Freshness Index Research Articles

PH-Responsive strips integrated with resazurin and carbon dots for monitoring shrimp freshness

Carbon dots (CDs) were synthesized via a one-step hydrothermal approach using tangerine peel (Tan) and resazurin (Res) to fabricate biocompatible indicators for food freshness. The CDs' pH-responsive mechanism, morphology, zeta potential, XPS, and optical and fluorescence analysis were investigated. The as-prepared tangerine peel/resazurin carbon dots (Tan/Res CDs) exhibited pH-responsive emission that changed from yellow to orange as the pH value increased. The Tan/Res CDs showed the sensing ability of ammonia with a detection limit of 0.84 μM by proportionally losing fluorescence intensity as the concentration increased from 1 to 100 μM. The CDs were coated onto paper strips to impart biogenic amine (BAs) detection for pH-responsive intelligent monitoring of packaged foods. The Tan/Res CDs paper-based indicator exhibited an impressive color change from yellow to brown during the detection of ammonia vapor. The indicator also showed the ability to detect BAs through a color change, demonstrating the ability to monitor the freshness of shrimp in situ. Additionally, the efficacy of the Tan/Res CDs indicator is validated by total volatile basic nitrogen (TVB-N), providing customers and suppliers with a simple, inexpensive, and portable tool to monitor the freshness of seafood in real-time.

Application of bacterial nanocellulose decorated with zeolitic imidazolate framework (ZIF-L) as a platform for food freshness monitoring

Recently, the food freshness indicator (FFI) has garnered great interest from consumers and food producers. A novel FFI based on bacterial nanocellulose (BNC)/zeolitic imidazolate framework-L (ZIF-L) and grape anthocyanins was developed and characterized using field emission scanning electron microscopy, Fourier-transform infrared, X-ray diffraction, water contact angle, and BET techniques. The results confirmed that the BNC fibrils were decorated by in situ growth of ZIF-L, with a 3D flower-shaped structure and randomly multiple sharp-edged petals, and hydroxyl and oxygenated heterocycle aromatic ring functional groups on its surface. The reversibility, color stability performance, and moisture sorption of FFI were studied and its applicability in a two-layer arrangement as a visual freshness monitoring of shrimp and minced beef was evaluated. The FFI was able to distinguish (ΔE > 5) the fresh, medium fresh, and spoiled minced meat and shrimp visually during 10 and 4 days of storage at 4 °C, respectively. Also, monitoring of food chemical and microbiological parameters approved the correlation of food spoilage with the color parameters of FFI. These results confirmed the function of ZIF-L in the fabrication of highly pH-sensitive food intelligent packaging material.

A pattern-free paper enzyme biosensor for one-step detection of fish freshness indicator hypoxanthine with a microfluidic aggregation effect

In this study, a paper-based enzyme biosensor for hypoxanthine (Hx) was developed, enabling visual and one-step fish freshness detection. Xanthine oxidase and horseradish peroxidase were immobilized on nitrocellulose membranes with 3,3′,5,5′-tetramethylbenzidine to output the colour signal. Chitosan oligosaccharide lactate-modified nitrocellulose membranes entrapped the dual-enzyme system and exhibited excellent microfluidic aggregation effect. The developed enzyme biosensor produced a linear response of 0.01–0.16 mmolL-1 with a detection limit of 8.22 μmolL-1, and was selective for Hx with recoveries of 96.13–103.11 % for fish samples. These biosensors were attached directly to the surface of fish samples and the colour was revealed within 3 min. Colour signals can be judged by the naked-eye to distinguish between fresh and spoiled fish samples and analyzed by a smartphone for quantitative analysis. The biosensor shows great potential as a powerful pattern- and reagent-free device for on-site freshness evaluation of fish.

Targeted deletion of ecto-5′-nucleotidase results in retention of inosine monophosphate content in postmortem muscle of medaka (Oryzias latipes)

