Meat Freshness Research Articles

Development and evaluation of pH-sensitive Euryale ferox starch-based films containing nano-SiO2 and Chinese rose (Rosa chinensis) extract for freshness monitoring of chicken breast meat.

In this study, smart films of EFS, EFS-SiO2 and EFS-SiO2-CRE were successfully developed by using Euryale ferox starch (EFS), nano-SiO2 and Chinese rose extract (CRE). The Chinese rose flower had a high content of anthocyanins (1.73mg/g) and CRE exhibited different colors in varying pH buffers (2-13). The addition of nano-SiO2 decreased tensile strength (TS) (41.08 to 16.75MPa) and elongation at break (EAB) (6.71 to 2.69%) of the EFS film. Incorporation with CRE could significantly increase water vapor permeability (4.47 to 5.35 10-11gm-1s-1Pa-1), TS (16.75 to 26.19MPa) and EAB (2.69 to 4.62%) of the EFS-SiO2 film. Incorporation of nano-SiO2 and CRE significantly enhanced the thermal stability and light barrier performance of the EFS film. The EFS-SiO2-CRE films showed excellent pH and ammonia sensitivities with different colors varying from red to blue. The EFS-SiO2-CRE-III film displayed strong antioxidant activity with a maximum DPPH scavenging rate of 96.54±0.44%. When employed for monitoring freshness of chicken breast meat, the EFS-SiO2-CRE-III film showed the most significant visible color changes at 24h when the TVB-N content was 21.7mg/100g. Findings supported the application of this strategy in fabrication of the EFS-SiO2-CRE-III film for smart packaging.

Strong, tough, antibacterial, antioxidant, biodegradable multi-functional intelligent hydrogel film for real-time detection and maintenance of salmon freshness.

In this study, we prepared a new multi-functional intelligent hydrogel preservation film using soy hull nanocellulose (SHNC), polyvinyl alcohol (PVA), chitosan (CS), and anthocyanin (Anth) as raw materials. The physicochemicals of the hydrogel preservation film, and its role in monitoring the freshness and freshness of salmon was evaluated. The results showed that the monomers were crosslinked by hydrogen, ester bonds, and electrostatic interactions in the hydrogel film, and there were three-dimensional pores in the hydrogel film. Meanwhile, SHNC/PVA/CS/Anth-3 exhibited excellent mechanical properties (elongation: 345.26%; tensile strength: 26.84MPa; compressive strength: 139.27MPa) and excellent biodegradation performance. Additionally, the hydrogel film displayed excellent antioxidant and antibacterial properties (90.59%). The preservation experiment showed that, at 4°C, the hydrogel film could not only inhibit the growth and reproduction of bacteria on the surface of salmon meat, but it could also detect the freshness of salmon meat in real time, Meanwhile, the film could extend the shelf life of salmon meat from 6 d to 14 d. This study provides a new perspective for constructing a multi-functional intelligent hydrogel preservation film.

AI-Driven Non-Destructive Detection of Meat Freshness Using a Multi-Indicator Sensor Array and Smartphone Technology

AI-Driven Non-Destructive Detection of Meat Freshness Using a Multi-Indicator Sensor Array and Smartphone Technology

Combination model for freshness prediction of pork using VIS/NIR hyperspectral imaging with chemometrics.

This study aimed to develop an enhanced model for predicting pork freshness by integrating hyperspectral imaging (HSI) and chemometric analysis. A total of 30 Longissimus thoracis samples from three sows were stored under vacuum conditions at 4°C±2°C for 27 days to acquire data. The freshness prediction model for pork loin employed partial least squares regression (PLSR) with Monte Carlo data augmentation. Total bacterial count (TBC) and volatile basic nitrogen (VBN), which exhibited increases correlating with metabolite changes during storage, were designated as freshness indicators. Metabolic contents of the sample were quantified using nuclear magnetic resonance. A total of 64 metabolites were identified, with 34 and 35 showing high correlations with TBC and VBN, respectively. Lysine and malate for TBC (R2 = 0.886) and methionine and niacinamide for VBN (R2 = 0.909) were identified as the main metabolites in each indicator by Model 1. Model 2 predicted main metabolites using HSI spectral data. Model 3, which predicted freshness indicators with HSI spectral data, demonstrated high prediction coefficients; TBC R2p = 0.7220 and VBN R2p = 0.8392. Furthermore, the combination model (Model 4), utilizing HSI spectral data and predicted metabolites from Model 2 to predict freshness indicators, improved the prediction coefficients compared to Model 3; TBC R2p = 0.7583 and VBN R2p = 0.8441. Combining HSI spectral data with metabolites correlated to the meat freshness may elucidate why certain HSI spectra indicate meat freshness and prove to be more effective in predicting the freshness state of pork loin compared to using only HSI spectral data.

