Use of time-temperature integrators and predictive modelling for shelf life control of chilled fish under dynamic storage conditions

Modeling the influence of propionic acid concentration and pH on the kinetics of Salmonella Typhimurium

Salmonella Typhimurium is a foodborne pathogen often found in the poultry production chain. Antibiotics have been used to reduce S. Typhimurium contamination in poultry aviaries and improve chicken growth. However, antibiotics were banned in several countries. Alternatively, organic acids, such as propionic acid (PA), can control pathogens. This study determined the PA minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and mathematically modeled S. Typhimurium growth/inactivation kinetics under the influence of PA at different pH values (4.5, 5.5, and 6.5) which are within the pH range of the chicken gastrointestinal tract. The PA MIC against S. Typhimurium was pH-dependent, resulting in 5.0, 3.5 and 9.0 mM undissociated PA at pH 4.5, 5.5, and 6.5, respectively. The Baranyi and Roberts and the Weibull model fit growth and inactivation data well, respectively. Secondary models were proposed. The validated model predicted 3-log reduction of S. Typhimurium in 3 h at 68.2 mM of undissociated PA and pH 4.5. The models presented a good capacity to describe the kinetics of S. Typhimurium subjected to PA, representing a useful tool to predict PA antibacterial action depending on the pH.

Chilled Pacu (Piaractus mesopotamicus) fillets: Modeling Pseudomonas spp. and psychrotrophic bacteria growth and monitoring spoilage indicators by 1H NMR and GC-MS during storage

This study aimed to assess the growth of Pseudomonas spp. and psychrotrophic bacteria in chilled Pacu (Piaractus mesopotamicus), a native South American fish, stored under chilling conditions (0 to 10 °C) through the use of predictive models under isothermal and non-isothermal conditions. Growth kinetic parameters, maximum growth rate (μmax, 1/h), lag time (tLag, h), and (Nmax, Log10 CFU/g) were estimated using the Baranyi and Roberts microbial growth model. Both kinetic parameters, growth rate and lag time, were significantly influenced by temperature (P < 0.05). The square root secondary model was used to describe the bacteria growth as a function of temperature. Secondary models, √μ = 0.016 (T + 10.13) and √μ =0.017 (T + 9.91) presented a linear correlation with R2 values >0.97 and were further validated under non-isothermal conditions. The model's performance was considered acceptable to predict the growth of Pseudomonas spp. and psychrotrophic bacteria in refrigerated Pacu fillets with bias and accuracy factors between 1.24 and 1.49 (fail-safe) and 1.45-1.49, respectively. Fish biomarkers and spoilage indicators were assessed during storage at 0, 4, and 10 °C. Volatile organic compounds, VOCs (1-hexanol, nonanal, octenol, and indicators 2-ethyl-1-hexanol) showed different behavior with storage time (P > 0.05). 1H NMR analysis confirmed increased enzymatic and microbial activity in Pacu fillets stored at 10 °C compared to 0 °C. The developed and validated models obtained in this study can be used as a tool for decision-making on the shelf-life and quality of refrigerated Pacu fillets stored under dynamic conditions from 0 to 10 °C.

The sensory evaluation and antimicrobial efficacy of Lactobacillus acidophilus supernatant on Salmonella enteritidis in milk

Postbiotics are metabolites derived from living probiotic bacteria like Lactobacillus strains, during the fermentation process and/or produced in pure form on laboratory scales. These compounds, depending on the type of probiotic from which they are prepared, have specific antibacterial agents such as: organic acids, bacteriocins, short-chain fatty acids, and peptides. The objective of this study was to investigate the effect of Lactobacillus acidophilus supernatant (LAS) on the growth pattern of Salmonella enteritidis at fluctuating temperatures and the sensory evaluation of milk that contains this probiotic. Baranyi and Roberts's model determined the best-fit curve for the microbial growth. According to mathematical equations, the highest and lowest specific growth (μ max) rates of S. enteritidis were obtained at 0.055 h-1 and 0.0059 h-1 and also highest and lowest maximum generation time (MGT) values were obtained at 20.06 h and 8.85 h, respectively. Sensory evaluation by the Triangel test reveals that LAS could not establish a significant (p > .05) adverse effect on milk perceptible. Regarding the results obtained in the present study, LAS, without causing adverse sensory change, could act as a safe food additive for the control of bacterial pathogens and reducing food waste, particularly in milk and milk-containing food products.

