopathy detection, frozen meat storage duration prediction, and fish freshness evaluation. Overall, OCT-based assessment improves food quality control, safety monitoring, and the efficiency of supply chain management.
References and Further Reading
- Ekramirad, N., Yoon, S. C., Bowker, B. C., & Zhuang, H. (2024). Nondestructive assessment of woody breast myopathy in chicken fillets using optical coherence tomography imaging with machine learning: A feasibility study. Food and Bioprocess Technology, 17(11), 4053-4070. DOI: 10.1007/s11947-024-03369-1, https://link.springer.com/article/10.1007/s11947-024-03369-1
- Zhang, L. et al. (2023). Storage Duration Prediction for Long-Expired Frozen Meat Exceeding State Reserve Time via Swept-Source Optical Coherence Tomography (SS-OCT) under Low-Frequency Electric Field. Photonics, 10(9), 956. DOI: 10.3390/photonics10090956, https://www.mdpi.com/2304-6732/10/9/956
- Thampi, A., Hitchman, S., Coen, S., & Vanholsbeeck, F. (2021). Towards real time assessment of intramuscular fat content in meat using optical fiber-based optical coherence tomography. Meat Science, 181, 108411. DOI: 10.1016/j.meatsci.2020.108411, https://www.sciencedirect.com/science/article/pii/S0309174020308433
- Madhubhashini, M. N., Kahandawala, B. S., Sandaruwan, H. B., Silva, B. N., Wijenayake, U., & Wijesinghe, R. E. (2026). High-resolution optical imaging for sustainable fish freshness and safety assessment. Optik, 350, 172733. DOI: 10.1016/j.ijleo.2026.172733, https://www.sciencedirect.com/science/article/abs/pii/S0030402626000690
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