Non-destructive prediction of thiobarbituricacid reactive substances (TBARS) value for freshness evaluation of chicken meat using hyperspectral imaging

Visible near-infrared hyperspectral imaging as a tool to characterise chicken breasts with myopathies and their durability

The surgency of myopathies has posed challenges for the industry as well as researchers, making relevant the use of objective and non-destructive technologies to inspect and discriminate these disorders. In this context, hyperspectral imaging (HSI) provides special properties that allow for an accurate selection of the affected region(s). Two experiments were conducted to evaluate the feasibility of visible and near-infrared (VIS-NIR) HSI to (1) discriminate between myopathies and (2) assess their evolution during refrigerated storage. Hyperspectral images of 98 and 77 chicken breasts, for experiment (1) and (2), respectively, were analysed dividing the breast in 3 regions to precisely assign each one a myopathy or the absence of one. Support vector machine models were employed for classification. Differences between myoglobin content and water binding detected in the VIS-NIR range (386-1016 nm) were relevant enough to accurately discriminate between myopathies (76.1 % accuracy), especially spaghetti meat (94.0 % balanced accuracy). Discrimination was also successful for storage days, detecting spoilage through spectral myoglobin isoform fingerprints (99.3 % accuracy) in the short-wave NIR region (800-1015 nm). These findings suggest a potential industrial use of hyperspectral systems to sort chicken breasts based on myopathy presence by region, and to predict the evolution of their quality traits during refrigerated storage, ultimately tailoring the breast destination for each case and avoiding food waste.

A double cross-linked film based on carboxymethyl chitosan binding with L-cysteine/ oxidized konjac glucomannan with slow-release of nisin for food preservation

In order to address the issue of food contamination by microorganisms and effectively harness the antibacterial properties of nisin, we attempted to incorporate nisin into natural polymer films while addressing its inherent instability. An antibacterial food packaging film based on carboxymethyl chitosan (CCS) binding with L-cysteine (CYS) and oxidized konjac glucomannan (OKG) was developed through both Schiff base reaction and addition reaction of thiol aldehyde. To analyze the effect of addition reaction of thiol aldehyde on the CCS-CYS/OKG films' physicochemical properties, the CCS-CYS was prepared with different CYS combination rates, which were further used to fabricate composite films. It is found that the incorporation of CYS improved the mechanical properties of CCS-CYS/OKG films and facilitated the formation of a denser network structure. The incorporation of CYS also enhanced the film's ultraviolet barrier property, swelling behaviors, as well as loading and release capacity of nisin. As the CYS binding rate of 22.76 %, the CCS-CYS(2)/OKG film exhibited an efficient loading capacity for nisin at 91.53 % with a sustained release over 240 min. Kinetic model analysis revealed that nisin was released through non-Fickian diffusion, mainly driven by gradient concentration and osmotic pressure. Furthermore, the CCS-CYS(2)/OKG-nisin film also displayed significant antibacterial activity against Staphylococcus aureus with an inhibition zone diameter of 22.63 mm at 10 h, thereby, that was also successfully employed for salmon preservation.

Prediction of chicken breast meat freshness based on hyperspectral imaging technique and high-throughput sequencing

In this article, the hyperspectral imaging technique and the high-throughput sequencing were combined to construct prediction models for the freshness of chicken breast meat. The quality indicators including color, pH, TVC, TVB-N and TBARS were measured to reflect the freshness changes of chicken breast meat under 4 ℃ storage. Meanwhile, spectral images of chicken breast meat were obtained using visible near-infrared (400-1,000 nm) hyperspectral imaging. Through high-throughput sequencing, the major spoilage bacteria including Pseudomonas, Brochothrix and Escherichia were screened out to construct the models for predicting chicken freshness. After spectral preprocessing and characteristic wavelength selection, the prediction models were established using partial least squares regression (PLSR) and support vector machine (SVM). Among the models, the SNV-PLSR model based on characteristic wavelength for Pseudomonas content (Rp2=0.84, RMSEP=0.38, RPD=3.79) posed stronger predictive and generalization abilities. Therefore, the Pseudomonas count was chosen as a characteristic indicator for establishing an HSI-based prediction model to reflect the freshness of chicken breast meat.

Effect of Low-Temperature Plasma Sterilization on the Quality of Pre-Prepared Tomato-Stewed Beef Brisket During Storage: Microorganism, Freshness, Protein Oxidation and Flavor Characteristics

Traditional tomato-braised beef brisket with potatoes is celebrated for its rich, complex flavors and culinary appeal but requires lengthy preparation. Pre-packaged versions of the dish rely on thermal sterilization for safety; however, high-temperature processing accelerates protein and lipid oxidation, thereby compromising its sensory quality. As the demand for ready-to-eat meals grows, the food industry faces the challenge of ensuring microbial safety while preserving flavor integrity. In this study, low-temperature plasma sterilization (LTPS) (160 KV, 450 s) was evaluated as a non-thermal alternative to conventional high-temperature short-time (HSS) sterilization. Furthermore, a comprehensive analysis was conducted over a 10-day storage period, assessing microbial viability, physicochemical properties (pH, shear force, and water-holding capacity), oxidative markers (TBARS, TVB-N, and protein carbonyls), volatile compounds (GC-MS), and electronic nose (e-nose) responses. The results revealed that LTPS (160 kV, 450 s) successfully maintained bacterial counts below regulatory limits (5 lg CFU/g) for 72 h, ensuring that the microbial indicators of short-term processed products sold to supermarkets through cold chain logistics were in the safety range. Additionally, LTPS-treated samples showed a 4.2% higher water-holding capacity (p < 0.05) during storage, indicating improved preservation of texture. Furthermore, LTPS-treated samples exhibited 32% lower lipid oxidation (p < 0.05) and retained 18% higher sulfhydryl content (p < 0.05) compared to HSS, indicating reduced protein oxidation. GC-MS and e-nose analyses showed that LTPS preserved aldehydes and ketones associated with meaty aromas, while HSS contributed to sulfur-like off-flavors. Principal component analysis showed that the LTPS samples had shorter distances across various storage periods compared to HSS, indicating reduced differences in aroma difference. The findings of this study demonstrate LTPS's dual efficacy in microbial control and aroma preservation. The technology presents a viable strategy for extending the shelf life of pre-prepared meat dishes while reducing oxidative and flavor deterioration, thereby establishing a solid foundation for LTPS application in the pre-prepared food sector.

