Developing a multispectral imaging for simultaneous prediction of freshness indicators during chemical spoilage of grass carp fish fillet

Simultaneous determination of pigments of spinach (Spinacia oleracea L.) leaf for quality inspection using hyperspectral imaging and multi-task deep learning regression approaches

Rapid and accurate determination of pigment content is important for quality inspection of spinach leaves during storage. This study aimed to use hyperspectral imaging at two spectral ranges (visible/near-infrared, VNIR: 400-1000 nm; NIR: 900-1700 nm) to simultaneously determine the pigment (chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids) content in spinach stored at different durations and conditions (unpackaged and packaged). Partial least squares (PLS), back propagation neural network (BPNN) and convolutional neural network (CNN) were used to establish single-task and multi-task regression models. Single-task CNN (STCNN) models and multi-task CNN (MTCNN) models obtained better performances than the other models. The models using VNIR spectra were superior to those using NIR spectra. The overall results indicated that hyperspectral imaging with multi-task learning could predict the quality attributes of spinach simultaneously for spinach quality inspection under various storage conditions. This research will guide food quality inspection by simultaneously inspecting multiple quality attributes.

A solution for fillet quality: Slaughter age's effect on protein mechanism and oxidation

Physico-chemical properties of fish flesh are reliable predictors of fillet quality and nutritional value. In our study, the age-related variations of the chemical composition, pH, water activity (aw), water holding capacity (WHC), color and texture analysis, protein thermal stability, myofibrillar fragmentation index (MFI), glycogen content, protein oxidation and protein profiles were investigated in Oncorhynchus mykiss (rainbow trout) fillet. The results revealed that protein denaturation temperatures (Tmax1 and Tmax2) decreased by 2 % and 11.6 % depending on fish age. Tmax1 and Tmax2 values in the same groups were raised 71 % at 11 months' fish and this increase was 58 % at 23 months' fish. An age-related reduction by 66.6 % and 31.25 % was noticed for protein oxidation markers sulfhydryl groups and disulfide bonds. MFI value increased by 86.6 % connected with age. The characteristics of fish meat quality are complex and are influenced by various factors that affect the degree of freshness of the product and its acceptance in the market. Taking into account the different demands of the consumer, this study has shown that age at slaughter has an impact on final product quality and that the recommended age at slaughter, taking into account market weight, positively affects meat quality.

Quality Evaluation of Mackerel Fillets Stored under Different Conditions by Hyperspectral Imaging Analysis

This study was designed to compare the quality changes in mackerel fillets stored under different conditions by using hyperspectral imaging (HSI) techniques. Fillets packaged in vacuum were stored for six days under five different conditions: refrigerated at 4°C (R group); iced at 5±3°C (I group); kept at an ambient of 17±2°C (A group); frozen at -18°C for 24 h and thawed in a refrigerator at 4°C for 5 h on the sampling day (FTR group); FTR thawed in tap water instead of thawing in a refrigerator (FTW group). The FTR group had the lowest total bacterial count, drip loss, 2-thiobarbituric acid reactive substances, volatile basic nitrogen, and texture profile analysis values among groups during the entire storage period (p<0.05). Scanning electron microscopy revealed that the FTR group had less damage, while the other groups had shrunken muscle tissues. HSI integrated with the partial least squares model yielded reliable and efficient results, with high R2cv values, for several quality parameters of the mackerel fillets. Overall, the FTR group, involving freezing and thawing in a refrigerator, appears to be the most favorable option for maintaining the quality of mackerel fillets, which could be practically implemented in the industry. HSI is a suitable and effective technique for determining the quality of mackerel fillets stored under different conditions.

Recent Advance of Intelligent Packaging Aided by Artificial Intelligence for Monitoring Food Freshness

Food safety is a pressing concern for human society, as it directly impacts people's lives, while food freshness serves as one of the most crucial indicators in ensuring food safety. There exist diverse techniques for monitoring food freshness, among which intelligent packaging based on artificial intelligence technology boasts the advantages of low cost, high efficiency, fast speed and wide applicability; however, it is currently underutilized. By analyzing the current research status of intelligent packaging both domestically and internationally, this paper provides a clear classification of intelligent packaging technology. Additionally, it outlines the advantages and disadvantages of using intelligent packaging technology for food freshness detection methods, while summarizing the latest research progress in applying artificial intelligence-based technologies to food freshness detection through intelligent packaging. Finally, the author points out the limitations of the current research, and anticipates future developments in artificial intelligence technology for assisting freshness detection in intelligent packaging. This will provide valuable insights for the future development of intelligent packaging in the field of food freshness detection.