Inosine monophosphate (IMP) is an important indicator of meat freshness and contributes to its umami taste. An attractive strategy for enhancing umami is to suppress the IMP-degrading activity and increase the IMP content in the skeletal muscle through genome editing technology using the CRISPR-Cas9 system. However, the molecular mechanisms underlying IMP degradation remain unclear. We cloned two ecto-5′-nucleotidase genes, designated as ecto-5′-nucleotidase-a (nt5ea) and ecto-5′-nucleotidase-b (nt5eb), from medaka (Oryzias latipes), a vertebrate model organism. Expression analysis using embryos showed that nt5ea or nt5eb overexpression remarkably upregulated IMP degradation, and that the IMP-degrading activity was higher in Nt5ea than in Nt5eb. Furthermore, we established frame-shifted or large deletion (lacking nt5ea or nt5eb locus) mutant strains and assayed the effects of gene disruptions on the amount of IMP in skeletal muscle. The nt5ea-deficient medaka showed considerable higher levels of IMP at 48 h postmortem than did the wild-type fish. The nt5eb mutants also exhibited higher IMP contents than that in the wild types, but the increase was less than that in the nt5ea mutants. Our results demonstrated that nt5e is an important regulator of IMP levels in skeletal muscle and that its loss of function was effective in maintaining IMP content.

A Smartphone Coupled Freshness Indicator Prepared by Rub‐coating of Hibiscus Flowers on Paper substrates for Visual Monitoring of the Spoilage of Milk

AbstractThis study developed an inexpensive and easy‐to‐use milk freshness indicator (H‐Paper) by rub‐coating hibiscus flowers onto paper. As per the best of our knowledge, this is the first example of a food quality indicator prepared by direct hand‐rubbing of a natural halochromic material onto paper substrates. Unlike the previously reported colorimetric indicators from natural sources, our indicator does not require the extraction of anthocyanins from the natural product. The H‐Paper undergoes a quantifiable color change from green to purple to pink corresponding to fresh, spoiling, and spoiled milk samples. Digital photographs of H‐Paper treated with milk samples were acquired using a smartphone, and RGB indices were analyzed using a free application. The red chromatic shift was used as a parameter to quantify color change of H‐Paper to follow the spoilage of milk. Anthocyanins present in the hibiscus flowers are responsible for this colorimetric response. This work demonstrates a proof‐of‐concept for directly rub‐coating halochromic materials onto a substrate to fabricate food freshness indicators. The H‐Paper indicator has advantages of naked‐eye analysis, consumer‐friendliness, and instrument‐free operation. This requires neither any laboratory accessories nor the expertise of a trained analyst for its preparation and operation, which is appropriate for use in resource‐limited settings.

The affect of some natural preservative solutions and immersion time on the quality of chrysanthemum cut flowers (Chrysantemum morifolium L.)

Chrysanthemum morifolium L. is one of the ornamental plants that has problems in maintaining the freshness of the flower. The handling given to maintain the shelf life of the flower is to soak the flowers with a natural preservative solution. This study aims to find out the effect of several types of natural preservative solutions and long soaking on the quality of freshness of chrysanthemum cut flowers, as well as to find out whether there is an interaction between the two treatments. This research was conducted at the Laboratory of Seed Science and Technology and Horticulture Laboratory of the Department of Agrotechnology, Faculty of Agriculture, University of Syiah Kuala, Banda Aceh from March 30 to April 15, 2021. The study used a Complete Randomized Design of a 4 x 3 Factorial pattern with 3 repeats. The parameters observed include the diameter of the full blooming flower, the flower's ness index, the flower freshness period index, total absorbed solution, color measurement and organoleptic test. The results showed that the combination of treatment between natural and long-soaked solution types had a real effect on the parameters of the flower freshness index. The best freshness period of flowers is in the combination of 10% sugar solution type treatment with a 6-hour soaking length.

Polyphenol-loaded bacterial cellulose nanofiber as a green indicator for fish spoilage

Seafood products as a source of vitamins, minerals, and polyunsaturated fatty acids represent an important component of the human diet. However, they are susceptible to spoilage even under appropriate storage conditions, making it indispensable to develop freshness indicators. In this study, we introduce a green user-friendly pH indicator film for the naked-eye monitoring of fish spoilage. The pH indicator was prepared by successful loading of a mixture of anthocyanin and curcumin on bacterial cellulose (BC) nanofiber substrate. BC nanofiber with the advantages of biocompatibility, biodegradability, high purity, and superior mechanical strength was promising for generating pH-sensing arrays. The Fourier transform infrared (FT-IR) analysis proved the incorporation of anthocyanin and curcumin into the BC skeleton. Besides, the scanning electron microscopy (SEM) results clarified the morphology of the modified film by anthocyanin and curcumin. The pH indicator film was still stable after preserving for 60 days at different temperatures. The curcumin-anthocyanin loaded nanofiber indicated a distinct color change after spoilage by its exposure to fish meat in a transparent plastic package. Hence, the modified film by the anthocyanin-curcumin mixture is potent for the naked-eye monitoring of meat spoilage.