Influence of Phosphate Marinades on the Quality and Flavor Characteristics of Prepared Beef

Phosphate has been widely used in beef to improve processing characteristics such as tenderness and water-holding capacity. However, the effects of phosphates on the quality and especially the flavor of beef are not well understood. This study investigated the influence of eight different phosphate marinade solutions on the quality and flavor of prepared beef. The results revealed that the thawing loss in the control group was 11.47%, and NaCl with sodium hexametaphosphate (SYCP) had the lowest thawing loss, with a value of 2.13%, which was reduced by 81.43% as compared to the control group. The shear force of the control group was 3.85 kg, and the shear work was 10.03 kg. The best tenderness was recorded in the NaCl with sodium hexametaphosphate (SYST) group, which had a shear force of 1.14 kg and shear work of 3.34 kg. The incorporation of phosphates suppressed fat oxidation and increased the total free amino acid content. Additionally, the levels of certain key volatile flavor compounds, particularly those associated with fat oxidation, such as hexanal, heptanal, octanal, and nonanal, were reduced. In terms of sensory evaluation, juiciness, flavor, tenderness, and overall acceptability in the treatment group were significantly increased (p < 0.05). Overall, the results indicate that adding phosphates can enhance the quality of processed beef, inhibit lipid oxidation, and improve sensory evaluation.

Calibration of visible and near-infrared spectral imaging technology to predict the quality evolution of retail fresh pork bellies with different fat content

This study investigates quality changes occurred in sliced pork belly with different fat content during refrigerated storage, and the potential of spectral imaging technology in predicting quality properties. Pork bellies with different fat levels (low 'LF', medium 'MF' and high 'HF') were selected from slaughtering houses and directly transferred to the laboratory. The sliced bellies were packed in modified atmosphere packages with high oxygen levels (80 %) and the essential visual and olfactory characteristics, microbiological load, pH, lipid oxidation and colour values were assessed throughout 20 days of refrigerated storage. The spectral images of all belly samples were acquired in the wavelength range from 386 to 1015 nm. Results revealed significant quality losses throughout storage attributed primarily to lipid oxidation and colour changes. The HF bellies showed lower L* and higher a* values than LF and MF. Additionally, the LF and MF bellies, with higher proportion of polyunsaturated fatty acids, showed higher lipid oxidation compared to the HF bellies throughout storage. The appropriate combination of spectral preprocessing, together with the appropriate selection of the region of interest, facilitated the development of robust models to predict the visual appearance, odour, lipid oxidation, and a* values of belly slices during refrigerated storage. The obtained results demonstrated the potential of spectral imaging for predicting quality characteristics of sliced fresh pork bellies during refrigerated storage.

Muscle-Specific Effects of Genotype, Animal Age, and Wet Aging Duration on Beef Color, Tenderness, and Sensory Characteristics

This study investigated the effects of genotype, animal age, muscle type, and aging duration on meat quality characteristics of Psoas major (PM), Longissimus thoracis (LT), Longissimus lumborum (LL), and Gluteus Medius (GM) muscles. The PM, LT, LL, and GM muscles were sourced from a total of 32 bulls, consisting of 16 humped (Bos indicus) and 16 humpless (Bos indicus × Bos taurus) bulls aged 21 ± 2 and 30 ± 3 months. The muscles underwent aging durations of 0, 7, and 14 days. Meat pH, color, drip loss, cooking loss, instrumental shear force, lipid oxidation (thiobarbituric acid reactive substances/TBARS), and sensory analysis were performed. Our results indicated that humped bulls had superior color, while humpless bulls exhibited better sensory characteristics. The 30 ± 3 months of age bulls showed improved color and sensory characteristics with higher TBARs values than the 21 ± 2 months of age bulls. The color, tenderness, and sensory characteristics improved in PM and LT at 7 days, whereas in LL and GM they improved at 14 days. PM showed better tenderness and overall acceptability among different muscles, while LL showed better color and oxidative stability. This study suggested the necessity of muscle-specific aging strategies to enhance the meat quality characteristics of humped and humpless bulls. Further research could explore additional aging durations and other muscle types to better understand their impact on meat quality characteristics.