Dynamic changes in postmortem quality of mirror carp (Cyprinus carpio L.): Based on oxidation reaction and mitochondrial function properties

The dynamic changes in the postmortem quality of mirror carp (Cyprinus carpio L.) were investigated. With extended postmortem time, conductivity, redness, lipid oxidation, and protein oxidation all increased, while lightness, whiteness, and freshness decreased. At 4 h postmortem, the pH value reached a minimum (6.58), while the centrifugal loss and hardness reached a maximum (17.13% and 2539 g). Additionally, variations in mitochondria-related parameters during apoptosis were studied. Within 72 h postmortem, the content of reactive oxygen species initially decreased and subsequently increased; furthermore, there was a significant increase in the mitochondrial membrane permeability transition pore, membrane fluidity, and swelling (P < 0.05). Meanwhile, the cytosolic cytochrome c level decreased from 0.71 to 0.23, which indicated potential mitochondrial damage. Thus, mitochondrial dysfunction during postmortem aging can give rise to oxidation and the production of ammonia and amine compounds, which leads to flesh quality deterioration.

Inactivation of Listeria monocytogenes through the synergistic interaction between plasma-activated water and organic acid

This study observed that when plasma-activated water (PAW) was combined with organic acid, it showed a synergistic inactivation effect on Listeria monocytogenes, which is highly resistant to PAW. When comparing various organic acids, lactic acid (LA) showed the greatest synergistic effect, followed by malic acid (MA), citric acid (CA), and acetic acid (AA), whereas propionic acid (PA) did not show a synergistic effect. Organic acid lowered the activity of ROS defense enzymes (catalase, superoxide dismutase) by reducing intracellular pH (pH_i), which induced the increase in the accumulation of ROS of PAW within the cell. In the end, the synergistic inactivation effect appeared as the increased occurrence of oxidative damage when organic acid was combined as a series of preceding causes. In this case, LA with the greatest ability to lower the pH induced the greatest synergistic effect, suggesting that LA is the best candidate to be combined with PAW. As a result of observing changes in inactivation activity for L. monocytogenes of PAW combined with 1.0% LA while storing at - 80, -20, 4, 25, & 37 °C for 30 days, respectively, it was confirmed that the lower the temperature, the lower the activity loss during the storage period, and that it had an activity of 3.72 log reduction based on 10 min treatment when stored at - 80 °C for 30 days. Application of PAW combined with 1.0% LA stored at - 80 °C for 30 days to mackerel inoculated with L. monocytogenes in ice form resulted in a decrease of 4.53 log after 120 min treatment, without changing the quality of mackerel. These results suggest that combining LA with PAW can be an effective control strategy for L. monocytogenes with high resistance to PAW, and can be effectively utilized, even in ice form.

Influence of repeated freeze-thaw treatments on the oxidation and degradation of muscle proteins from mirror carp (Cyprinus carpio L.), based on myofibrillar protein structural changes

The effects of repeated freeze-thaw (F-T) treatments on the oxidation and degradation of muscle proteins from mirror carp (Cyprinus carpio L.) were investigated. The myofibrillar fragmentation index, trichloroacetic acid-soluble peptides, total volatile basic nitrogen, amino nitrogen, and carbonyl content of the samples significantly increased (P < 0.05). However, the samples showed a significant reduction in the fragmentation index, myofibrillar protein (MP) solubility, and total sulfhydryl content after five F-T cycles (P < 0.05). Moreover, the sodium dodecyl sulfate-polyacrylamide gel electrophoresis bands of the MP faded because of the oxidation and degradation of the protein with increasing F-T cycles. By the fifth F-T cycle, the α-helix and β-turn content significantly decreased by 10.41 % and 5.72 %, respectively (P < 0.05), whereas the β-sheet and random coil content significantly rose by 7.66 % and 8.47 %, respectively (P < 0.05). Furthermore, the intrinsic fluorescence of the MP showed a substantial decrease in intensity and a redshift. In summary, iterative F-T cycles destroyed the MP structure and caused the oxidation and degradation of muscle proteins from mirror carp.