Nondestructive detection of S‐ovalbumin content in eggs using portable NIR spectrometer and MPA‐CARS

AbstractThe feasibility of applying a low‐cost and portable NIR spectrometer to detect the S‐ovalbumin content of eggs was investigated in this study, and a model population analysis based competitive adaptive reweighted sampling (MPA‐CARS) algorithm was proposed to reduce the dimensionality of spectral data. The NIR spectra of egg samples with different storage periods were collected in the wavelength range of 900–1700 nm. Standard normal variate (SNV) and Savitzky–Golay1st derivative were used to preprocess the raw spectral data. Then, CARS and the proposed MPA‐CARS were applied to select effective wavelengths from the whole spectral range. Statistical results showed that MPA‐CARS had better feature extraction performance than CARS and the number of selected feature wavelengths was less. Support vector machine (SVM), back propagation neural network (BPNN) and extreme gradient boosting (XGBoost) were used to establish calibration models for predicting S‐ovalbumin content, in which the simplified XGBoost model based on MPA‐CARS feature wavelengths yielded the best performance, with R2P of 0.906 and RMSEP of 7.799%. Therefore, portable NIR has the potential to be a useful tool for S‐ovalbumin content detection. This could help food processing industry to arrange miniaturized NIR sensors to detect egg quality at different points in the egg supply chain.Practical applicationsS‐ovalbumin content is a freshness index of eggs and can affect the quality of processed foods. This study demonstrated the feasibility of using portable NIR spectrometer to detect the S‐ovalbumin content of eggs, which can help food processing agencies to implement low‐cost NIR sensors to detect egg quality at different stages of the supply chain.

Visualization research of egg freshness based on hyperspectral imaging and binary competitive adaptive reweighted sampling

Freshness is an important indicator for evaluating egg quality and is crucial for the food processing industry and consumers. The aim of this study is to non-destructively detect and visualize the freshness of eggs during storage by using hyperspectral imaging (HSI) and multivariate analysis. The hyperspectral images of egg samples with different storage time were collected in the spectral range of 401–1002 nm. A binary competitive adaptive reweighted sampling (BCARS) algorithm considering the synergetic effect among variables was proposed to select feature wavelengths from the whole spectral range and compared with competitive adaptive reweighted sampling (CARS). A slime mould algorithm optimized support vector regression (SMA-SVR) model was proposed to develop calibration models for HU (egg freshness indicator). Statistical analysis results indicated that the proposed BCARS had better feature extraction performance than CARS and the SMA-SVR model outperformed the compared models, in which the BCARS-SMA-SVR model yielded the best performance with a determination coefficient (R2) of 0.946 for calibration set and 0.914 for prediction set. Finally, by transferring the quantitative model to each pixel of hyperspectral image, the visualizing distribution map of HU was generated, providing an intuitive evaluation for egg freshness, which facilitates to the management of storage and marketing. The results provided the possibility of implementing a multispectral imaging for online monitoring of egg quality.

Cellulose nanofiber mediated natural dye based biodegradable bag with freshness indicator for packaging of meat and fish

This work reports the development of a biodegradable bag with freshness detection property for packaging of fish and meat. A nanocomposite film was prepared using cellulose nanofibers and cellulose acetate. Cellulose nanofibers were synthesized from cellulosic materials extracted from grass. Naturally occurring anthocyanin was introduced to activate the film for ammonia detection. Anthocyanin was extracted from the seeds of a dye bearing plant called Melastoma Malabathricum. Presence of cellulose nanofibers facilitates the absorption of anthocyanin on the film surface. The inherent property of colour changing ability with the change in pH, anthocyanin converts the film into a sensor for ammonia vapour. This colour change ability of the films was characterised using a colour measurement instrument. The film showed a tensile strength of ⁓29 MPa and thermal stability ⁓288 °C. Utilizing the thermoplastic nature of cellulose acetate, such films could be easily converted to a packaging bag by heat sealing.

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 R2 = 0.81 (group A) and R2 = 0.87 (group B) for MetMb and R2 = 0.80 (group A) and R2 = 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.