Quality Differences in Frozen Mackerel According to Thawing Method: Potential Classification via Hyperspectral Imaging

Seafood quality preservation remains a critical focus in the food industry, particularly as the freeze-thaw process significantly impacts the freshness and safety of aquatic products. This study investigated quality changes in frozen mackerel subjected to two thawing methods, room temperature (RT) and running water (WT), and assessed the potential of hyperspectral imaging (HSI) for classifying these methods. After thawing, mackerel samples were stored at 5 °C for 21 days, with physicochemical, textural, and spectroscopic analyses tracking quality changes and supporting the development of a spectroscopic classification model. Compared with the WT method, the RT method delayed changes in key quality indicators, including pH, total volatile basic nitrogen (TVB-N), and total viable count (TVC), by 1-2 days, suggesting it may better preserve initial quality. Texture profile analysis showed similar trends, supporting the benefit of RT in maintaining quality. A major focus was on using HSI to assess quality and classify thawing methods. HSI achieved high classification accuracy (Rc2 = 0.9547) in distinguishing thawing methods up to three days post-thaw, with 1100, 1200, and 1400 nm wavelengths identified as key spectral markers. The HIS's ability to detect differences between thawing methods, even when conventional analyses showed minimal variation, highlights its potential as a powerful tool for quality assessment and process control in the seafood industry, enabling detection of subtle quality changes that traditional methods may miss.

Prediction and Visualization of Total Volatile Basic Nitrogen in Yellow Croaker (Larimichthys polyactis) Using Shortwave Infrared Hyperspectral Imaging

In the present investigation, we have devised a hyperspectral imaging (HSI) apparatus to assess the chemical characteristics and freshness of the yellow croaker (Larimichthys polyactis) throughout its storage period. This system operates within the shortwave infrared spectrum, specifically ranging from 900 to 1700 nm. A variety of spectral pre-processing techniques, including standard normal variate (SNV), multiple scatter correction, and Savitzky-Golay (SG) derivatives, were employed to augment the predictive accuracy of total volatile basic nitrogen (TVB-N)-which serves as a critical freshness parameter. Among the assessed methodologies, SG-1 pre-processing demonstrated superior predictive accuracy (Rp2 = 0.8166). Furthermore, this investigation visualized freshness indicators as concentration images to elucidate the spatial distribution of TVB-N across the samples. These results indicate that HSI, in conjunction with chemometric analysis, constitutes an efficacious instrument for the surveillance of quality and safety in yellow croakers during its storage phase. Moreover, this methodology guarantees the freshness and safety of seafood products within the aquatic food sector.

Effects of temperature fluctuations on the quality and microbial diversity of beef meatballs during simulated cold chain distribution

BACKGROUND

Cold chain distribution with multiple links maintains low temperatures to ensure the quality of meat products, whereas temperature fluctuations during this are often disregarded by the industry. The present study simulated two distinct temperatures cold chain distribution processes. Quality indicators and high-throughput sequencing were employed to investigate the effects of temperature fluctuations on the quality and microbial diversity of beef meatballs during cold chain distribution.

RESULTS

Quality indicators revealed that temperature fluctuations during simulated cold chain distribution significantly (P < 0.05) exacerbated the quality deterioration of beef meatballs. High-throughput sequencing demonstrated that temperature fluctuations affected the diversity and structure of microbial community. Lower microbial species abundance and higher microbial species diversity were observed in the temperature fluctuations group. Proteobacteria and Pseudomonas were identified as the dominant phylum and genus in beef meatballs, respectively, exhibiting faster growth rates and greater relative abundance under temperature fluctuations.

CONCLUSION

The present study demonstrates that temperature fluctuations during simulated cold chain distribution can worsen spoilage and shorten the shelf life of beef meatballs. It also offers certain insights into the spoilage mechanism and preservation of meat products during cold chain distribution. © 2024 Society of Chemical Industry.

Xanthan gum ink based on Lycium ruthenicum anthocyanin as an indicator of color change for monitoring freshness of cold fresh meat

The continuous development of intelligent food packaging has led to an increased focus on using freshness-indicating inks, which could provide a high level of quality control and consumer experience. This study aimed to further promote the application of xanthan gum ink in food freshness indication by optimizing its performance in screen printing. A novel freshness-indicating ink was prepared using Lycium ruthenicum anthocyanin (LRA) as the core indicator, glucose as the pigment carrier, soybean oil as the linker, and xanthan gum (XG) as the thickener. Scanning electron microscopy (SEM) demonstrated that the ink was uniformly distributed on paper using screen printing. Rheological and particle size analyses revealed that the incorporation of XG significantly enhanced the interaction force between droplets in the ink system. Further tests on viscosity, fineness, and initial dryness indicated that XG, a natural microbial polysaccharide with excellent stability, could effectively improve the flowability of the ink. Specifically, at a 0.3 % XG content, the ink exhibited a unimodal particle size distribution with an average particle size of 851.02 nm and a zeta potential of -27 mV. This indicated the ink system was stable and uniform, with optimal rheological properties and printing suitability. Furthermore, the printed freshness indication labels exhibited a significant change in color as the freshness of the refrigerated meat changed. This study develops a natural and safe method for monitoring the freshness of refrigerated meat and provides an optimized idea for applying indicator inks.

Chitosan-based packaging films with antibacterial-sterilization integrated continuous activity for extending the shelf life of perishable foods

The current food packaging films can be preservative but lack the function of combining antibacterial and sterilization which lead to films can not maximize prolong shelf life of perishable foods. This study provided a new strategy to realize prolonging shelf life of perishable foods by integrating antibacterial and sterilization which focused on applying photodynamic inactivation to films with continuous activity, where curcumin (CUR) and sodium copper chlorophyll (SCC) were loaded into chitosan (CS) films. Compared to pure CS films, the barrier capacity (oxygen permeability and water vapor permeability) and mechanical properties of composite films were improved by introducing CUR and SCC. In addition, the composite film can effectively against food-borne pathogenic bacteria and significantly prolong the shelf life of cherries and pork. The provided strategy has potential application prospects in food preservation packaging.