Ca2+ATPase enzyme activities and lipid and protein oxidations of grass carp (Ctenopharyngodon idellus) stored at 4 °C for 30 min under electromagnetic fields

This work studied the effects of electromagnetic fields (EMF) with frequencies between 100 and 400 Hz and a fixed strength of 12 mT on cold storage of grass carp at 4 °C for 30 min, and Ca²⁺ATPase enzyme activities, and lipid and protein oxidations in samples were measured to assess changes in intracellular Ca²⁺ concentration and oxidative stability. Results showed higher Ca²⁺ATPase activities in samples treated with EMF frequencies. Significant (p < 0.05) decreases occurred in protein oxidation for samples treated between 100 and 300 Hz, but an increase was observed for treatment with 400 Hz. However, the lipid oxidation increased for samples treated up to 200 Hz and decreased with further increase in frequency to 300 and 400 Hz. Nuclear magnetic resonance analysis showed that exposure to different frequencies of EMF could reduce the association of water molecules with protein for both bound and immobilized water. Overall, treatments of EMF between 100 and 400 Hz could improve grass carp quality during cold storage.

Japanese dace (Tribolodon hakonensis) fish freshness estimation using front-face fluorescence spectroscopy coupled with chemometric analysis

Although fish and its related products are good sources of protein and unsaturated fatty acids, like omega-3 in the human diet, their shelf-life is limited by biochemical and microbial changes. In this study, a front-face fluorescence spectroscopy technique was used to acquire Excitation-emission matrices (EEM) to monitor Japanese dace (Tribolodon hakonensis) fish freshness degradation during storage. EEM of Japanese dace fish parts (intact eyeball and surface-containing scales), excitation from 220 to 585 nm and emissions from 250 to 600 nm, were measured at different times during storage. To simplify the acquired complex spectra datasets from each fish part, the variables were reduced to those that were only significant/important (those with higher positive or negative correlation) for K value prediction, and as an index of freshness. Partial least square regression (PLSR) results demonstrated that combining the fluorescence EEM of the eyeball and surface-containing scales the best monitoring of fish freshness; excitation at 280 and 350 nm for both the eyeball and surface-containing scales, with 2.84 and 0.96 as RMSE and R², respectively. These findings demonstrate that multiple excitation fluorescence approaches can be convenient for the freshness evaluation of fish.

Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review

Fluorescence spectroscopy, color imaging and multispectral imaging (MSI) have emerged as effective analytical methods for the non-destructive detection of quality attributes of various white meat products such as fish, shrimp, chicken, duck and goose. Based on machine learning and convolutional neural network, these techniques can not only be used to determine the freshness and category of white meat through imaging and analysis, but can also be used to detect various harmful substances in meat products to prevent stale and spoiled meat from entering the market and causing harm to consumer health and even the ecosystem. The development of quality inspection systems based on such techniques to measure and classify white meat quality parameters will help improve the productivity and economic efficiency of the meat industry, as well as the health of consumers. Herein, a comprehensive review and discussion of the literature on fluorescence spectroscopy, color imaging and MSI is presented. The principles of these three techniques, the quality analysis models selected and the research results of non-destructive determinations of white meat quality over the last decade or so are analyzed and summarized. The review is conducted in this highly practical research field in order to provide information for future research directions. The conclusions detail how these efficient and convenient imaging and analytical techniques can be used for non-destructive quality evaluation of white meat in the laboratory and in industry.

Beef Cut Classification Using Multispectral Imaging and Machine Learning Method

Classification of beef cuts is important for the food industry and authentication purposes. Traditional analytical methods are time constraints and incompatible with the modern food industry. Taking advantage of its rapidness and being nondestructive, multispectral imaging (MSI) has been widely applied to obtain a precise characterization of food and agriculture products. This study aims at developing a beef cut classification model using MSI and machine learning classifiers. Beef samples are imaged with a snapshot multi-spectroscopic camera within a range of 500-800 nm. In order to find a more accurate classification model, single- and multiple-modality feature sets are used to develop an accurate classification model with different machine learning-based classifiers, namely, linear discriminant analysis (LDA), support vector machine (SVM), and random forest (RF) algorithms. The results demonstrate that the optimized LDA classifier achieved a prediction accuracy of over 90% with multiple modality feature fusion. By combining machine learning and feature fusion, the other classification models also achieved a satisfying accuracy. Furthermore, this study demonstrates the potential of machine learning and feature fusion method for meat classification by using multiple spectral imaging in future agricultural applications.