Recent Advances in Green Halochromic Smart Film Packaging: Investigating the Natural Colorant as Biosensor in Smart Film Packaging for Real-time Meat Freshness Monitoring

Recent Advances in Green Halochromic Smart Film Packaging: Investigating the Natural Colorant as Biosensor in Smart Film Packaging for Real-time Meat Freshness Monitoring

Novel Co-MOF-doped gelatin/agar intelligent film for beef freshness visual tracking based on the structural change of ZIF-67 under ammonia etching effect.

It is an important task to construct intelligent packaging for meat freshness monitoring with good color stability and indication function. Herein, cobalt-based metal-organic framework nanomaterials (Co-MOF, ZIF-67) with antimicrobial and ammonia-sensitive properties were successfully synthesized and added into gelatin/agar (GA) matrix to develop highly stable intelligent films (GA/ZIF67). The incorporation of ZIF-67 nanoparticles enhanced the hydrophobicity (water contact angle >90°) and UV-blocking properties (close to 0.3% at T280) of the films and endowed the films with excellent antimicrobial activity. The GA/ZIF67 films exhibited outstanding ammonia-sensitive functionality and color stability. More crucially, the ammonia-sensitive color-changing mechanism of ZIF-67 may be attributed to the slow etching effect of its crystal facets upon exposure to ammonia. With the gradual spoilage of beef, the color of the GA/ZIF67 film changes from blue-violet to gray-yellow/orange-red. In addition, the RGB value of the film collected by a mobile device App was used to quickly determine the freshness of beef, reducing individual variability in color perception. Overall, this work offers novel insights into exploring Co-MOF as a new type of indicator for developing a rapid and real-time beef freshness monitoring system, which has great potential for application in the intelligent packaging field.

Drop-on-demand printing of amine-responsive fluorescence-ratiometric sensor array for online monitoring meat freshness.

Aiming to enable online freshness-monitoring of meat within modified-atmosphere package, we developed a ratiometric array that was fluorescently responsive to volatile organic compounds-ammonia (NH3) released by protein decaying. The array was consisted of two 3mm×6mm rectangles precisely and uniformly printed with fluorescein isothiocyanate (FITC) as indicator and rhodamine B (RhB) as internal reference on the filter-paper, respectively. The fluorescence intensity of the array area was calibrated according to Green/Red ratio of the digitalized pixels extracted from images facilitated by a smartphone. The fluorescence-ratiometric sensor array displayed remarkable detection performances, including high sensitivity (LOD=1.1ppm), stability (91% responding attenuation over 10 d of storage) and reproducibility (RSD<10%), which was further validated with real pork and shrimp samples. Subsequently, the fluorescent signals of the dual-rectangle array showed high correlation to the total volatile base nitrogen value that was officially used for indexing the meat freshness status.

Machine Vision with a CMOS-Based Hyperspectral Imaging Sensor Enables Sensing Meat Freshness.

Imaging spectral information of materials and analysis of its properties have become an intriguing tool for consumer electronics used for food inspection, beauty care, etc. Those sensory physical quantities are difficult to quantify. Hyperspectral imaging cameras, which capture the figure and spectral information simultaneously, can be a good candidate for nondestructive remote sensing. In this study, with the aid of a hyperspectral imaging system (HIS) and machine learning (ML) techniques, meat freshness is converted into a measurable physical quantity, i.e., the freshness index (FI). Herein, the FI is defined as meat fluorescence, which has a strong correlation with the bacterial density. Combined with ML techniques, hyperspectral data are processed more efficiently. By employing linear discriminant and quadratic component analyses, the FI can be estimated from its decision boundary after hyperspectral data are obtained in an unknown freshness state. We demonstrate that the HIS integrated with ML performs as the artificial eye and brain, which is advanced machine vision for consumer electronics, including refrigerators and smartphones. Advanced sensing versatility utilized by computational sensing systems allows hyper-personalization and hyper-customization of human life.

Non-Targeted Metabolomics Analysis of Small Molecular Metabolites in Refrigerated Goose Breast Meat.

Poultry represents a rich source of multiple nutrients. Refrigeration is commonly employed for poultry preservation, although extended storage duration can adversely affect the meat quality. Current research on this topic has focused on the analysis of biochemical indices in chilled goose meat, with limited information on changes in metabolites that influence the quality of the meat during storage. This study used non-targeted metabolomics and the random forest algorithm to investigate metabolite changes in goose meat over an extended storage period. The results showed a significant change in the composition of the meat as the duration of storage increased, with the identification of 121 distinct metabolites. Further analysis identified 18 metabolites that could be used as indicators of the degradation of carbohydrates, amino acids, nucleotides, and lipids. These metabolites could be used as markers to monitor the deterioration process. These intermediate metabolites tended to be transformed into lower-level products involving pyruvate, acetyl coenzyme A, and fumaric acid, used in the tricarboxylic acid cycle, performing substance transformation. This comprehensive analysis of metabolites provides a valuable reference for monitoring the freshness of goose meat, potentially improving the safety of domestic poultry products.