Monitoring the Aging and Edible Safety of Pork in Postmortem Storage Based on HSI and Wavelet Transform

The process of meat postmortem aging is a complex one, in which improved tenderness and aroma coincide with negative effects such as water loss and microbial growth. Determining the optimal postmortem storage time for meat is crucial but also challenging. A new visual monitoring technique based on hyperspectral imaging (HSI) has been proposed to monitor pork aging progress. M. longissimus thoracis from 15 pigs were stored at 4 °C for 12 days while quality indexes and HSI spectra were measured daily. Based on changes in physical and chemical indicators, 100 out of the 180 pieces of meat were selected and classified into rigor mortis, aged, and spoilt meat. Discrete wavelet transform (DWT) technology was used to improve the accuracy of classification. DWT separated approximate and detailed signals from the spectrum, resulting in a significant increase in classification speed and precision. The support vector machine (SVM) model with 70 band spectra achieved remarkable classification accuracy of 97.06%. The study findings revealed that the aging and microbial spoilage process started at the edges of the meat, with varying rates from one pig to another. Using HSI and visualization techniques, it was possible to evaluate and portray the postmortem aging progress and edible safety of pork during storage. This technology has the potential to aid the meat industry in making informed decisions on the optimal storage and cooking times that would preserve the quality of the meat and ensure its safety for consumption.

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.

Preparation and Characterization of a Biodegradable Film Using Irradiated Chitosan Incorporated with Lysozyme and Carrageenan and Its Application in Crayfish Preservation

In this study, a composite film was prepared using irradiated chitosan, lysozyme, and carrageenan for crayfish preservation. First, the chitosan was degraded by gamma rays, with the best antimicrobial properties being found at 100 KGy. By using the response surface method, the components of the composite film were irradiated chitosan (CS) at 0.016 g/mL, lysozyme (LM) at 0.0015 g/mL, and carrageenan (CA) at 0.002 g/mL. When compared to the natural chitosan film, the Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) results demonstrated that the chemical properties of the composite film did not change with the addition of LM and CA, while the physical and antibacterial properties increased, including tensile strength (16.87 → 20.28 N), hydrophobicity (67.9 → 86.3°), and oxygen permeability (31.66 → 24.31 m³·um/m²·day·kPa). Moreover, the antibacterial activity of the films increased with the addition of LM and CA, especially for Shewanella putrefaciens: the zone of inhibition (mm) of CS, CS/LM, and CS/LM/CA was 9.97 ± 0.29, 14.32 ± 0.31, and 14.78 ± 0.21, respectively. Finally, the CS/LM/CA film could preserve crayfish for 10 days at 4 °C, whereas the polyethylene (PE) film could only preserve them for 6 days. Moreover, the composite film was excellent at inhibiting oxidative deterioration (TBARS value: 2.12 mg/kg, day10) and keeping the texture of crayfish muscle. Overall, our results suggested that the CS/LM/CA composite film produced can be applied as a biodegradable film in aquatic product packaging.

Determination of Freshness of Mackerel (Scomber japonicus) Using Shortwave Infrared Hyperspectral Imaging

Shortwave infrared (SWIR) hyperspectral imaging was applied to classify the freshness of mackerels. Total volatile basic nitrogen (TVB-N) and acid values, as chemical compounds related to the freshness of mackerels, were also analyzed to develop a prediction model of freshness by combining them with hyperspectral data. Fresh mackerels were divided into three groups according to storage periods (0, 24, and 48 h), and hyperspectral data were collected from the eyes and whole body, separately. The optimized classification accuracies were 81.68% using raw data from eyes and 90.14% using body data by multiple scatter correction (MSC) pretreatment. The prediction accuracy of TVB-N was 90.76%, and the acid value was 83.76%. These results indicate that hyperspectral imaging, as a nondestructive method, can be used to verify the freshness of mackerels and predict the chemical compounds related to the freshness.

Neutral Electrolyzed Water in Chicken Breast-A Preservative Option in Poultry Industry

Chicken is one of the most consumed meats in the world because it is an economical protein source with a low fat content. Its conservation is important to maintain safety along the cold chain. In the present study, the effect of Neutral Electrolyzed Water (NEW) at 55.73 ppm was evaluated on contaminated chicken meat with Salmonella Typhimurium and Escherichia coli O157:H7, which was stored in refrigerated conditions. The present study was carried out to check whether the application of NEW can help to preserve chicken breasts without affecting its sensory characteristics. Chicken quality was measured by analyzing physicochemical properties (pH, color, lactic acid, total volatile basic nitrogen, and thiobarbituric acid reactive substances content) after bactericidal intervention. This work includes a sensory study to determine if its use affects the organoleptic properties of the meat. The results showed that in the in vitro assay, NEW and NaClO, achieved bacterial count reductions of >6.27 and 5.14 Log10 CFU for E. coli and Salmonella Typhimurium, respectively, even though, in the in situ challenge, they showed a bacterial decrease of 1.2 and 0.33 Log10 CFU/chicken breast in contaminated chicken breasts with E. coli and Salmonella Typhimurium, respectively, after 8 days of storage, and NaClO treatment did not cause bacterial reduction. Nonetheless, NEW and NaClO did not cause lipid oxidation and nor did they affect lactic acid production, and they also slowed meat decomposition caused by biogenic amines. Sensory results showed that chicken breast characteristics like appearance, smell, and texture were not affected after NEW treatment, and obtained results showed that NEW could be used during chicken meat processing due to the chicken physicochemical stability. However, more studies are still needed.