Novel technique for treating grass carp (Ctenopharyngodon idella) by combining plasma functionalized liquids and Ultrasound: Effects on bacterial inactivation and quality attributes

A novel technique for treating grass carp by combining plasma functionalized liquids and ultrasound to inactivate bacteria was developed. The effects of the plasma functionalized liquids (PFL) including plasma functionalized water (PFW) and buffer (PFB) and their respective combination with ultrasound treatment (USPFW and USPFB) on the oxidative and physical qualities of grass carp were also investigated. Individual applications of PFW and PFB significantly reduced the populations of Escherichia coli and Shewanella putrefaciens in the range of 0.31-1.18 log CFU/g, compared with the control with a reduction of 0.18 log CFU/g, while combined treatments of USPFW and USPFB presented additional reductions of 0.05-0.65 log CFU/g, with potential synergy demonstrated for PFW and ultrasound. The treatment resulted in improved biomedical index and nutritional value of fatty acids and lipids, protein structural unfolding, increased lipid oxidation and protein degradation with values within the acceptable limits, and the combined treatment was more effective for retarding the hardness reduction in grass carp, while the colour change was also significantly affected, resulting in increased whiteness. The results indicated that the combined treatments may be a promising approach to improving the quality of seafood products.

Optimisation of treatment conditions for reducing Shewanella putrefaciens and Salmonella Typhimurium on grass carp treated by thermoultrasound-assisted plasma functionalized buffer

A novel method of thermoultrasound-assisted plasma functionalized buffer (PFB) for decontaminating grass carp was evaluated using the Box-Behnken design (BBD) with processing variables including PFB generating voltage (PV), ultrasound treatment time (UT) and temperature (TP). The predicted models were found to be significant (p < 0.05) and displayed sufficient fitness with experimental data as indicated by non-significant (p > 0.05) lack of fit and high coefficient of determination (R2≥0.97) values. The optimum decontamination conditions for the responses of S. putrefaciens and S. Typhimurium were PV of 66 V, UT of 14.90 min and TP of 60 ℃, achieving reductions of 4.40 and 3.97 log CFU/g, respectively, with a desirability of 0.998. Among the variables, temperature presented higher significance for inactivating bacteria and the production of volatile basic nitrogen and lipid peroxidation under the optimized conditions were within the limits of freshness for grass carp. Additionally, the effects of PFB and the optimized thermoultrasound-assisted PFB decontamination were mild on the microstructure of grass carp with slight ruptures and loose myofibril structures, indicating the potential of thermoultrasound-assisted PFB for seafood products decontamination with reduced processing time.

Evaluation of the total volatile basic nitrogen (TVB-N) content in fish fillets using hyperspectral imaging coupled with deep learning neural network and meta-analysis

Recently, hyperspectral-imaging (HSI), as a rapid and non-destructive technique, has generated much interest due to its unique potential to monitor food quality and safety. The specific aim of the study is to investigate the potential of the HSI (430-1010 nm) coupled with Linear Deep Neural Network (LDNN) to predict the TVB-N content of rainbow trout fillet during 12 days storage at 4 ± 2 °C. After the acquisition of hyperspectral images, the TVB-N content of fish fillets was obtained by a conventional method (micro-Kjeldahl distillation). To simplify the calibration models, nine optimal wavelengths were selected by the successive projections algorithm. A seven layers LDNN was designed to estimate the TVB-N content of samples. The LDNN model showed acceptable performance for prediction of TVB-N content of fish fillet (R²p = 0.853; RSMEP = 3.159 and RDP = 3.001). The performance of LDNN model was comparable with the results of previous works. Although, the results of the meta-analysis did not show any significant difference between various chemometric models. However, the least-squares support vector machine algorithm showed better prediction results as compared to the other models (RMSEP: 2.63 and R²_p = 0.897). Further studies are required to improve the prediction power of the deep learning model for prediction of rainbow-trout fish quality.