Development of a microbial time-temperature indicator for real-time monitoring the quality of Australian vacuum-packed lamb

A time-temperature indicator (TTI) system based on the pH-dependent colour change caused by the growth of a Carnobacterium maltaromaticum strain was developed to specifically provide a real-time indication of quality and shelf life of Australian vacuum-packed (VP) lamb throughout cold chains. Each component of the developed TTI system was studied to select an optimal concentration of a chemical chromatic indicator (chlorophenol red, CR; between 0.01 % and 0.30 %) and supplementary glucose (between 0 % and 10 %), and an appropriate C. maltaromaticum strain (among four different strains) in a simple BHI medium. BHI medium containing 0.01 % CR and 1 % added glucose, inoculated with C. maltaromaticum strain 1 were required for development of the TTI system to indicate quality and shelf life of VP lamb. Different inoculum levels of C. maltaromaticum strain 1 (103 to 105 CFU/mL) were also examined at 8 °C for their effects on the TTI response. As expected, higher inoculum levels of C. maltaromaticum led to a shorter endpoint of the TTI system but it was found that a 3 log10 higher inoculum level in the TTI than the expected total viable counts of VP lamb was required to accurately predict VP lamb shelf life by the TTI. To further evaluate the applicability of the TTI system, we evaluated its response at two other temperatures (2 °C and 4 °C) relevant to the storage conditions for VP lamb. The data showed a strong agreement between the observed TTI's endpoints and predicted shelf lives of VP lamb. This indicated that the developed TTI has the potential to be developed further for commercial application to provide a real-time, distinct, and accurate indication of Australian VP lamb.

The Use of Predictive Microbiology for the Prediction of the Shelf Life of Food Products

Microbial shelf life refers to the duration of time during which a food product remains safe for consumption in terms of its microbiological quality. Predictive microbiology is a field of science that focuses on using mathematical models and computational techniques to predict the growth, survival, and behaviour of microorganisms in food and other environments. This approach allows researchers, food producers, and regulatory bodies to assess the potential risks associated with microbial contamination and spoilage, enabling informed decisions to be made regarding food safety, quality, and shelf life. Two-step and one-step modelling approaches are modelling techniques with primary and secondary models being used, while the machine learning approach does not require using primary and secondary models for describing the quantitative behaviour of microorganisms, leading to the spoilage of food products. This comprehensive review delves into the various modelling techniques that have found applications in predictive food microbiology for estimating the shelf life of food products. By examining the strengths, limitations, and implications of the different approaches, this review provides an invaluable resource for researchers and practitioners seeking to enhance the accuracy and reliability of microbial shelf life predictions. Ultimately, a deeper understanding of these techniques promises to advance the domain of predictive food microbiology, fostering improved food safety practices, reduced waste, and heightened consumer confidence.

Application of intelligent packaging for meat products: A systematic review

BACKGROUND

Today, in response to consumer demand and market trends, the development of new packaging with better performance such as intelligent packaging has become more important. This packaging system is able to perform intelligent functions to increase shelf life, increase safety and improve product quality.

OBJECTIVES

Recently, various types of packaging systems are available for meat products, especially cooked, fresh and processed meats. But because meat products are very perishable, monitoring their quality and safety in the supply chain is very important. This systematic article briefly reviews some of the recent data about the application of intelligent packaging in meat products.

METHODS

The search was conducted in Google Scholar, Science Direct, Elsevier, Springer, Scopus, and PubMed, from April 1996 to April 2021 using a different combination of the following keyword: intelligent packaging, and meat.

RESULTS

The results showed that the intelligent packaging presents several benefits compared to traditional packaging (e.g., antimicrobial, antioxidant, and shelf life extension) at the industrial processing level. Thus, these systems have been applied to improve the shelf life and textural properties of meat and meat products.