Construction of a simple dual-mode ATP-sensing system for reliable fish freshness evaluation

Adenosine triphosphate (ATP), the main carrier of chemical energy, plays a key role in various biochemical reactions such as cellular metabolism. Currently, ATP levels are considered important indicators of microbial content in food safety, and food freshness can be determined by detecting ATP content. Some ATP sensing strategies have been applied to evaluate food freshness. However, cumbersome nanomaterial preparation, low sensitivity, and low reliability hamper their widespread application. Herein, a simple, high-performance, and reliable dual-mode sensing system based on hemin-G-quadruplex (G4) DNAzyme was established to detect ATP and assess fish freshness. Two nucleic acid probes, including subunits of the hemin-G4 DNAzyme in inactive structures and anti-ATP aptamer, self-assemble upon the input of ATP into the active hemin-G4 DNAzyme unit. The generated DNAzyme acts as a biocatalyst for colorimetric or fluorescent readout of the sensing process. The colorimetric and fluorescent dual-mode sensing system enables highly sensitive and reliable analysis of target ATP with detection limits of 71 nM and 73 nM, respectively. Moreover, the biosensor exhibited good selectivity for differentiating ATP from other interfering analytes. The proposed system was used to detect ATP in perch samples, and a linear correlation between ATP level and microbial content was confirmed. The established ATP-sensing system reliably evaluated fish freshness. Notably, in comparison with microbiological counts, the proposed DNAzyme-based dual-mode strategy for freshness evaluation is facile, highly efficient, and cost-effective, thus providing a promising method for food safety and quality monitoring.

Multi-task convolutional neural network for simultaneous monitoring of lipid and protein oxidative damage in frozen-thawed pork using hyperspectral imaging

Lipid and protein oxidation are the main causes of meat deterioration during freezing. Traditional methods using hyperspectral imaging (HSI) need to train multiple independent models to predict multiple attributes, which is complex and time-consuming. In this study, a multi-task convolutional neural network (CNN) model was developed for visible near-infrared HSI data (400-1002 nm) of 240 pork samples treated with different freeze-thaw cycles (0-9 cycles) to evaluate the feasibility of simultaneously monitoring lipid oxidation (thiobarbituric acid reactive substance content) and protein oxidation (carbonyl content) in pork. The performance of the commonly used partial least squares regression (PLSR) model based on the spectra after pre-processing (Standard normal variate, Savitzky-Golay derivative, and Savitzky-Golay smoothing) and feature selection (Regression coefficients) and single-output CNN model was compared. The results showed that the multi-task CNN model achieved the optimal prediction accuracies for lipid oxidation (R²p = 0.9724, RMSEP = 0.0227, and RPD = 5.2579) and protein oxidation (R²p = 0.9602, RMSEP = 0.0702, and RPD = 4.6668). In final, the changes of lipid and protein oxidation of pork in different freeze-thaw cycles were successfully visualized. In conclusion, the combination of HSI and multi-task CNN method shows the potential of end-to-end prediction of pork oxidative damage. This study provides a new, convenient and automated technique for meat quality detection in the food industry.

Incorporating Portulaca oleracea extract endows the chitosan-starch film with antioxidant capacity for chilled meat preservation

This study aimed to investigate the application potential of Portulaca oleracea extract (POE) in active packaging for the preservation of chilled meat. First, the antioxidant capacity and active ingredients of POE were systematically studied. The results demonstrated that POE has excellent antioxidant capacity and contains abundant antioxidant compounds. Subsequently, antioxidant-active packaging films based on chitosan and starch containing different concentrations of POE (CS/POE films) were successfully developed. The main physicochemical and mechanical properties of the CS/POE films were characterized and evaluated. The CS/POE films exhibited remarkable antioxidant activity and can significantly reduce lipid oxidation in meat. Compared with polyethylene film, the CS/POE films-treated meats had better preservation effects and longer shelf-life. These findings suggested that CS/POE film has the potential to become a good alternative to conventional plastics in food packaging. In conclusion, Portulaca oleracea extract is an excellent natural antioxidant with great potential in active packaging for chilled meat preservation.

Effects of the Aging Period and Method on the Physicochemical, Microbiological and Rheological Characteristics of Two Cuts of Charolais Beef

Wet-aging (WA) and dry-aging (DA) methods are usually used in the beef industry to satisfy the consumers' tastes; however, these methods are not suitable for all anatomical cuts. In this study, WA and DA were applied to improve the quality of two cuts of Charolais beef (Longissimus dorsi and Semitendinosus). For 60 days (i.e., 2 days, 15 days, 30 days and 60 days of sampling), a physicochemical, rheological, and microbiological analysis were performed at WA (vacuum packed; temperature of 4 ± 1 °C) and at DA (air velocity of 0.5 m/s; temperature of 1 ± 1 °C; relative humidity of 78 ± 10%) conditions. The results showed that the aging method influenced the aging loss (higher in the DA), cooking loss (higher in the WA), malondialdehyde concentration (higher in the DA) and fatty acid profile (few changes). No differences in the drip loss and color were observed, which decreased after 30 days of aging. The WBSF and TPA test values changed with increasing an aging time showing that the aging improved the tenderness of meat regardless of the aging method. Moreover, the aging method does not influence the microbiological profile. In conclusion, both WA and DA enhanced the quality of the different beef cuts, suggesting that an optimal method-time and aging combination could be pursued to reach the consumers' preferences.