Sensing Technology for Fish Freshness and Safety: A Review

Standard analytical methods for fish freshness assessment are based on the measurement of chemical and physical attributes related to fish appearance, color, meat elasticity or texture, odor, and taste. These methods have plenty of disadvantages, such as being destructive, expensive, and time consuming. All these techniques require highly skilled operators. In the last decade, rapid advances in the development of novel techniques for evaluating food quality attributes have led to the development of non-invasive and non-destructive instrumental techniques, such as biosensors, e-sensors, and spectroscopic methods. The available scientific reports demonstrate that all these new techniques provide a great deal of information with only one test, making them suitable for on-line and/or at-line process control. Moreover, these techniques often require little or no sample preparation and allow sample destruction to be avoided.

Quest of Intelligent Research Tools for Rapid Evaluation of Fish Quality: FTIR Spectroscopy and Multispectral Imaging Versus Microbiological Analysis

The aim of the present study was to assess the microbiological quality of farmed sea bass (Dicentrarchus labrax) fillets stored under aerobic conditions and modified atmosphere packaging (MAP) (31% CO₂, 23% O₂, 46% Ν₂,) at 0, 4, 8, and 12 °C using Fourier transform infrared (FTIR) spectroscopy and multispectral imaging (MSI) in tandem with data analytics, taking into account the results of conventional microbiological analysis. Fish samples were subjected to microbiological analysis (total viable counts (TVC), Pseudomonas spp., H₂S producing bacteria, Brochothrix thermosphacta, lactic acid bacteria (LAB), Enterobacteriaceae, and yeasts) and sensory evaluation, together with FTIR and MSI spectral data acquisition. Pseudomonas spp. and H₂S-producing bacteria were enumerated at higher population levels compared to other microorganisms, regardless of storage temperature and packaging condition. The developed partial least squares regression (PLS-R) models based on the FTIR spectra of fish stored aerobically and under MAP exhibited satisfactory performance in the estimation of TVC, with coefficients of determination (R²) at 0.78 and 0.99, respectively. In contrast, the performances of PLS-R models based on MSI spectral data were less accurate, with R² values of 0.44 and 0.62 for fish samples stored aerobically and under MAP, respectively. FTIR spectroscopy is a promising tool to assess the microbiological quality of sea bass fillets stored in air and under MAP that could be effectively employed in the future as an alternative method to conventional microbiological analysis.

High-CO2 Modified Atmosphere Packaging with Superchilling (-1.3 °C) Inhibit Biochemical and Flavor Changes in Turbot (Scophthalmus maximus) during Storage

The effects of modified atmosphere packaging (MAP) in combination with superchilling (−1.3 °C) on the physicochemical properties, flavor retention, and organoleptic evaluation of turbot samples were investigated during 27 days storage. Results showed that high-CO₂ packaging (70% or 60% CO₂) combined with superchilling could reduce the productions of off-flavor compounds, including total volatile basic nitrogen (TVB-N) and ATP-related compounds. Twenty-four volatile organic compounds were determined by gas chromatography–mass spectrometry (GC/MS) during storage, including eight alcohols, 11 aldehydes, and five ketones. The relative content of off-odor volatiles, such as 1-octen-3-ol, 1-penten-3-ol, (E)-2-octenal, octanal, and 2,3-octanedione, was also reduced by high-CO₂ packaging during superchilling storage. Further, 60% CO₂/10% O₂/30% N₂ with superchilling (−1.3 °C) could retard the water migration on the basis of the water holding capacity, low field NMR, and MRI results, and maintain the quality of turbot according to organoleptic evaluation results during storage

Functionalization of water as a nonthermal approach for ensuring safety and quality of meat and seafood products

Meat and seafood products present a viable medium for microbial propagation, which contributes to foodborne illnesses and quality losses. The development of novel and effective techniques for microbial decontamination is therefore vital to the food industry. Water presents a unique advantage for large-scale applications, which can be functionalized to inactivate microbial growth, ensuring the safety and quality of meat and seafood products. By taking into account the increased popularity of functionalized water utilization through electrolysis, ozonation and cold plasma technology, relevant literature regarding their applications in meat and seafood safety and quality are reviewed. In addition, the principles of generating functionalized water are presented, and the safety issues associated with their uses are also discussed.Functionalization of water is a promising approach for the microbiological safety and quality of meat and seafood products and possesses synergistic effects when combined with other decontamination approaches. However, functionalized water is often misused since the active antimicrobial component is applied at a much higher concentration, despite the availability of applicable regulations. Functionalized water also shows reduced antimicrobial efficiency and may produce disinfection by-products (DBPs) in the presence of organic matter, especially at a higher concentration of active microbial component. Utilization should be encouraged within regulated guidelines, especially as hurdle technology, while plasma functionalized water which emerges with great potentials should be exploited for future applications. It is hoped that this review should encourage the industry to adopt the functionalized water as an effective alternative technique for the food industry.