ZnO-based chemi-resistive sensors for CO2 detection: a review

PurposeCarbon dioxide (CO2) has attracted special scientific interest over the last years mainly because of its relation to climate change and indoor air quality. Except for this, CO2 can be used as an indicator of food freshness, patients’ clinical state and fire detection. Therefore, the accurate monitoring and controlling of CO2 levels are imperative. The development of highly sensitive, selective and reliable sensors that can efficiently distinguish CO2 in various conditions of temperature, humidity and other gases’ interference is the subject of intensive research with chemi-resistive zinc oxide (ZnO)-based sensors holding a privileged position. Several ZnO nanostructures have been used in sensing applications because of their versatile features. However, the deficient selectivity and long-term stability remain major concerns, especially when operating at room temperature. This study aims to encompass an extensive study of CO2 chemi-resistive sensors based on ZnO, introducing the most significant advances of recent years and the best strategies for enhancing ZnO sensing properties.Design/methodology/approachAn overview of the different ZnO nanostructures used for CO2 sensing and their synthesis methods is presented, focusing on the parameters that highly affect the sensing mechanism and, thus, the performance of CO2 sensors.FindingsThe selectivity and sensitivity of ZnO sensors can be enhanced by adjusting various parameters during their synthesis and by doping or treating ZnO with suitable materials.Originality/valueThis paper summarises the advances in the rapidly evolving field of CO2 sensing by ZnO sensors and provides research directions for optimised sensors in the future.

Intelligent films based on pectin, sodium alginate, cellulose nanocrystals, and anthocyanins for monitoring food freshness

To address consumer-level food waste, and pollution from commercial plastics, we developed intelligent films using sodium alginate (SA), pectin (PC), cellulose nanocrystals (CNCs), and anthocyanins extracted from red cabbage (RCA). We also investigated two methods of reinforcing these films – cross-linking (CL), and the addition of CNCs. Both together and separately, these methods improved SA/PC films’ mechanical properties and thermal stability. The optimal SA/PC/CNCs/RCA/CL films exhibited pH-dependent color-response properties and high water resistance. These were then tested as colorimetric freshness indicators for shrimp samples, both through seepage and the monitoring of volatile compounds. The colors of the indicators changed from lilac to dark green to greenish-yellow after storage at 25 °C for 72 h, whereas at 4 °C, they changed much more slowly over the same time period. This demonstrated the excellent potential of such films to reduce food waste by providing real-time warnings of pH variation resulting from spoilage.

Effects of hot or cold boning on the freshness and bacterial community changes of lamb cuts during chilled storage

Deboning methods are vital during fresh meat processing, influencing the evolution of spoilage. In this study, we examined the effects of deboning methods (including hot boning (HB), conventional chilling and boning (CCB) and very fast chilling and boning (VFCB)) on freshness and bacterial changes of lamb cuts stored at 4 °C. The freshness of lamb was evaluated by total volatile basic nitrogen (TVB-N), thiobarbituric acid reactive substances (TBARS), total viable count mesophilic (TVCm) and total viable count psychrophilic (TVCp), and the bacterial community was determined by 16S rRNA high-throughput sequencing. The results showed basically no significant difference in the freshness indicators between HB and CCB lamb, and those of VFCB lamb were significantly lower than HB and CCB lamb except TBARS. In the early and mid storage, Pseudomonas and Ralstonia were dominant in HB lamb and norank_f_Mitochondria was dominant in CCB and VFCB lamb. In the end of storage, Pseudomonas was dominant in all lambs. Furthermore, the nutrient metabolism and some pathways potentially involved in cellular interaction might be prominent during lamb spoilage. Our work can provide information for delaying spoilage and supporting the high-quality development of raw lamb.

Enzymatic determination of hypoxanthine in fish samples as a freshness indicator using the CUPRAC colorimetric sensor