CONCLUSIONS

It is necessary to control the number of intelligent compounds that are included in the packaging as they clearly influence the quality and nutritional properties as well as the final cost of the food products.

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

Fish freshness can be considered as the combination of different nutritional and organoleptic attributes that rapidly deteriorate after fish capture, i.e., during processing (cutting, gutting, packaging), storage, transport, distribution, and retail. The rate at which this degradation occurs is affected by several stress variables such as temperature, water activity, or pH, among others. The food industry is aware that fish freshness is a key feature influencing consumers’ willingness to pay for the product. Therefore, tools that allow rapid and reliable assessment and prediction of the attributes related to freshness are gaining relevance. The main objective of this work is to provide a comprehensive review of the mathematical models used to describe and predict the changes in the key quality indicators in fresh fish and shellfish during storage. The work also briefly describes such indicators, discusses the most relevant stress factors affecting the quality of fresh fish, and presents a bibliometric analysis of the results obtained from a systematic literature search on the subject.

Active and Intelligent Packaging for Enhancing Modified Atmospheres and Monitoring Quality and Shelf Life of Packed Gilthead Seabream Fillets at Isothermal and Variable Temperature Conditions

The study investigated the effect of active modified atmosphere packaging (20% CO2–60% N2–20% O2) with CO2 emitters (MAP-PAD) and conventional MAP (MAP) on the quality and shelf-life of gilthead seabream fillets during chill storage, while the most appropriate enzymatic Time Temperature Integrators (TTI) were selected for monitoring their shelf-life at isothermal and variable temperature storage conditions (Teff = 4.8 °C). The concentration of CO2 and O2 in the headspace of the package, volatile compounds and of the microbial population were monitored during storage. The kinetic parameters for bacterial growth were estimated at 0–10 °C using the Baranyi growth model. The MAP-PAD samples presented significantly lower microbial growth rates and longer lag phases compared to the MAP samples, leading to significant shelf-life extension: 2 days of extension at 2.5 °C and 5 °C, while 50% extension at variable conditions (Teff = 4.8 °C). CO2 emitters in the package improved the chemical freshness (K-values) and volatile compounds (characterizing freshness). The responses of different enzymatic TTI were modeled as the function of enzyme concentration, temperature and storage time. The activation energy (Ea) ranged from 97 to 148 kJ mol−1, allowing the selection of appropriate TTIs for the shelf-life monitoring of each fish product: LP-150U for the MAP and M-25U for the MAP-PAD samples. The validation experiment at Teff = 4.8 °C confirmed the applicability of Arrhenius-type models, as well as the use of TTIs as effective chill chain management tools during distribution and storage.

Dual bacterial strains TTI for monitoring fish quality in food cold chain

Most microbial time-temperature indicators (TTIs) considered only one spoilage strain. This research compared single and dual spoilage strains-based microbial TTI for quality changes of chilled grouper fish (Epinephelus fuscoguttatus x E. lanceolatus) fillet products during distribution. The next-generation sequencing (NGS) and traditional plate count approach showed that Pseudomonas fragi and Vibrio parahaemolyticus were specific spoilage bacteria at 7 and 15°C. A dual-strain TTI response provides more accurate results than a single-strain TTI and provides an irreversible color change from yellow to reddish-brown, showing levels of fish freshness. The microbial TTI comprises fish spoilage bacteria strains with 3 log CFU/ml, a nutrient broth supplemented with 2% NaCl as a medium, and phenol red with 0.25 mg/ml as a pH indicator. Overall, this study points to the applicability of a dual-strain microbial TTI as a valuable tool for monitoring fish quality changes during cold chain break condition.