On-line prediction of hazardous fungal contamination in stored maize by integrating Vis/NIR spectroscopy and computer vision

This work presents a fusion scheme to combine visible/near infrared spectroscopy and computer vision for on-line detection of Aspergillus spp. and Fusarium spp. contamination in stored maize. Spectroscopy and image information of 270 groups of maize kernels were collected at speed of 0.15 m/s. Principal component analysis indicated fungi growth on maize could be monitored by both techniques. Spectroscopy method was found sensitive for infection level identification, while computer vision was more effective for fungal strain recognition. Linear discriminant analysis based on fusion of spectral and image features provided 100% accuracy for discrimination of samples infected by different strains after stored for 12 d, which is at least 5.6% higher than single-type features. Classification rate of samples with different infection levels achieved 92.2%, also 5.5% and 10.0% higher than single technique. Moreover, data fusion improved colony counts prediction in samples by partial least squares regression, with root mean-square error of prediction value being reduced by 25.0% and 17.4%, respectively. This study demonstrated the superiority of data fusion for fungal detection in grain during on-line processing.

Prediction of various freshness indicators in fish fillets by one multispectral imaging system

In current study, a simple multispectral imaging (430–1010 nm) system along with linear and non-linear regressions were used to assess the various fish spoilage indicators during 12 days storage at 4 ± 2 °C. The indicators included Total-Volatile Basic Nitrogen (TVB-N) and Psychrotrophic Plate Count (PPC) and sensory score in fish fillets. immediately, after hyperspectral imaging, the reference values (TVB-N, PPC and sensory score) of samples were obtained by traditional method. To simplify the calibration models, nine optimal wavelengths were selected by genetic algorithm. The prediction performance of various chemometric models including partial least-squares regression (PLSR), multiple-linear regression (MLR), least-squares support vector machine (LS-SVM) and back-propagation artificial neural network (BP-ANN) were compared. All models showed acceptable performance for simultaneous predicting of PPC, TVB-N and sensory score (R²_P ≥ 0.853 and RPD ≥ 2.603). Non-linear models were considered better quantitative model to predict all of three freshness indicators in fish fillets. Among the three spoilage indices, the best predictive power was obtained for PPC value and the weakest one was acquired for TVB-N content prediction. The best model for prediction TVB-N (R²_p = 0.862; RMSEP = 3.542 and RPD = 2.678) and sensory score (R²_p = 0.912; RMSEP = 1.802 and RPD = 3.33) belonged to GA-LS-SVM and for prediction of PPC value was BP-ANN (R²_p = 0.921; RMSEP = 0.504 and RPD = 3.64). Therefore, developing multispectral imaging system based on LS-SVM model seems to be suitable for simultaneous prediction of all three indicators (R²_P > 0.862 and RPD > 2.678). Further studies needed to improve the accuracy and applicability of HSI system for predicting freshness of rainbow-trout fish.

Online Feature Selection for Robust Classification of the Microbiological Quality of Traditional Vanilla Cream by Means of Multispectral Imaging

The performance of an Unsupervised Online feature Selection (UOS) algorithm was investigated for the selection of training features of multispectral images acquired from a dairy product (vanilla cream) stored under isothermal conditions. The selected features were further used as input in a support vector machine (SVM) model with linear kernel for the determination of the microbiological quality of vanilla cream. Model training (n = 65) was based on two batches of cream samples provided directly by the manufacturer and stored at different isothermal conditions (4, 8, 12, and 15 °C), whereas model testing (n = 132) and validation (n = 48) were based on real life conditions by analyzing samples from different retail outlets as well as expired samples from the market. Qualitative analysis was performed for the discrimination of cream samples in two microbiological quality classes based on the values of total viable counts [TVC ≤ 2.0 log CFU/g (fresh samples) and TVC ≥ 6.0 log CFU/g (spoiled samples)]. Results exhibited good performance with an overall accuracy of classification for the two classes of 91.7% for model validation. Further on, the model was extended to include the samples in the TVC range 2-6 log CFU/g, using 1 log step to define the microbiological quality of classes in order to assess the potential of the model to estimate increasing microbial populations. Results demonstrated that high rates of correct classification could be obtained in the range of 2-5 log CFU/g, whereas the percentage of erroneous classification increased in the TVC class (5,6) that was close to the spoilage level of the product. Overall, the results of this study demonstrated that the UOS algorithm in tandem with spectral data acquired from multispectral imaging could be a promising method for real-time assessment of the microbiological quality of vanilla cream samples.

