Assessment and Prediction of Fish Freshness Using Mathematical Modelling: A Review

Research Progress of Machine Learning in Extending and Regulating the Shelf Life of Fruits and Vegetables

Fruits and vegetables are valued for their flavor and high nutritional content, but their perishability and seasonality present challenges for storage and marketing. To address these, it is essential to accurately monitor their quality and predict shelf life. Unlike traditional methods, machine learning efficiently handles large datasets, identifies complex patterns, and builds predictive models to estimate food shelf life. These models can be continuously refined with new data, improving accuracy and robustness over time. This article discusses key machine learning methods for predicting shelf life and quality control of fruits and vegetables, with a focus on storage conditions, physicochemical properties, and non-destructive testing. It emphasizes advances such as dataset expansion, model optimization, multi-model fusion, and integration of deep learning and non-destructive testing. These developments aim to reduce resource waste, provide theoretical basis and technical guidance for the formation of modern intelligent agricultural supply chains, promote sustainable green development of the food industry, and foster interdisciplinary integration in the field of artificial intelligence.

Drivers in the fisheries domain: A bibliometric and text mining analysis

Fisheries have garnered attention from researchers throughout the last several decades. This sector's contribution has been recognised globally, leading to exponential growth in the number of research studies published in this area. Among all the dimensions from which this field has been explored, a critical theme under focus has been the drivers in the fisheries domain. Therefore, this study aims to provide a wholesome view of such studies that have explored drivers in the context of fisheries using bibliometric analysis and text-mining tools. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, 322 studies on the theme were extracted from the Scopus and Web of Science databases. The studies extracted were analysed using VOSviewer and Orange software. The analysis uncovered the top journals and publishers in this domain and revealed the hidden patterns in the existing literature. The researchers posit that rather than judging the growth solely based on the number of citations and publications over the period, focus should be concentrated towards identifying themes that have gained immense attention from researchers over the years. The results indicate a shifting trend in recent times, centered on topics related to sustainability and climate change, among many more. The findings have important implications for researchers to make valuable contributions in this domain.

Microbiological quality assessment of Clarias gariepinus, Bagrus bajad, and Pangasianodon hypophthalmus fillets

In this study, 80 catfish fillets were randomly collected from Egyptian local markets and retailers. The samples included 20 African catfish (Clarias gariepinus), 20 bayad (Bagrus bajad), and 40 pangasius catfish (Pangasianodon hypophthalmus) fillets. Pangasianodon hypophthalmus fillet samples were divided into 20 white basa and 20 red basa fillets. We conducted a microbiological analysis of catfish fillet samples, evaluating mesophilic aerobic bacteria, psychrophilic aerobic bacteria, H2S-producing bacteria, Staphylococcus spp., Enterobacteriaceae, Coliforms, and fecal Coliform counts. Additionally, we identified the existence of Salmonella spp., Vibrio spp., Yersinia spp., Escherichia spp., Aeromonas spp., and Pseudomonas spp. in the catfish fillet samples. In our study, the psychrophilic bacterial counts in Bagrus bajad (5.21 log CFU/g) were found to be higher compared to the counts in Clarias gariepinus (4.31 log CFU/g) and Pangasianodon hypophthalmus (3.89-4.7 log CFU/g). The fecal Coliform in Clarias gariepinus fillets was significantly higher than in other catfish fillets. We isolated Escherichia coli, Escherichia fergusonii, Aeromonas hydrophila, and Pseudomonas luteola from the catfish fillets, while no Salmonella spp., Vibrio spp., or Yersinia spp. were detected. These isolates were identified using 16S rRNA sequencing and phylogenetic analysis. Furthermore, ten Escherichia spp. were serologically identified, revealing that O26 and O78 were the most commonly occurring serotypes. This study highlights the microbiological analysis conducted on catfish fillets and concludes that the fillet samples from these catfish were of superior quality and deemed acceptable for human consumption.

Bacterial cellulose/gelatin-based pH-responsive functional film for food freshness monitoring

Food safety is related to public health and environmental safety. Therefore, it is necessary to develop accurate and effective detection methods to assess food quality and safety. In this study, a pH-responsive functional film (BC/GA/FITC/PCA) was generated for the real-time and visual monitoring of shrimp freshness. Bacterial cellulose /Gelatin (BC/GA) was used as a film-forming matrix, and fluorescein isothiocyanate (FITC) and red cabbage (PCA) were used as the response signals. The addition of FITC and PCA increased the shading capacity (< 30 %) and antioxidant properties (22.8 %) of the films. WCA (82.73 ± 0.95°), WVP (1.48 × 10-11 g·cm/cm2·s·Pa) and OTR (2.42 × 10-15 cm3·cm/cm2·s·Pa) indicated that the film possessed water resistance and oxygen barrier properties. When exposed to daylight, the film underwent a color transition from purple to green as the ammonia concentration increased. In addition, the blue-green fluorescence of the films gradually increased and the detection limit was low (170 ppb). In particular, the change in film color caused by shrimp spoilage corresponded to the TVBN value. This study work provides a new strategy for controlling and monitoring food safety and has a wide range of applications in the fields of food-active packaging and smart packaging.