Critical review and recent advances of 2D materials-Based gas sensors for food spoilage detection

Many people around the world are concerned about meat safety and quality, which has resulted in the ongoing advancement of packaged food technology. Since the emergence of graphene in 2004, the number of studies on layered two-dimensional materials (2DMs) for applications ranging from food packaging to meat quality monitoring has been expanding quickly. Recently, scientists have been working hard to develop a novel class of 2DMs that keep the good things about graphene but don't have zero bandgaps at room temperature. Much work has been done on layered transition metal dichalcogenides (TMDCs) like different metal sulfides and selenides for meat spoilage gas sensors. This review looks at (i) the main indicators of meat spoilage and (ii) the detection methods that can be used to find out if meat has been spoiled, such as chemiresistive, electrochemical, and optical methods. (iii) the role of 2DMs in meat spoilage detection and (iv) the emergence of advanced methods for selective classification of target analytes in meat/food spoilage detection in recent years. Thus, this review demonstrates the potential scope of 2DMs for developing intelligent sensor systems for food and meat spoilage detection with high viability, simplicity, cost-effectiveness, and other multipurpose tools.

Prediction in the Dynamics and Spoilage of Shewanella putrefaciens in Bigeye Tuna (Thunnus obesus) by Gas Sensors Stored at Different Refrigeration Temperatures

Shewanella putrefaciens have a faster growth rate and strong spoilage potential at low temperatures for aquatic products. This study developed a nondestructive method for predicting the kinetic growth and spoilage of S. putrefaciens in bigeye tuna during cold storage at 4, 7 and 10 °C by electronic nose. According to the responses of electronic nose sensor P30/2, the fitted primary kinetic models (Gompertz and logistic models) and secondary model (square root function model) were able to better simulate the dynamic growth of S. putrefaciens, with high R² and low RMSE values in the range of 0.96–0.99 and 0.021–0.061, respectively. A partial least squares (PLS) regression model based on both electronic nose sensor response values and electrical conductivity (EC) values predicted spoilage of S. putrefaciens in bigeye tuna more accurately than the PLS model based on sensor signal values only. In addition, SPME/GC-MS analysis suggested that 1-octen-3-ol, 2-nonanone, 2-heptanone, dimethyl disulfide and methylamine, N, N-dimethyl- are the key VOCs of tuna inoculated with S. putrefaciens.

The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art

Predictive microbiology has steadily evolved into one of the most important tools to assess and control the microbiological safety of food products. Predictive models were traditionally developed based on experiments in liquid laboratory media, meaning that food microstructural effects were not represented in these models. Since food microstructure is known to exert a significant effect on microbial growth and inactivation dynamics, the applicability of predictive models is limited if food microstructure is not taken into account. Over the last 10-20 years, researchers, therefore, developed a variety of models that do include certain food microstructural influences. This review provides an overview of the most notable microstructure-including models which were developed over the years, both for microbial growth and inactivation.

Control of temperature dependence of microbial time-temperature integrator (TTI) by microencapsulation of lactic acid bacteria into microbeads with different proportions of alginate

This study has been conducted to investigate the temperature dependence and mass transfer kinetics of a microbial time-temperature integrator (TTI) developed by using emulsification/internal ionotropic gelation method. We report the effect of the Na-alginate concentrations (0.5%, 2.0%, 4.0% and 6.0% w/v) and temperature (8, 15, 20, 25 and 30 °C) on the TTI responses (changes in pH and titratable acidity [TA]). Results revealed that Ca-alginate microbeads (Ca-AMs) prepared from 2.0% Na-alginate were more uniform and smaller, with a narrow size distribution, in comparison with the other Ca-AMs. For microbeads with above 2.0% Na-alginate, the TTI response rates decreased because of the lower diffusion efficiency. Linearity in the TA was greatest for the 2.0% Ca-AMs. Therefore, the mass transfer and TTI response kinetics data demonstrated that 2.0% Na-alginate was optimal for producing Ca-AMs from which an ideal microbial TTI could be developed to monitor food spoilage processes with accuracy and precision.

User-friendly lab-on-paper optical sensor for the rapid detection of bacterial spoilage in packaged meat products

A lab-on-paper colorimetric sensor for detection and quantification of bacterial meat spoilage is reported.