Antimicrobial Carvacrol Incorporated in Flaxseed Gum-Sodium Alginate Active Films to Improve the Quality Attributes of Chinese Sea bass (Lateolabrax maculatus) during Cold Storage

The objective of this research was to explore the antimicrobial activity and mechanism of carvacrol against Vibrio Parahemolyticus, Shewanella putrefaciens, Staphylococcus aureus and Pseudomonas fluorescens and evaluate the effect of the addition of carvacrol/β-cyclodextrin emulsions to flaxseed gum (FSG)-sodium alginate (SA) edible films on the preservation of Chinese sea bass (Lateolabrax maculatus) fillets during refrigerated storage. The minimum inhibitory concentration (MIC) of carvacrol against V. parahemolyticus, S. putrefaciens, S. aureus and P. fluorescens were 0.5, 0.5, 0.125, and 0.5 mg/mL, respectively. Alkaline phosphatase activity assay, nucleotide and protein leakage, and scanning electron microscope demonstrated that carvacrol damaged the external structure of the tested bacterial cells causing leakage of cytoplasmic components. At the same time, when FSG-SA films containing carvacrol used as coating agents for Chinese sea bass fillets cold storage, FSG-SA films containing 1.0 or 2.0 mg/mL carvacrol could significantly reduce TVB-N content, K-value, the degree of microbial deterioration and maintain quality of sea bass fillets according to organoleptic evaluation results.

Preservative Effects of Gelatin Active Coating Enriched with Eugenol Emulsion on Chinese Seabass (Lateolabrax maculatus) during Superchilling (−0.9 °C) Storage

This research was to evaluate the effects of gelatin (G) active coating containing eugenol/β-cyclodextrin (βCD) emulsions combined with superchilling (−0.9 °C) on physicochemical, microbiological, and organoleptic properties of Chinese seabass samples during 30 days of storage. Results showed that seabass samples dipped in G-βCD coatings containing 0.15% or 0.3% eugenol combined with superchilling could significantly lower the total volatile basic nitrogen, K value, total viable count, H2S-producing bacteria, Pseudomonas spp. and Psychrophilic counts, and free fatty acids. Further, G-βCD coatings containing eugenol with superchilling (−0.9 °C) were more effective in retarding the water migration by low field NMR and MRI results, maintaining quality of seabass during storage according to organoleptic evaluation results.

Comparison of various chemometric analysis for rapid prediction of thiobarbituric acid reactive substances in rainbow trout fillets by hyperspectral imaging technique

This study explores the potential application of hyperspectral imaging (HSI; 430-1,010 nm) coupled with different linear and nonlinear models for rapid nondestructive evaluation of thiobarbituric acid-reactive substances (TBARS) value in rainbow trout (Oncorhynchus mykiss) fillets during 12 days of cold storage (4 ± 2°C). HSI data and TBARS value of fillets were obtained in the laboratory. The primary prediction models were established based on linear partial least squares regression (PLSR) and least squares support vector machine (LS-SVM). In full spectral range, the prediction capability of LS-SVM ( R P 2  = 0.829; RMSEP = 0.128 mg malondialdehyde [MDA]/kg) was better than PLSR ( R P 2  = 0.748; RMSEP = 0.155 mg MDA/kg) model and LS-SVM model exhibited satisfactory prediction performance ( R P 2  > 0.82). To simplify the calibration models, a combination of uninformative variable elimination and backward regression (UB) was used as variable selection. Nine wavelengths were selected. Various chemometric analysis methods including linear PLSR and multiple linear regression and nonlinear LS-SVM and back-propagation artificial neural network (BP-ANN) were compared. The simplified models showed better capability than those were built based on the whole dataset in prediction of TBARS values. Moreover, the nonlinear models were preferred over linear models. Among the four chemometric algorithms, the best and weakest models were LS-SVM and PLSR model, respectively. UB-LS-SVM model was the optimal models for predicting TBARS value in rainbow trout fillets ( R P 2  = 0.831; RMSEP = 0.125 mg MDA/kg). The establishing of lipid-oxidation prediction model in rainbow trout fish was complicated, due to the fluctuations of TBARS values during storage. Therefore, further researches are needed to improve the prediction results and applicability of HIS technique for prediction of TBARS value in rainbow trout fish.