Development and comparison of classification models on VIS-NIR hyperspectral imaging spectra for qualitative detection of the Staphylococcus aureus in fresh chicken breast

Chicken is at risk of contaminated foodborne pathogens in the production process. Timely and nondestructive detection of foodborne pathogens in chicken is essential for food security. The study aims to explore the feasibility of developing efficient classification models for qualitative detection of Staphylococcus aureus in chicken breast using the hyperspectral imaging technique. Principal component analysis was used to process the full spectral information and three wavelength selection methods (competitive adaptive reweighted sampling, genetic algorithm, and successive projections algorithm) were applied to extract effective wavelengths. These methods were combined with the support vector machine algorithm to develop conventional classification models, respectively. In addition, a convolutional neural network model based on deep learning was designed and trained for comparison. The performance of the convolutional neural network model was significantly better than that of conventional classification models. The overall accuracy for chicken sample classifications was improved from 83.88% to 91.38%. The results demonstrated that deep learning can effectively extract spectral features and promote the application of hyperspectral imaging in foodborne pathogens detection of chicken products.

Non-destructive prediction of yak meat freshness indicator by hyperspectral techniques in the oxidation process

This study examined the potential of hyperspectral techniques for the rapid detection of characteristic indicators of yak meat freshness during the oxidation of yak meat. TVB-N values were determined by significance analysis as the characteristic index of yak meat freshness. Reflectance spectral information of yak meat samples (400-1000 nm) was collected by hyperspectral technology. The raw spectral information was processed by 5 methods and then principal component regression (PCR), support vector machine regression (SVR) and partial least squares regression (PLSR) were used to build regression models. The results indicated that the full-wavelength based on PCR, SVR, and PLSR models were shown greater performance in the prediction of TVB-N content. In order to improve the computational efficiency of the model, 9 and 11 characteristic wavelengths were selected from 128 wavelengths by successive projection algorithm (SPA) and competitive adaptive reweighted sampling (CARS), respectively. The CARS-PLSR model exhibited excellent predictive power and model stability.

Development of a Portable Near-Infrared Spectroscopy Tool for Detecting Freshness of Commercial Packaged Pork

Real-time monitoring of meat quality requires fast, accurate, low-cost, and non-destructive analytical methods that can be used throughout the entire production chain, including the packaged product. The aim of this work was to evaluate the potential of a portable near-infrared (NIR) spectroscopy tool for the on-site detection of freshness of pork loin fillets in modified atmosphere packaging (MAP) stored on display counters. Pork loin slices were sealed in MAP trays under two proportions of O2/CO2/N2: High-Ox-MAP (30/40/30) and Low-Ox-MAP (5/20/75). Changes in pH, color, thiobarbituric acid reactive substances (TBARS), Warner−Bratzler shear force (WBSF), and microbiology (total viable counts, Enteriobacteriaceae, and lactic acid bacteria) were monitored over 15 days post-mortem at 4 °C. VIS-NIR spectra were collected from pork fillets before (through the film cover) and after opening the trays (directly on the meat surface) with a portable LABSPEC 5000 NIR system in diffuse reflectance mode (350−2500 nm). Quantitative NIR models by partial least squares regression (PLSR) showed a promising prediction ability for meat color (L*, a*, C*, and h*) and microbiological variables (R2VAL > 0.72 and RPDVAL > 2). In addition, qualitative models using PLS discriminant analysis obtained good accuracy (over 90%) for classifying pork samples as fresh (acceptable for consumption) or spoiled (not acceptable) based on their microbiological counts. VIS-NIR spectroscopy allows rapid evaluation of product quality and shelf life and could be used for on-site control of pork quality.

Preliminary Investigation on the Relationship between Raman Spectra of Beef and Metmyoglobin and Metmyoglobin Reductase Activity

A hand-held Raman spectroscopic device was used as a rapid nondestructive testing device to predict the metmyoglobin (MetMb) and metmyoglobin reductase activity (MRA) values on the surface layer of fresh beef. Longissimus dorsi muscles were from 10 young bulls (Holstein-Friesian) from two different cattle farms (group A = 5 and B = 5). The Raman spectra of 100 samples were correlated with the MetMb and MRA values using partial least squares regression (PLSR). Two groups could be discriminated, and the separate correlation models were better than the joint correlation model for the fresh beef. The coefficients of determination are R 2 = 0.81 (group A) and R 2 = 0.87 (group B) for MetMb and R 2 = 0.80 (group A) and R 2 = 0.85 (group B) for MRA. The results show the usefulness of Raman spectra in predicting the inner traits such as MetMb and MRA during meat storage. In conclusion, it is feasible to determine the MetMb and MRA values by Raman spectroscopy. Color is an important indicator of beef freshness and can vary depending on the age, sex, and breed of the cow. They play a very important role in human nutrition. The color of meat is an important indicator of meat freshness, and many researchers are already investigating the causes of color changes. The research was conducted in this environment.

Recent advances in muscle food safety evaluation: Hyperspectral imaging analyses and applications

As there is growing interest in process control for quality and safety in the meat industry, by integrating spectroscopy and imaging technologies into one system, hyperspectral imaging, or chemical or spectroscopic imaging has become an alternative analytical technique that can provide the spatial distribution of spectrum for fast and nondestructive detection of meat safety. This review addresses the configuration of the hyperspectral imaging system and safety indicators of muscle foods involving biological, chemical, and physical attributes and other associated hazards or poisons, which could cause safety problems. The emphasis focuses on applications of hyperspectral imaging techniques in the safety evaluation of muscle foods, including pork, beef, lamb, chicken, fish and other meat products. Although HSI can provide the spatial distribution of spectrum, characterized by overtones and combinations of the C-H, N-H, and O-H groups using different combinations of a light source, imaging spectrograph and camera, there still needs improvement to overcome the disadvantages of HSI technology for further applications at the industrial level.