Optimization of the Effects of Different Temperatures and Compositions of Filmogenic Solution on Lactobacillus Salivarius Using Predictive Mathematical Models

It is well known that intake of probiotic brings health benefits. Lactic bacteria with probiotic potential have aroused the interest of the industry in developing food products that incorporate such benefits. However, incorporating probiotic bacteria into food is a challenge for the industry, given the sensitivity of probiotic cultures to process conditions. Therefore, the objective of this study is to evaluate gelatin- and inulin-based filmogenic solutions as a potential vehicle for incorporating probiotics into food products and to model the fermentation kinetics. L. salivarius (Lactobacillus salivarius) growth in filmogenic solutions was analyzed under the influence of a variety gelatin concentrations (1.0–3.0%) and inulin concentrations (4.0–6.0%) and fermented under the effect of different temperatures (25–45 °C). A full 2³ factorial plan with three replicates at the central point was used to optimize the process. The impacts of process conditions on cell development are fundamental to optimize the process and make it applicable by the industry. The present study showed that the optimal conditions for the development of probiotic cells in filmogenic solutions are a combination of 1.0% gelatin with 4.0% inulin and fermentation temperature of 45 °C. It was observed that the maximum cell growth occurred in an estimated time of about 4 h of fermentation. L. salivarius cell production and substrate consumption during the fermentation of the filmogenic solution were well simulated by a model proposed in this article, with coefficients of determination of 0.981 (cell growth) and 0.991 (substrate consumption).

Novel Color Change Film as a Time-Temperature Indicator Using Polydiacetylene/Silver Nanoparticles Embedded in Carboxymethyl Cellulose

Time-temperature indicators (TTIs) can be important tools in product applications to monitor food quality losses, especially for fruits and vegetables. In this context, the effects of silver nanoparticles (AgNPs) and glycerol on the color change of polydiacetylene/AgNPs (PDA/AgNPs) embedded in carboxymethyl cellulose (CMC) film as time-temperature indicators (TTIs) were investigated. A CMC film prepared with 30 mg/L AgNPs and a 1:3 (v/v) PDA:AgNP ratio exhibited a faster color change than under other conditions. At 35 °C, the films with PDA/AgNPs changed color from purplish-blue to purple and purple to reddish-purple over time due to the higher thermal conductivity of AgNPs and larger PDA surface area exposed to specific temperatures. The total color difference (TCD) of PDA/AgNP-embedded CMC film directly changed with regard to time and temperature. However, adding glycerol to the system resulted in a symmetrical chemical structure, a factor that delayed the color change. Scanning electron micrographs showed AgNPs embedded in the CMC films. Transmission electron micrographs indicated a core-shell structure of PDA/AgNP vesicles in the CMC matrix. PDA/AgNP vesicles were confirmed by second derivative Fourier transform infrared spectroscopy, with a new peak at 1390-1150 cm-1. The kinetics of TTIs from PDA/AgNP-embedded CMC films yielded an activation energy of 58.70 kJ/mol.

Predictive modelling for the growth kinetics of Pseudomonas spp. on button mushroom (Agaricus bisporus) under isothermal and non-isothermal conditions

Baranyi model was fitted to experimental growth data of Pseudomonas spp. on the button mushrooms (Agaricus bisporus) stored at different isothermal conditions (4, 12, 20 and 28 °C), and the kinetic growth parameters of Pseudomonas spp. on the button mushrooms were obtained. The goodness of fit of the Baranyi model was evaluated by considering the root mean squared error (RMSE) and the adjusted coefficient of determination (adjusted-R²). The Baranyi model gave RMSE values lower than 0.193 and adjusted-R² values higher than 0.975 for all isothermal storage temperatures. The maximum specific growth rate (µ_max) was described as a function of temperature using secondary models namely, Ratkowsky and Arrhenius models. The Ratkowsky model described the temperature dependence of µ_max better than the Arrhenius model. Therefore, the differential form of the Baranyi model was merged with the Ratkowsky model, and solved numerically using the fourth-order Runge-Kutta method to predict the concentration of Pseudomonas spp. populations on button mushrooms under non-isothermal conditions in which they are frequently subjected to during storage, delivery and retail marketing. The validation performance of the dynamic model used was assessed by considering bias (B_f) and accuracy (A_f) factors which were found to be 0.998 and 1.016, respectively. The dynamic model developed also exhibited quite small mean deviation (MD) and mean absolute deviation (MAD) values being -0.013 and 0.126 log CFU/g, respectively. The modelling approach used in this work could be an alternative to traditional enumeration techniques to determine the number of Pseudomonas spp. on mushrooms as a function of temperature and time.