Preparation of soybean isolate protein/xanthan gum/agar-Lycium ruthenicum anthocyanins intelligent indicator films and its application in mutton preservation.

The preparation of intelligent indicator films containing anthocyanins and their utilization for real-time monitoring of meat freshness represents a prominent research topic of food packaging. In this study, anthocyanins (ALR) were extracted from Lycium ruthenicum (LR) using solvent extraction. Subsequently, these anthocyanins were incorporated into films composed of soybean isolate protein (SPI), xanthan gum (XG) and agar, resulting in SPI/XG/Agar-ALR pH-responsive intelligent indicator films. The physical properties, structural characterization and application in mutton preservation were evaluated to identify the intelligent indicator films with the optimal addition ratio of ALR. The results indicated that the SPI/XG/Agar-5% films exhibited exceptional performance in terms of thickness, mechanical properties, water vapor transmission rate, oxygen transmission rate and light transmission rate. Scanning electron microscope observations revealed that the SPI/XG/Agar-5% films possessed a smooth and flat surface, while fourier transform infrared spectroscopy analysis confirmed their excellent compatibility. The DPPH radical scavenging rate of the SPI/XG/Agar-5% film reached 80.75±0.63%. When applied to the preservation of mutton, the SPI/XG/Agar-5% film significantly extended the shelf life and effectively monitored the freshness of the meat. This study not only broadens the application scope of Lycium ruthenicum anthocyanins but also provides a foundation for the development of smart packaging materials.

Precisive designing and drop-on-demand printing of spoilage-responsive colorimetric sensor array for intelligent food package

Precisive designing and drop-on-demand printing of spoilage-responsive colorimetric sensor array for intelligent food package

Amine-responsive PVA-based fluorescent indicator films incorporating β-Glucan/FITC for visual detection of chilled meat freshness

Amine-responsive PVA-based fluorescent indicator films incorporating β-Glucan/FITC for visual detection of chilled meat freshness

Highly selective dual-signal readout H2S probe: Applications in monitoring of water samples, food spoilage and live cell imaging

We present a new probe (DN) for colorimetric and fluorimetric detecting hydrogen sulfide (H2S) on the basis of the H2S-triggered thiolysis of 4-nitro-2,1,3-benzoxadiazoyl (NBD) ether. In H2O/DMSO medium (9/1, v/v, pH 7.4), the aryl ether bond in DN was cleaved by H2S via nucleophilic aromatic substitution to yield a phenolate product with lighting up red fluorescence accompanied with a distinguished color transformation from yellow to pink. Probe DN features near-infrared emission (660nm), large Stokes Shift (168nm), good sensitivity (LOD: 15.1nM) and relative fast response time (5min) for specific sensing of H2S. Conveniently, a paper strips-based test kit was developed for tracking and assessing meat freshness by monitoring the release of H2S. What is more, DN is demonstrated to image both exogenous and endogenous H2S in live cells with relative short analysis time (30-60min), providing a new research tool for exploring the relationship between H2S and clinical diseases.

Engineering a shellfish-inspired bio-based double-layered smart packaging material with enhanced water resistance and barrier performance for universally applicable meat freshness monitoring

Engineering a shellfish-inspired bio-based double-layered smart packaging material with enhanced water resistance and barrier performance for universally applicable meat freshness monitoring

Bi-MOF-based point-of-care testing paper for dual-mode detection of H2S

Hydrogen sulfide (H2S) is noxious gas and significantly threatens human health. Herein, a Bi-based metal-organic frameworks (Bi-MOFs) based paper analysis device (PAD) has been developed for rapid and effective dual-mode detection of H2S. The dominant H2S sensing mechanism is explored. The H2S can react with Bi-MOF to form bismuth sulfide (Bi2S3) MOF (Bi2S3-MOF), changing the color of PAD from white to black. The distinguish color change makes it very convenience for visible detection. Meanwhile, the generated Bi2S3-MOF exhibits excellent photothermal property, endowing it possible for photothermal imaging detection. In this regard, the PAD boasts a wide linear detection range of 0-40μM for H2S with an impressively low limit of detection (LOD) (0.23μM). The constructed sensing system is demonstrated with outstanding selectivity and storage stability. Satisfied recovery is reached for H2S detection in diverse real samples. Interestingly, the PAD can be used as intelligent label for assessing meat freshness by monitor H2S release from meat under different storage temperatures. With integration capabilities of smartphones, the portable and user-friendly PAD offers a simple and rapid solution for on-the-go detection of H2S in food and environment. The investigation provides an instructive way for environment monitoring and food safety guarding.