Visualized detection of quality change of cooked beef with condiments by hyperspectral imaging technique

The heat treatment and seasoning of meat are indispensable before its consumption. In this work, the spectral characteristics of cooked meat and condiments were analysed by hyperspectral imaging (HSI) technology. The spectral reflectance of spices was significantly lower than that of meat protein, and that the spectral reflectance of protein regularly increased upon heating at 800-956 nm range. PCA pre-process and SVM models were used to predict beef moisture (R 2 = 0.912) and tenderness (R 2 = 0.771) based on 100 beef data. Mapping technology clearly showed the dynamic change of meat tenderness during heating, and the performance of 3D mapping was better than that of 2D mapping. Based on 750 nm/900 nm ratio image and machine-vision method, spice uniformity was accurately calculated. Thus, the quality of cooked meat and condiments distribution can be simultaneously evaluated by HSI. This technology can be used in the intelligent production of complex meat products in the future.

Identification of Four Chicken Breeds by Hyperspectral Imaging Combined with Chemometrics

The current study aims to explore the potential of the combination of hyperspectral imaging and chemometrics in the rapid identification of four chicken breeds. The hyperspectral data of four chicken breeds were collected in the range of 400–900 nm. Five pretreatment methods were used to pretreat the original spectra. The important characteristic wavelength variables were extracted by random frog (RF), successive projection algorithm (SPA), and competitive adaptive reweighted sampling (CARS) algorithms. The classification models were established by using support vector machine (SVM), k-nearest neighbor (KNN), and partial least squares-discriminant analysis (PLS-DA). The results showed that the mean normalization pretreatment method was preferable, and overall classification accuracy of SVM-based models was higher than that of KNN-based and PLS-DA-based models. The correct classification rate (CCR) of the full-spectrum SVM model (Full-SVM) could reach 96.25%. The SPA method extracted 13 important wavelengths, and the SVM model based on SPA (SPA-SVM) achieved 90% CCR. This study can provide a theoretical reference for the discriminant analysis of chicken breeds.

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

Meat 4.0 refers to the application the fourth industrial revolution (Industry 4.0) technologies in the meat sector. Industry 4.0 components, such as robotics, Internet of Things, Big Data, augmented reality, cybersecurity, and blockchain, have recently transformed many industrial and manufacturing sectors, including agri-food sectors, such as the meat industry. The need for digitalised and automated solutions throughout the whole food supply chain has increased remarkably during the COVID-19 pandemic. This review will introduce the concept of Meat 4.0, highlight its main enablers, and provide an updated overview of recent developments and applications of Industry 4.0 innovations and advanced techniques in digital transformation and process automation of the meat industry. A particular focus will be put on the role of Meat 4.0 enablers in meat processing, preservation and analyses of quality, safety and authenticity. Our literature review shows that Industry 4.0 has significant potential to improve the way meat is processed, preserved, and analysed, reduce food waste and loss, develop safe meat products of high quality, and prevent meat fraud. Despite the current challenges, growing literature shows that the meat sector can be highly automated using smart technologies, such as robots and smart sensors based on spectroscopy and imaging technology.

Effects of Onion Extract and Onion Peel Extract on the Formation of Polycyclic Aromatic Hydrocarbons in Charcoal-Grilled Pork Patties

ABSTRACT

This study investigated the effects of different concentrations (0.0005, 0.005, 0.05, 0.25, and 0.5%) of onion extract (OE) and onion peel extract (OPE) on the formation of four polycyclic aromatic hydrocarbons (PAHs) in charcoal-grilled pork patties. Both OE and OPE inhibited the formation of four PAHs in charcoal-grilled pork patties, with the highest inhibition rate reaching 88.33% on 0.50% OE addition and 98.79% on 0.05 and 0.25% OPE addition. OPE has greater inhibitory effect on the formation of four PAHs than OE does; this may be related to OPE's higher concentrations of flavonoids and higher free-radical scavenging activities. Both OE and OPE worked to lower thiobarbituric acid reactive substance values of charcoal-grilled pork patties. The inhibitory effect of OE and OPE on four PAHs showed the same trend as their antilipid oxidation effects, but the correlation was not strong. In addition to antilipid oxidation, other pathways are also involved in the inhibition of PAH formation.

HIGHLIGHTS

Lycium barbarum polysaccharide inhibits lipid oxidation and protein degradation in Tan sheep meatballs during frozen storage

The aim of the present study was to evaluate the effectiveness of Lycium barbarum polysaccharide (LBP) on lipid oxidation and protein degradation in Tan sheep meatballs during the frozen period. The meatballs were treated with LBP at 0.01%, 0.02%, and 0.03% and stored at –18±1°C for 0, 3, 6, 9, and 12 weeks. The effects of LBP treatment were investigated using the contents of total volatile basic nitrogen (TVB-N), texture profile (TP), thiobarbituric acid reactive substances (TBARS), colour, and pH values, compared with 0.02% butylated hydroxytoluene treatment and the blank control. The results showed that LBP treatment significantly decreased TBARS content compared with the control, which confirmed LBP to be a highly effective component in preventing lipid oxidation of Tan sheep meatballs during frozen storage, and protein degradation in Tan sheep meatballs had a significant inhibition effect because of TVB-N value reduction. In addition, the colour, TP and pH values of meatballs treated with LBP were improved dramatically. To further determine the quality changes of the blank control and all treated groups during storage, the comprehensive score evaluation equation based on principal component analysis was obtained: Y=0.51632Y₁+0.29589Y₂ (cumulative contribution rate=81.221%), and the 0.02% LBP-treated group had a higher comprehensive score than the other groups, and the quality of LBP-treated meatballs was better as well. In summary, LBP may reduce or inhibit lipid oxidation and protein degradation, and enhance overall quality and shelf-life in prepared meat products.