Implementation of Time Temperature Indicators to Improve Temperature Monitoring and Support Dynamic Shelf Life in Meat Supply Chains

Based on the well-investigated OnVu™ TTI kinetics, models were developed to adjust the label to different food products and predict the discolouration process under dynamic temperature conditions. After the successful validation under laboratory conditions, the applicability of the time temperature indicator (TTI) as shelf life indicator was tested in a national poultry chain. The TTI accurately reflected the temperature fluctuations occurring under real chain conditions. Shelf life predictions based on the discolouration of the TTIs were in accordance with the microbial shelf life of the product. The models were integrated in an online software tool to check for the compliance of the cold chain and predict the remaining shelf life of the product. The implementation of TTI and the software result in a valuable tool to support the decision-making process in the cold chain. The application of flexible shelf life enables the reduction of food waste in the meat supply chain.

Cellulose Fibers Enable Near-Zero-Cost Electrical Sensing of Water-Soluble Gases

We report an entirely new class of printed electrical gas sensors that are produced at near "zero cost". This technology exploits the intrinsic hygroscopic properties of cellulose fibers within paper; although it feels and looks dry, paper contains substantial amount of moisture, adsorbed from the environment, enabling the use of wet chemical methods for sensing without manually adding water to the substrate. The sensors exhibit high sensitivity to water-soluble gases (e.g., lower limit of detection for NH3 < 200 parts-per-billion) with a fast and reversible response. The sensors show comparable or better performance (especially at high relative humidity) than most commercial ammonia sensors at a fraction of their price (<$0.02 per sensor). We demonstrate that the sensors proposed can be integrated into food packaging to monitor freshness (to reduce food waste and plastic pollution) or implemented into near-field-communication tags to function as wireless, battery-less gas sensors that can be interrogated with smartphones.

Filipe CD, Didar TF. Intelligent Food Packaging: A Review of Smart Sensing Technologies for Monitoring Food Quality

Food safety is a major factor affecting public health and the well-being of society. A possible solution to control food-borne illnesses is through real-time monitoring of the food quality throughout the food supply chain. The development of emerging technologies, such as active and intelligent packaging, has been greatly accelerated in recent years, with a focus on informing consumers about food quality. Advances in the fields of sensors and biosensors has enabled the development of new materials, devices, and multifunctional sensing systems to monitor the quality of food. In this Review, we place the focus on an in-depth summary of the recent technological advances that hold the potential for being incorporated into food packaging to ensure food quality, safety, or monitoring of spoilage. These advanced sensing systems usually target monitoring gas production, humidity, temperature, and microorganisms' growth within packaged food. The implementation of portable and simple-to-use hand-held devices is also discussed in this Review. We highlight the mechanical and optical properties of current materials and systems, along with various limitations associated with each device. The technologies discussed here hold great potential for applications in food packaging and bring us one step closer to enable real-time monitoring of food throughout the supply chain.

Predicting Shelf-life of Ice Cream by Accelerated Conditions

Shelf-life is defined as the amount of time during which a food product retains its desired sensory, chemical, and physical characteristics while remaining safe for consumption. The food industry needs to rapidly obtain the necessary information for determining the shelf life of its products. Here we studied the approaches available for conducting accelerated shelf-life tests. Accelerated shelf-life testing is applied to a variety of products to rapidly estimate change in characteristics with time. The aim of this work was to use accelerated shelf-life testing to study the changes in pH, microbiology, and sensory characteristics of ice cream by the application of a kinetic approach and, based on the observations, to estimate its shelf life. As per the current law, there is no shelf life on ice cream. Our results suggest that the shelf life of an ice cream sample was 24.27 months at –18℃, 2.29 months at –6℃, 0.39 months at –1℃, and 0.15 months at 4℃. Results of this study suggest that a set expiration date on ice cream might also contribute to effective management of ice cream characteristics in the retail chilled chain.