Coating Effects of ε-Polylysine and Rosmarinic Acid Combined with Chitosan on the Storage Quality of Fresh Half-Smooth Tongue Sole (Cynoglossus semilaevis Günther) Fillets

The study was to evaluate the effects of chitosan-based coating combined with rosmarinic acid (RA) with different concentrations of ε-polylysine (ε-PL) on flavor retention and sensorial properties of half-smooth tongue sole fillets during storage at 4 °C. Results showed that chitosan-based coatings combined with ε-PL and RA contributed to the reduction of off-flavor compounds, such as total volatile base nitrogen (TVB-N), trimethylamine (TMA), and ATP-related compounds, and accumulation of free amino acids (FAAs). Nineteen volatile organic compounds were analyzed by gas chromatography-mass spectrometer (GC/MS) during storage, including seven alcohols, six aldehydes, and six ketones. The coating treated fresh half-smooth tongue sole (HTS) fillets significantly reduced the relative content of off-odor volatiles, such as 1-octen-3-ol, propanal, hexanal, and octanal. According to sensory evaluation results, chitosan-based coating combined with ε-PL and RA was an effective way to maintain quality of HTS fillets during refrigerated storage.

Fabrication of gold nanorods for SERS detection of thiabendazole in apple

Thiabendazole (TBZ) is a kind of pesticide that is widely used in agriculture, and its residue may pose a threat to human health. In order to measure TBZ residues in food samples, a surface-enhanced Raman spectroscopy (SERS) method combined with a homogeneous and reusable gold nanorods (GNR) array substrate was proposed. GNR with a high uniformity was synthesized and then applied to the self-assembly of a GNR vertically aligned array. The relative standard deviation (RSD) of the array for SERS could reach 15.4%, and the array could be reused for more than seven times through the treatment of plasma etching. A logarithmic correlation between TBZ concentration and Raman intensity was obtained, with the best determination coefficient (R²) and the corresponding limit of detection (LOD) of 0.991 and 0.037 mg/L in methanol solution, and 0.980 and 0.06 ppm in apple samples, respectively. The recoveries of TBZ in apple samples ranged from 76% to 107%. This study provided a rapid and sensitive approach for detecting TBZ in apples based on SERS coupled with GNR array substrate, showing great potential for analyzing other trace contaminants in food matrices.

Evaluation of Fourier transform infrared spectroscopy and multispectral imaging as means of estimating the microbiological spoilage of farmed sea bream

The objective of the present study was the evaluation of Fourier transform infrared (FTIR) spectroscopy and multispectral imaging (MSI), in tandem with multivariate data analysis, as means of estimating the microbiological quality of sea bream. Farmed whole ungutted fish were stored aerobically at 0, 4 and 8 °C. At regular time intervals, fish samples (i.e. cut portions) were analysed microbiologically, while FTIR and MSI measurements also were acquired at both the skin and flesh sides of the samples. Partial least squares regression (PLSR) models were calibrated to provide quantitative estimations of the microbiological status of fish based on spectral data, in a temperature-independent manner. The PLSR model based on the FTIR data of fish skin exhibited good performance when externally validated, with the coefficient of determination (R²) and the root mean square error (RMSE) being 0.727 and 0.717, respectively. Hence, FTIR spectroscopy appears to be promising for the rapid and non-invasive monitoring of the microbiological spoilage of whole sea bream. Contrarily, the MSI models' performance was unsatisfactory, delimitating their potential exploitation in whole fish quality assessment. Model optimization results concerning fish flesh indicated that MSI may be propitious in skinned fish products, with its definite competence warranting further investigation.