Fish consumption is essential for a healthy diet. However, all seafood including fish are susceptible to deterioration unless properly preserved. Controlling the freshness of fresh or packaged fish is a challenging issue for the food industry in terms of human health and shelf life determination. One of the main indicators showing the freshness of fish is undoubtedly the amount of hypoxanthine (Hx). As soon as the organism dies, Hx begins to be released with the cessation of ATP synthesis and shows a gradual increase over time. Therefore, Hx determination is an important indicator in the control of fish freshness. Based on this fact, a colorimetric method for the enzymatic determination of Hx using the CUPRAC (Cupric ion Reducing Antioxidant Capacity) sensor was developed. Uric acid (UA) and H2O2 are enzymatically produced by xanthine oxidase (XOD) from Hx, and both products respond to the CUPRAC reagent to produce the cuprous neocuproine (Cu(I)-Nc) chromophore chelate formed in situ on a Nafion anionic membrane on which the cationic Cu(II)-Nc complex was fixed. Hx was measured at different time intervals in the meat samples taken from sea bass (Dicentrarchus labrax), which was left to stand at room temperature for a time period between 0 and 24 h; the level of spoilage was determined from the coloration of the CUPRAC membrane sensor (via absorbance measurement at 450 nm). It was observed that there was a linear increase in the amount of Hx during the measurement period. The method was optimized for Hx determination, verified with interference analysis and standard additions to real samples, and validated against HPLC. The linear detection range of the developed method for Hx was 2.0–32.0 μM with an LOD of 0.79 μM, and early stages of fish degradation could be detected at several nanomoles of Hx per gram of fish meat. The proposed method was demonstrated to have distinct superiority over many recent colorimetric sensors of fish freshness in regard to its lower LOD for Hx, wider linear range, capability to cope with interferents (including biologically important antioxidants, such as cysteine, reduced glutathione, ascorbic acid, UA and α-tocopherol) and applicability to real samples.

Monitoring the freshness of pork during storage via near-infrared spectroscopy based on colorimetric sensor array coupled with efficient multivariable calibration

The quality of pork meat is vital since it is one of the most essential sources of proteins and other nutrients. Near-infrared spectroscopy via colorimetric sensor array (NIRS-CSA) technology as a novel approach combined with multivariate calibrations was proposed to quantitatively evaluate total volatile basic nitrogen (TVB-N) as an indicator of freshness in pork. Using nine chemoselective dyes, the CSA was initially fabricated. The synergy interval-partial least squares (Si-PLS) was applied to select optimum variable intervals. Thereafter, different variable selection algorithms were executed, evaluated and compared. By utilizing 61 variables (7.73% of the Si-PLS variables), the synergy interval- competitive adaptive reweighted sampling-partial least squares (Si-CARS-PLS) model yielded preeminent performance with Rp = 0.9850, RMSEP = 0.7148, and RPD = 6.00. Therefore, this study discovered that combining NIRS-CSA with Si-CARS-PLS as efficient variable selection algorithm could be employed as a fast and cheap strategy for assessing the freshness of pork meat during storage. • The colorimetric sensor array was fabricated using nine chemically sensitive dyes. • TVB-N was satisfactorily measured and predicted by the NIRS-CSA. • The different variables selection based PLS improved modeling performances. • The Si-CARS-PLS model was optimum for TVB-N prediction.

Post-harvest quality changes and shelf-life determination of washed and blanched sugar kelp (Saccharina latissima)

Sugar kelp (Saccharina latissima) is a native European brown macroalga with the potential to become a vital part of the green transition of the food industry. Knowledge of the sugar kelp shelf-life is essential to designing the food supply chain to ensure safe and high-quality food. Establishing a single-compound quality index (SCQI) of freshness would be useful for the industry. However, information is currently lacking on how different post-harvest treatments affect the shelf-life of sugar kelp, even though it is important knowledge for manufacturers, authorities and consumers. The objective of this study was to establish the shelf-life of refrigerated sugar kelp following five post-harvest treatments and evaluate the effect of these treatments on changes in quality attributes (sensory, microbial, chemical and physical) during storage to select the SCQI. The post-harvest treatments included washing in sea water, washing in potable water, blanching for 2 min in sea water or potable water and untreated sugar kelp. Based on sensory analysis, the refrigerated (+ 2.8°C) shelf-lives for sugar kelp from all treatments were seven to 9 days. The end of the sensory shelf-life correlated with the development of >7 log (CFU g−1) aerobic viable counts, suggesting this attribute can be used as a SCQI to evaluate the shelf-life of sugar kelp. The microbiota was dominated by putative spoilage organisms from the Pseudoalteromonadaceae and Psychromonadaceae families. Untreated and washed sugar kelp continued to respire and consume carbohydrates up to 5 days post-harvest, indicating respiration rates may be used to determine freshness of non-blanched kelp. Favorable organoleptic properties, e.g., sweetness and umami, decreased during storage and coincided with a reduction in water-soluble mannitol and free glutamic acid. Both blanching treatments changed texture and color and reduced iodine and vitamin C contents while retaining components such as fucoxanthin, chlorophyll a and β-carotene. This study provides crucial documentation of quality changes during the post-harvest storage period of sugar kelp, including information about sugar kelp spoilage and nutrient changes, which would facilitate the development of best practices for manufacturers using sugar kelp in their production of food.