Current applications and future trends of artificial senses in fish freshness determination: A review

Fish is a highly demanding food product and the determination of fish freshness is crucial as it is a fundamental factor in fish quality. Therefore, the fishery industry has been working on developing rapid fish freshness determination methods to monitor freshness levels. Artificial senses that mimic human senses are developed as convenient emerging technologies for fish freshness determination. Computer vision, electronic nose (e-nose), and electronic tongue (e-tongue) are the emerging artificial senses for fish freshness determination. This review article is uniquely worked upon to investigate the current applications of the artificial senses in fish freshness determination while describing the steps, and fundamental principles behind each artificial sense, comparing them with their advantages and limitations, and future trends related to fish freshness determination. Among the artificial senses, computer vision determines the freshness of fish in a completely nondestructive way while the e-tongue determines the freshness of fish in a completely destructive way. There are developed e-noses for fish freshness determination in both destructive and nondestructive ways. By analyzing visual cues such as color, computer vision systems can assess fish quality without the need for physical contact and it makes computer vision suitable for large-scale industrial fish quality assessing applications. Overall, this review study reveals artificial senses as a proven replacement for traditional sensory panels in determining fish freshness precisely and conveniently. As future trends, there is a demand for developing applications for consumers to determine fish freshness based on artificial senses.

Two dimensional iron metal-organic framework nanosheet with peroxidase-mimicking activity for colorimetric detection of hypoxanthine related to shrimp freshness

Two dimensional iron metal-organic framework nanosheet (2D Fe MOF) was facilely synthesized at room temperature by simple stirring of iron salts and terephthalic acid ligand in a mixed solution containing triethylamine. Its morphology and structure were fully characterized by TEM, AFM, XPS and TEM element mapping. Then, its peroxidase-mimicking activity was studied by using H2O2 and 3, 3', 5, 5'- tetramethylbenzidine as substrate. Km and Vmax of 2D Fe MOF towards H2O2 were 0.02 mM and 2.08 × 10-8 M s-1, respectively. Through the formation of cascade reaction between xanthine oxidase and 2D Fe MOF, a visual method for hypoxanthine (Hx) detection was constructed to evaluate aquatic products freshness. After effective validation, this method presented wide linear range (5.0-500.0 μM), low limit of detection (3.29 μM), satisfied accuracy (recovery of 94.78-99.85%), and good selectivity. By using this method, Hx content in shrimp samples at different storage time were determined.

Quality changes, potential spoilage organisms, and shelf-life prediction of brackish river prawn (Macrobrachium macrobrachion) at different storage temperatures

The brackish river prawn (Macrobrachium macrobrachion) is a species of commercial importance in West Africa. However, like other fishery products, it is prone to deterioration due mainly to microbial activities. The present study aimed at evaluating the spoilage characteristics of M. macrobrachion and predicting the growth of the main spoilage bacteria as well as the shelf-life of the product as a function of storage temperature. Freshly caught brackish river prawn samples from Lake Aheme were aerobically stored at 0, 7, 15, and 28 °C and, at pre-determined times during storage, they were taken for microbiological, chemical, and sensory analysis. At sensory rejection times, the spoilage potential of 185 isolates from specific groups of organisms enumerated was assessed in prawn of which the endogenous microbiota was heat inactivated. Isolates capable of producing strong off-odor were identified using 16S rRNA sequencing. Models predicting the maximum growth rate of Pseudomonas spp. and H2S-producing bacteria in the brackish river prawn as well as the shelf-life of the product were developed. These models were validated using an independent experiment during which prawn was stored at 0, 4, 10, and 25 °C. Results showed that Pseudomonas spp. at 0 °C, Pseudomonas spp. and H2S-producing bacteria at 7 °C, and H2S-producing bacteria at 15 °C and 28 °C were the dominant groups of microorganisms during storage. As expected, total volatile basic nitrogen, trimethylamine, and pH with initial values of 21.2 ± 3.0 mg-N/100 g, 4.1 ± 0.8 mg-N/100 g, and 7.46 ± 0.15 increased during storage reaching approximately 35 mg-N/100 g, 10 mg/ 100 g and 8, respectively at sensory rejection times which were 7 h at 28 °C, 1.2 d at 15 °C, 4.6 d at 7 °C, and 11.7 d at 0 °C. The main spoilage organisms were Citrobacter braakii at 28 °C, Citrobacter braakii, Pseudomonas kurunegalensis, and Shewanella bicestrii at 15 °C, Shewanella putrefaciens, Shewanella baltica, and Pseudomonas bubulae at 7 °C, and Pseudomonas versuta at 0 °C. The validation of the developed models showed an adequate agreement between the predicted and observed values. This study highlights the specific spoilage characteristics of the brackish river prawn and reveals that Gram-negative rod bacteria are the main spoilage organisms even at high storage temperatures, contrary to many earlier reports on the spoilage of tropical fishery products.

Dynamic Modelling and Simulation of Food Systems: Recent Trends and Applications

Several factors influence consumers' choices of food products [...].