Visualize the quality of frozen fish using fluorescence imaging aided with excitation-emission matrix

Potential of fluorescence fingerprints for fish meat authentication: Differences in freshness evaluation in white and dark meat at frozen state

As dark meat has a faster deterioration rate and its unintentional mixing occurs during processing, it is crucial to know the status and freshness indicators of dark meat to ensure fishery product quality. In this method, fluorescence fingerprints (FFs) was applied as a rapid and noninvasive quality authentication method to determine differences between white and dark meat in the evaluation of freshness indicators at frozen state. Spotted mackerel (Scomber australasicus) fish chunks with different postmortem conditions (0-40 h ice stored) were obtained and frozen. A new generation of fluorescence spectrophotometer (F-7100) was used to acquire FFs of the frozen fish chunks (containing white and dark meat). Adenosine triphosphate metabolites and pH were determined in both white and dark meat using their relevant biochemical methods. Higher K-values in dark meat might be attributed to a higher accumulation rate of inosine (HxR) in dark meat than in white meat. The pH decrease rate in white meat was higher than that in dark meat during postmortem ice storage periods of fish. Principal component analysis of FFs spectra demonstrated clear discrimination (PC1 + PC2 = 91.7%) between white and dark meat of frozen fish due to the influence of freshness parameters based on the fluorescence features of fish meat. Furthermore, partial least squares regression validation models revealed that freshness indicators of white meat could be predicted more accurately at the frozen state than those of dark meat. This method could be applied during the processing of fishery products, thereby facilitating quality control activities and making it a promising authentication tool for the fisheries industries.

A comprehensive review of the principles, key factors, application, and assessment of thawing technologies for muscle foods

For years, various thawing technologies based on pressure, ultrasound, electromagnetic energy, and electric field energy have been actively investigated to minimize the amount of drip and reduce the quality deterioration of muscle foods during thawing. However, existing thawing technologies have limitations in practical applications due to their high costs and technical defects. Therefore, key factors of thawing technologies must be comprehensively analyzed, and their effects must be systematically evaluated by the quality indexes of muscle foods. In this review, the principles and key factors of thawing techniques are discussed, with an emphasis on combinations of thawing technologies. Furthermore, the application effects of thawing technologies in muscle foods are systematically evaluated from the viewpoints of eating quality and microbial and chemical stability. Finally, the disadvantages of the existing thawing technologies and the development prospects of tempering technologies are highlighted. This review can be highly instrumental in achieving more ideal thawing goals.

Hybrid Vibration and UV Fluorescence Technology for Rapid Imaging and Guidance for Manual Removal of Fish Bones from Fish Floss

The objective of the proposed human-machine cooperation (HMC) workstation is to both rapidly detect calcium-based fish bones in masses of minced fish floss and visually guide operators in approaching and removing the detected fish bones by hand based on the detection of fingernails or plastic-based gloves. Because vibration is a separation mechanism that can prevent absorption or scattering in thick fish floss for UV fluorescence detection, the design of the HMC workstation included a vibration unit together with an optical box and display screens. The system was tested with commonly used fish (swordfish, salmon, tuna, and cod) representing various cooking conditions (raw meat, steam-cooked meat, and fish floss), their bones, and contaminating materials such as derived from gloves made of various types of plastic (polyvinylchloride, emulsion, and rubber) commonly used in the removal of fish bones. These aspects were each investigated using the spectrum analyzer and the optical box to obtain and analyze the fluorescence spectra and images. The filter was mounted on a charge-coupled device, and its transmission-wavelength window was based on the characteristic band for fish bones observed in the spectra. Gray-level AI algorithm was utilized to generate white marker rectangles. The vibration unit supports two mechanisms of air and downstream separation to improve the imaging screening of fish bones inside the considerable flow of fish floss. Notably, under 310 nm ultraviolet B (UVB) excitation, the fluorescence peaks of the raw fillets, steam-cooked meat, and fish floss were observed at for bands at longer wavelengths (500-600 nm), whereas those of the calcium and plastic materials occurred in shorter wavelength bands (400-500 nm). Perfect accuracy of 100% was achieved with the detection of 20 fish bones in 2 kg of fish floss, and the long test time of around 10-12 min results from the manual removal of these fish bones.