Low-Cost Nonreversible Electronic-Free Wireless pH Sensor for Spoilage Detection in Packaged Meat Products.

Contamination of meat with pathogenic microorganisms can cause severe illnesses and food waste, which has significant negative impacts on both general health and the economy. In many cases, the expiration date is not a good indicator of meat freshness as there is a high risk of contamination during handling throughout the supply chain. Many biomarkers, including color, odor, pH, temperature, and volatile compounds, are used to determine spoilage. Among these, pH presents a simple and effective biomarker directly linked to the overgrowth of bacteria and degradation of the meat tissue. Low-cost methods for wireless pH monitoring are crucial in detecting spoilage on a large commercial scale. Existing technologies are often limited to short-range detection, with the use of batteries and different electronic components that increases both the manufacturing complexity and cost of the final device. To address these shortcomings, we have developed a cost-effective wireless pH sensor, which uses passive resonant frequency (RF) sensing, combined with a pH-responsive polymer that can be placed within packaged meat products and provide a remote assessment of the risk of microbial spoilage throughout the supply chain. The sensor tag consists of a sensing resonator coated with a pH-sensitive material and a passivated reference resonator operating in a differential frequency configuration. Upon exposure to elevated pH levels >6.8, the coating on the sensing resonator dissolves, which in turn results in a distinct change in the resonant frequency with respect to the reference resonator. Systematic theoretical and experimental results at different pH levels demonstrated that a 20% shift in resonant frequency demarcates the point for spoilage detection. As a proof of concept, the performance of the sensor in remotely detecting the risk of food spoilage was validated in packaged poultry over 10 days. The sensor fabrication process takes advantage of recent developments in the scalable manufacturing of flexible, low-cost devices, including selective laser etching of metalized plastic films and doctor-blade coating of stimuli-responsive polymer films. Furthermore, the biocompatibility of all the materials used in the sensor was confirmed with human intestinal cells (HCT-8 cells).

An improved ratiometric fluorescent tag based on aggregation-induced emission luminogen for in-situ monitoring of seafood freshness

Volatile basic nitrogens (VBNs) are an important indicator of food freshness. In this work, a novel ratiometric fluorescent sensor was developed. The sensor used blue-green fluorescent N-acetyl-L-cysteine capped silver nanoclusters (NAC-AgNCs) as an indicator and red-orange fluorescent glutathione capped gold nanoclusters (GSH-AuNCs) as an internal reference. With biogenic amines as model targets, results showed that the sensor was sensitive to VBNs with a limit of detection of 3.85 μM and 6.75 μM for spermidine and spermine, respectively. Based on these findings, a ratiometric fluorescent tag was further prepared and applied as a gas sensor for ammonia vapour monitoring, which was employed and validated to monitor the freshness of raw shrimp at different storage temperatures (4 and 25 °C). For all we know, this is the first ratiometric fluorescent tag based on metal nanoclusters with aggregation-induced emission properties for monitoring seafood freshness.

Prediction of the freshness of horse mackerel (Trachurus japonicus) using E-nose, E-tongue, and colorimeter based on biochemical indexes analyzed during frozen storage of whole fish

Electronic nose (E-nose), electronic tongue (E-tongue) and colorimeter combined with data fusion strategy and different machine learning algorithms (artificial neural network, ANN; extreme gradient boosting, XGBoost; random forest regression, RFR; support vector regression, SVR) were applied to quantitatively assess and predict the freshness of horse mackerel (Trachurus japonicus) during the 90-day frozen storage. The results showed that the fusion data of the E-nose, E-tongue and colorimeter could contain more information (with a total variance contribution rate of 94.734 %) than that of the independent one. ANN, RFR and XGBoost showed good performance in predicting biochemical indexes with the RP2 (the square correlation coefficient of the Test set) ≥ 0.929, 0.936, 0.888, respectively, while SVR models showed a bad performance (RP2 ≤ 0.835). In addition, among the established quantitative models, the RFR model had the best prediction effect on K value (freshness index) with Rp2 of 0.936, ANN model had the highest fitting degree in predicting carbonyl content (protein oxidation degree) with Rp2 of 0.978, XGBoost model had the best performance in predicting the TBA value (lipid oxidation degree) with Rp2 of 0.994, RFR model was the best strategy for predicting Ca2+-ATPase activity (protein denaturation degree) with Rp2 of 0.969. The results demonstrated that the freshness of frozen fish can be effectively evaluated and predicted by the combination of electronic sensor fusion signals.