Starch-pectin smart tag containing purple carrot peel anthocyanins as a potential indicator of analogous meat freshness

Smart films of starch/pectin and purple carrot peel (PCP) containing anthocyanins were developed, characterized, and used as pH-responsive tags to monitor plant-based chicken analogous. This study innovates by incorporating PCP in the film solution both as an extract and as a powder, and the resulting tags were applied to a plant-based food. PCP powder <100-mesh was directly incorporated into the film-forming suspension. For powder >100-mesh, two extracts were tested: an aqueous solution and a 1% NADES solution added to the film-forming suspension. Quantification of PCP anthocyanins by HPLC showed a higher extraction under acidic conditions (1664mg C3G equivalents 100g-1). Films with PCP presented greater light protection. Films with 15% and 25% PCP and those with added extract showed better tensile strength (3.0-3.6MPa), elongation at break (16-20%) and a water contact angle of 52°. All films responded to pH variations (1 to 14) and ammonia vapor and showed ΔE* values >5. After 3days, films used as smart tags monitoring chicken analogous presented noticeable color differences for PCPNADES (55±8) and 15%PCP (40±1). PCP showed strong potential as a pigmenting agent in films, especially as an aqueous extract with NADES for use as pH-responsive tags in chicken analogous.

Effect of marination time using vacuum marinator and calcium chloride on physicochemical quality of beef

Abstract Beef products contribute to long-term food security in Indonesia. The use of processing technology to maintain beef quality, as well as food additives, can extend the shelf life and maintain meat freshness. This study focused on marination time using vacuum marinators and Calcium chloride on the physicochemical quality of beef. The experimental method with a completely randomised design pattern with 4 treatments and 5 replications was used in this study. The treatment given was marination time using Calcium chloride at a dose of 250 mM on 100 g of beef using a vacuum marinator (V0 = no marination, V1 = 15 minutes, V2 = 30 minutes, and V3 = 45 minutes). Marination time with a vacuum marinator and the use of Calcium chloride had significant effects (P&lt;0.05) on pH, cooking loss, moisture content, and tenderness but had no significant impact (P&gt;0.05) on beef colour change. Marination time using a vacuum marinator and Calcium chloride can increase pH, moisture content, and tenderness and decrease the cooking loss of beef. The best physicochemical quality is the beef sample, which was marinated for 30 minutes (V2) using a vacuum marinator and Calcium chloride, which can be used sustainably.

Monitoring Meat Freshness with Intelligent Colorimetric Labels Containing Red Cabbage Anthocyanins Copigmented with Gelatin and Gallic Acid.

Polyvinyl alcohol (PVA)-based pH-responsive color indicators were developed using red cabbage anthocyanin (Anth) copigmented with gelatin and gallic acid (GA). The indicator prepared with gelatin and GA (GA/gelatin/Anth/PVA) was highly resistant to light exposure. GA/gelatin/Anth/PVA exhibited distinct color changes in pH 2-11 buffer solutions and stable color indication in acidic and neutral solid systems (pH 2 and 7) at 97% relative humidity. GA/gelatin/Anth/PVA exhibited the highest sensitivity to dimethylamine, followed by ammonia and trimethylamine. The addition of gelatin and GA facilitated hydrogen bonding, which enhanced thermal stability and water solubility without compromising tensile properties. A color change from purple to blue signaled spoilage when total volatile basic nitrogen values for beef and squid reached 21.0 and 37.8 mg/100 g, respectively. The GA/gelatin/Anth/PVA indicator shows potential for indicating the freshness of raw beef.

Development of a mobile application for rapid detection of meat freshness using deep learning

The freshness or spoilage of meat is critical in terms of meat color and quality criteria. Detecting the condition of the meat is important not only for consumers but also for the processing of the meat itself. Meat quality is influenced by various pre-slaughter factors including housing conditions, diet, age, genetic background, environmental temperature, and stress factors. Additionally, spoilage can occur due to the slaughtering process, though post-slaughter spoilage is more frequent and has a stronger correlation with postslaughter factors. The primary indicator of meat quality is the pH value, which can be high or low. Variations in pH values can lead to adverse effects in the final product such as color defects, microbial issues, short shelf life, reduced quality, and consumer complaints. Many of these characteristics are visible components of quality. This study aimed to develop a mobile application using deep learning-based image processing techniques for the rapid detection of freshness. The attributes of the source and the targeted predictions were found satisfactory, indicating that further advancements could be made in developing future versions of the application.

Performance evaluation of machine learning algorithms for meat freshness assessment

Performance evaluation of machine learning algorithms for meat freshness assessment