Rapid noninvasive monitoring of freshness variation in frozen shrimp using multidimensional fluorescence imaging coupled with chemometrics

Shrimp is one of the most delicious and popular food commodities worldwide due to its exceptional taste and characteristics. Freshness is considered as a key factor for shrimp consumers because freshness has a significant relationship with taste and shelf-life of shrimp. However, post-mortem metabolism of shrimp differs from that of fish as they are highly susceptible to post-harvest quality loss, and it is hard to distinguish the freshness variation of shrimp at frozen state instantly. Thus, instant monitoring of frozen shrimp freshness is challenging for the seafood and aquaculture industries and a reliable, expeditious, and noninvasive technique to estimate shrimp quality is in high demand. Accordingly, this study aimed to visualize changes in post-mortem freshness of frozen shrimp using multidimensional fluorescence imaging. Live coonstripe shrimp (Pandalus hypsinotus) were harvested and instantly killed by beheading, cooled on ice for 0, 6, 24, 48, 72 and 96 h (n = 8), followed by processing into frozen peeled deveined shrimp product and stored at -60 °C. 50% of frozen shrimp were analyzed for excitation-emission matrix (EEM), ATP-related compounds, and pH using a fiber optic supported fluorescence spectrophotometer (F-7100), high performance liquid chromatography (HPLC) and pH meter, respectively at each time point (n = 4). Then, fluorescence images were obtained from the remaining 50% of frozen shrimp (n = 4) by computer vision method equipped with a charge-coupled device (CCD) camera, MAX-303 xenon light source for an excitation light (Ex. 330 nm), and an automatic filter changer for emission band-pass filters (Em. 380-610 nm at 10 nm intervals). Chemical analysis of frozen shrimp revealed that K-value and pH of shrimp increased from 1.61 to 66.56% and 6.49-7.31, respectively, during storage on ice. Repeated partial least squares regression (PLSR) models of EEM for K-value prediction suggested an efficient excitation wavelength (330 nm) and its corresponding emission wavelengths (380-610 nm) to produce fluorescence images. Spatial-temporal changes of K-value and pH were visualized successfully in frozen shrimp by fluorescence imaging. K-value visualization was then validated effectively using another group of frozen shrimp (0-72 h ice stored) with different killing method (super chilling) and the prediction accuracy was R² = 0.80. This novel approach using a CCD camera coupled with EEM provides a state-of-the-art authentication method for practical assessment of frozen seafood freshness.

Spectroscopic Techniques for Monitoring Thermal Treatments in Fish and Other Seafood: A Review of Recent Developments and Applications

Cooking is an important processing method, that has been used since ancient times in order to both ensure microbiological safety and give desired organoleptic properties to the cooked food. Fish and other seafood products are highly sensitive to thermal treatments and the application of severe heat can result in negative consequences on sensory and nutritional parameters, as well as other quality attributes of the thermally processed products. To avoid such undesired effects and to extend the shelf life of these perishable products, both the heat processing methods and the assessment techniques used to monitor the process should be optimized. In this review paper, the most common cooking methods and some innovative ones will first be presented with a brief discussion of their impact on seafood quality. The main methods used for monitoring heat treatments will then be reviewed with a special focus on spectroscopic techniques, which are known to be rapid and non-destructive methods compared to traditional approaches. Finally, viewpoints of the current challenges will be discussed and possible directions for future applications and research will be suggested. The literature presented in this review clearly demonstrates the potential of spectroscopic techniques, coupled with chemometric tools, for online monitoring of heat-induced changes resulting from the application of thermal treatments of seafood. The use of fluorescence hyperspectral imaging is especially promising, as the technique combines the merits of both fluorescence spectroscopy (high sensitivity and selectivity) and hyperspectral imaging (spatial dimension). With further research and investigation, the few current limitations of monitoring thermal treatments by spectroscopy can be addressed, thus enabling the use of spectroscopic techniques as a routine tool in the seafood industry.