Integrating predictive models and sensors to manage food stability in supply chains

Food products move through complex supply chains, which require effective logistics to ensure food safety and to maximize shelf-life. Predictive models offer an efficient means to monitor and manage the safety and quality of perishable foods, however models require environmental data to estimate changes in microbial growth and sensory attributes. Currently, several companies produce Time-Temperature Indicators that react at rates that closely approximate predictive models; these devices are simple and cost-effective for food companies. However, even greater outcomes could be realized using sensors that transfer data to predictive models in real-time. This report describes developments in predictive models designed for supply chain management, as well as advances in environmental sensors. Important innovation can be realized in both supply chain logistics and food safety management by integrating these technologies.

The Effects of Short-Time Temperature Abuse on the Microbial and Sensory Quality of Chilled Saithe (Pollachius virens) Fillets

Chilled fish products are highly perishable with a limited shelf life (10 to 14 d). For this reason, the control of the cold chain for fish is essential. This study´s objective was to investigate the effects of short-time temperature abuse during processing on spoilage of chilled saithe (Pollachius virens) fillets. Analysis of microbial growth, freshness grades, and sensory score by Quality Index method, as well as pH, were carried out during a 10-d storage period at 2 ± 2 °C. Before storage, the fillets were kept at 16 °C for 0, 1, and 2 h. The results showed that spoilage of the fillets was accelerated with longer holding time at 16 °C. The 1- and 2-h holding before packing and storage caused a 22% (2 d) and 44% (4 d) loss of shelf life, respectively, compared to fillets that were packed immediately after processing. These findings indicate how bottlenecks and delays during processing may result in loss of microbial and sensory quality of chilled fish products.

PRACTICAL APPLICATION

The observations show the importance of maintaining a low temperature in fish, even for a short period such as during processing. Any delays, such as due to buffering or mechanical failure, may accelerate spoilage of chilled products during subsequent storage. This effect is even more pronounced when products are packed in bulk volumes as the cooling rate is much slower than the piece-by-piece cooling rate.

Quality Evaluation Focusing on Tissue Fractal Dimension and Chemical Changes for Frozen Tilapia with Treatment by Tangerine Peel Extract

This work aimed to establish an effective approach to evaluate the quality of frozen fish, focusing on changes in fish tissue structure and chemical composition during storage. Fresh tilapia samples were treated by coating with tangerine peel (TP) extract and then stored at −4, −8 and −18 °C, respectively, for 40 days. The frozen fish tissues were analyzed for structural and chemical changes. Fractal dimension, which quantifies the porous structure formed in the tissue samples, texture properties including hardness and springiness, and moisture content and water activity all decreased during the storage, while the extents of lipid oxidation, measured as peroxide value and thiobarbituric acid concentration, and protein degradation, monitored with total volatile basic nitrogen and trichloroacetic acid soluble peptides, increased. The change rates of these parameters decreased with decreasing the storage temperature and by applying TP extract. A model was developed for predicting fractal dimension, which indicated the quality of preserved tilapia and thus can be used to predict the shelf life under different storage temperatures. The results demonstrated that TP extract could extend the shelf life of frozen tilapia by 35–45% by inhibiting changes in tissue structure, moisture loss, lipid oxidation and protein degradation during frozen storage.

Predicting Gilthead Sea Bream (Sparus aurata) Freshness by a Novel Combined Technique of 3D Imaging and SW-NIR Spectral Analysis

A technique that combines the spatial resolution of a 3D structured-light (SL) imaging system with the spectral analysis of a hyperspectral short-wave near infrared system was developed for freshness predictions of gilthead sea bream on the first storage days (Days 0–6). This novel approach allows the hyperspectral analysis of very specific fish areas, which provides more information for freshness estimations. The SL system obtains a 3D reconstruction of fish, and an automatic method locates gilthead’s pupils and irises. Once these regions are positioned, the hyperspectral camera acquires spectral information and a multivariate statistical study is done. The best region is the pupil with an R² of 0.92 and an RMSE of 0.651 for predictions. We conclude that the combination of 3D technology with the hyperspectral analysis offers plenty of potential and is a very promising technique to non destructively predict gilthead freshness.