An evaluation of biochemical, structural and volatile changes of dry-cured pork using a combined ion mobility spectrometry, hyperspectral and confocal imaging approach

BACKGROUND

Food processing induces various modifications that affect the structure, physical and chemical properties of food products and hence the acceptance of the product by the consumer. In this work, the evolution of volatile components, 2-thiobarbituric acid reactive substances (TBARS), moisture content (MC) and microstructural changes of pork was investigated by hyperspectral (HSI) and confocal imaging (CLSM) techniques in synergy with gas chromatography-ion mobility spectrometry (GC-IMS). Models based on partial least squares regression (PLSR) were developed using the full HSI spectrum variables as well as optimum variables selected through a competitive adaptive reweighted sampling algorithm.

RESULTS

Prediction results for MC and TBARS using multiplicative scatter correction pre-processed spectra models demonstrated greater efficiency and predictability with determination coefficient of prediction of 0.928, 0.930 and root mean square error of prediction of 0.114, 1.002, respectively. Major structural changes were also observed during CLSM imaging, which were greatly pronounced in pork samples oven cooked for 15 and 20 h. These structural changes could be related to the denaturation of the major meat components, which could explain the loss of moisture and the formation of TBARS visualized from the HSI chemical distribution maps. GC-IMS identified 35 volatile components, including hexanal and pentanal, which are also known to have a higher lipid oxidation specificity.

CONCLUSION

The synergistic application of HSI, CLSM and GC-IMS enhanced data mining and interpretation and provided a convenient way for analyzing the chemical, structural and volatile changes occurring in meat during processing. © 2021 Society of Chemical Industry.

Effect of UVC Light-Emitting Diodes on Pathogenic Bacteria and Quality Attributes of Chicken Breast

ABSTRACT

This study was conducted to investigate the inactivation of foodborne pathogens and the quality characteristics of fresh chicken breasts after UVC light-emitting diode (UVC-LED) treatment. Fresh chicken breasts were separately inoculated with Salmonella Typhimurium, Escherichia coli O157:H7, and Listeria monocytogenes at initial populations of 6.01, 5.80, and 6.22 log CFU/cm2, respectively, and then treated with UVC-LED irradiation at 1,000 to 4,000 mJ/cm2. UVC-LED irradiation inactivated the test bacteria in a dose-dependent manner. After UVC-LED treatment at 4,000 mJ/cm2, the populations of Salmonella Typhimurium, E. coli O157:H7, and L. monocytogenes on chicken breasts were decreased by 1.90, 2.25, and 2.18 log CFU/cm2, respectively. No significant changes (P > 0.05) were found in color, pH, texture, and thiobarbituric acid-reactive substances of chicken breasts following UVC-LED irradiation at doses ≤4,000 mJ/cm2. These results indicate that UVC-LED radiation is a promising technology for reducing the level of microorganisms while maintaining the physicochemical characteristics of poultry meat.

HIGHLIGHTS

Effect of chitosan coating incorporated with oregano or cinnamon essential oil on the bacterial diversity and shelf life of roast duck in modified atmosphere packaging

The present study aimed to investigate the effect of chitosan edible coating containing 0.15% oregano essential oil (OEO) or 0.60% cinnamon essential oil (CEO) on the quality characteristics and dynamic changes in the bacterial community of roast duck slices under modified atmosphere packaging (MAP, 30% CO₂/70% N₂) during 21 days of storage at 2 ± 2 °C. The results showed that the application of chitosan coating (CH) alone inhibited the growth of microorganisms and prevented lipid oxidation throughout storage. Moreover, the storage stability was further improved by including OEO or CEO, which lowered (P < 0.05) values for total viable count (TVC), Enterobacteriaceae, 2-thiobarbituric acid reactive substance (TBARS) and total volatile basic nitrogen (TVB-N). Based on the microbiological results, the shelf-life of CH-OEO and CH-CEO treated roast duck slices was prolonged by at least 7 days compared to that of the control. In addition, packaging types applied in this study played a major role in the bacterial community development. Notably, Vibrio spp. were the most predominant bacteria in all samples, when TVC values approached the shelf-life threshold, suggesting that this bacterium may be the main contributor to the spoilage of roast duck. The growth inhibition of Vibrio spp. in the CH-OEO and CH-CEO treatments during the early period of chilled storage might be the reason for the extension of the shelf life. Taken together, CH incorporated with OEO or CEO could be developed as prospective edible packaging materials to preserve roast duck meat.

Deep learning and machine vision for food processing: A survey

The quality and safety of food is an important issue to the whole society, since it is at the basis of human health, social development and stability. Ensuring food quality and safety is a complex process, and all stages of food processing must be considered, from cultivating, harvesting and storage to preparation and consumption. However, these processes are often labour-intensive. Nowadays, the development of machine vision can greatly assist researchers and industries in improving the efficiency of food processing. As a result, machine vision has been widely used in all aspects of food processing. At the same time, image processing is an important component of machine vision. Image processing can take advantage of machine learning and deep learning models to effectively identify the type and quality of food. Subsequently, follow-up design in the machine vision system can address tasks such as food grading, detecting locations of defective spots or foreign objects, and removing impurities. In this paper, we provide an overview on the traditional machine learning and deep learning methods, as well as the machine vision techniques that can be applied to the field of food processing. We present the current approaches and challenges, and the future trends.