Use of Spectroscopic Techniques for a Rapid and Non-Destructive Monitoring of Thermal Treatments and Storage Time of Sous-Vide Cooked Cod Fillets

In this work, the potential of spectroscopic techniques was studied to investigate heat-induced changes occurring during the application of thermal treatments on cod (Gadus morhua L.) fillets. Vacuum-packed samples were thermally treated in a water bath at 50, 60, 70 and 80 °C for 5 and 10 min, and further stored for one, four, and eight days at 4 ± 1 °C before analysis. Several traditional (including cooking loss, drip loss, texture, protein solubility, protein oxidation, and color) and spectroscopic (fluorescence and diffuse reflectance hyperspectral imaging) measurements were conducted on the same samples. The results showed a decrease in fluorescence intensity with increasing cooking temperature and storage time, while the impact of cooking time was only noticeable at low temperatures. Diffuse reflectance data exhibited a decrease in absorbance, possibly as a result of protein denaturation and increased scattering at higher cooking temperatures. Both fluorescence and diffuse reflectance data were highly correlated with color parameters, whereas moderate correlations were observed with most other traditional parameters. Support vector machine models performed better than partial least square ones for both classification of cod samples cooked at different temperatures and in prediction of the cooking temperature. The best classification result was obtained on fluorescence data, achieving an accuracy of 92.5%, while the prediction models resulted in a root mean square error of prediction of cooking temperature lower than 5 °C. Overall, the classification and prediction models showed good results, indicating that spectroscopic techniques, especially fluorescence hyperspectral imaging, have a high potential for monitoring thermal treatments in cod fillets.

Performance of Fluorescence and Diffuse Reflectance Hyperspectral Imaging for Characterization of Lutefisk: A Traditional Norwegian Fish Dish

Lutefisk is a traditional Norwegian fish dish made from dried fish, such as cod or other whitefish. In Norway and other Nordic countries, lutefisk is considered among the most popular dishes served during Christmas or other festive occasions. However, to date, little attention has been paid to this product, and available research on the quality, processing, and chemistry of lutefisk is still limited. The quality of this very delicate product, with a high pH value, depends on many factors, such as the initial quality of raw materials (stockfish), the quantity of lye used during the preparation process of lutefisk, and time during soaking in the lye and water, among others, making it challenging to both optimize processing and monitor the quality of lutefisk. In this study, four commercially available lutefisk brands (labelled as A, B, C, and D) were characterized using two online spectroscopic techniques, namely fluorescence and diffuse reflectance hyperspectral imaging, implemented on conveyor belts to mimic industrial applications. The samples were also analyzed by the use of an offline laboratory instrument based on visible/near infrared diffuse reflectance spectroscopy. Three traditional measurements, including texture, water content, and pH, were also conducted on the same samples. Supervised classification PLS-DA models were built with each dataset and relationships between the spectroscopic measurements and the traditional data were investigated using canonical correlations. The spectroscopic methods, especially fluorescence spectroscopy, demonstrated high performance for the discrimination between samples of the different brands, with high correlations between the spectral and traditional measurements. Although more validations of the results of this study are still required, these preliminary findings suggest that the destructive, laborious, and time-consuming traditional techniques can be replaced by rapid and nondestructive online measurements based on hyperspectral imaging used in fluorescence or diffuse reflectance mode.

Classification of water contamination developed by 2-D Gabor wavelet analysis and support vector machine based on fluorescence spectroscopy

The identification of the specific categories of pollutants in the urban water supply system is necessary. Traditional detection methods are based mainly on common water quality indicators. However, inspecting these water quality indicators is made difficult by issues such as long analysis time, insufficient sensitivity, need for reagents, and generation of waste liquid. These problems hinder high-frequency water detection and monitoring. In this study, three-dimensional (3D) fluorescence spectroscopy is adopted as a monitoring method for water quality. An identification method based on two-dimensional (2D) Gabor wavelets and support vector machine (SVM) multi-classification is also proposed. The Delaunay triangulation method for interpolation is used to pre-process 3D fluorescence spectra and thereby eliminate Rayleigh scattering and Raman scattering. A 2D Gabor wavelet function generated by filters of different scales and rotation angles is proposed to extract the features of the spectra. The block statistics method, based on Gabor feature description, is employed to enhance the efficiency in describing spectra features. Then, multiple SVM classifiers are used in pollutant classification and recognition. By comparing the proposed method with principal component analysis, which is a commonly used feature extraction method, this study finds that the application of 2D Gabor wavelets and block statistics can effectively describe the characteristics of 3D fluorescence spectra. Moreover, 2D Gabor wavelets achieve high classification accuracy, especially for substances with closely positioned or overlapping characteristic peaks.