Guideline for proper usage of time temperature integrator (TTI) avoiding underestimation of food deterioration in terms of temperature dependency: A case with a microbial TTI and milk

A comprehensive review of intelligent controlled release antimicrobial packaging in food preservation

Intelligent responsive packaging provides informative feedback or control the release of active substances like antimicrobial agents in response to stimuli in food or the environment to ensure food safety. This paper provides an overview of two types of intelligent packaging, information-responsive and intelligent controlled-release, focusing on the recent research progress of intelligent controlled-release antimicrobial packaging with enzyme, pH, relative humidity, temperature, and light as triggering factors. It also summarizes the current status of application in different food categories, as well as the challenges and future prospects. Intelligent controlled-release technology aims to optimize the antimicrobial effect and ensure the quality of food products by synchronizing the release of active substances with food preservation needs through sensing stimuli, which is an innovative and challenging packaging technology. The paper seeks to provide a reference for the research and industrial development of responsive intelligent packaging and controlled-release packaging applications in food.

Informative and corrective responsive packaging: Advances in farm-to-fork monitoring and remediation of food quality and safety

Microbial growth and fluctuations in environmental conditions have been shown to cause microbial contamination and deterioration of food. Thus, it is paramount to develop reliable strategies to effectively prevent the sale and consumption of contaminated or spoiled food. Responsive packaging systems are designed to react to specific stimuli in the food or environment, such as microorganisms or temperature, then implement an informational or corrective response. Informative responsive packaging is aimed at continuously monitoring the changes in food or environmental conditions and conveys this information to the users in real time. Meanwhile, packaging systems with the capacity to control contamination or deterioration are also of great interest. Encouragingly, corrective responsive packaging attempting to mitigate the adverse effects of condition fluctuations on food has been investigated. This packaging exerts its effects through the triggered release of active agents by environmental stimuli. In this review, informative and corrective responsive packaging is conceptualized clearly and concisely. The mechanism and characteristics of each type of packaging are discussed in depth. This review also summarized the latest research progress of responsive packaging and objectively appraised their advantages. Evidently, the mechanism through which packaging systems respond to microbial contamination and associated environmental factors was also highlighted. Moreover, risk concerns, related legislation, and consumer perspective in the application of responsive packaging are discussed as well. Broadly, this comprehensive review covering the latest information on responsive packaging aims to provide a timely reference for scientific research and offer guidance for presenting their applications in food industry.

Enzymatic Time-Temperature Indicator Prototype Developed by Immobilizing Laccase on Electrospun Fibers to Predict Lactic Acid Bacterial Growth in Milk during Storage

Laccase was immobilized on a chitosan/polyvinyl alcohol/tetraethylorthosilicate electrospun film (ceCPTL) and colored with guaiacol to obtain a laccase time-temperature indicator (TTI) prototype. The activation energy (Ea) of coloration of the prototype was 50.89-33.62 kJ/mol when 8-25 μg/cm² laccase was immobilized on ceCPTL, and that of lactic acid bacteria (LAB) growth in milk was 73.32 kJ/mol. The Ea of coloration of the TTI prototype onto which 8-10 μg/cm² laccase was immobilized was in the required range for predicting LAB growth in milk. The coloration endpoint of the TTI prototype onto which 10 μg/cm² (0.01 U) laccase was immobilized could respond to the LAB count reaching 10⁶ colony-forming units (CFU)/mL in milk during a static temperature response test, and the prediction error was discovered to be low. In dynamic temperature response experiments with intermittent temperature changes between 4 and 25 °C, the coloration rate of the laccase TTI prototype was consistent with LAB growth. The results of this study indicate that the laccase TTI prototype can be applied as a visual monitoring indicator to assist in evaluating milk quality in cold chains.

Prediction of fruit quality based on the RGB values of time-temperature indicator

Time-temperature indicators (TTIs) are cost-efficient tools that may be used to predict food quality. In this paper, a diffusion TTI was used to predict fruit quality during storage. Both the color changing characters of TTI and the quality parameters, including weight loss, soluble solids content, vitamin C content, titratable acidity, and antioxidant capacity of three kinds of fruits (kiwifruit, strawberry, and mango), were investigated for storage temperatures (5, 10, 15, and 20 °C). The relationships between the color changing properties and fruit quality parameters have been built based on the activation energy (E_a ). The results showed that the storage temperature and time had significant effects on the color changing of TTI and fruit quality. The RGB value of TTI decreased with time, and the higher the storage temperature, the faster the RGB value reduced. Also, the higher the storage temperature, the faster the fruit quality changed and the poorer they were. Furthermore, all of the differences of E_a between TTI color response and fruit quality change are less than 25 kJ/mol, which indicates that the TTI can be used to predict these fruit quality. Finally, prediction models were built and validated based on the RGB values of TTI. It provides the possibility for low-cost quality monitoring and has more application potential in food quality predicting. PRACTICAL APPLICATION: By monitoring the color change of diffuse time-temperature indicator (TTI) and the quality change of fruit, the feasibility of TTI for fruit quality monitoring was determined and the quality prediction model was established. The diffusion TTI and fruit quality prediction model can realize the monitoring and predicting of fruit quality based on the TTI, which provides a basis for the combination of TTI Quick Response Code and fruit quality monitoring, with a view to achieving fruit quality status by scanning the Quick Response Code of TTI with mobile phones in the future. This method may provide a new solution to monitor the fruit quality during storage and distribution based on visualization technology that can simplify the methods of detecting fruit quality and achieve fast quality detection. It provides the possibility for low-cost quality monitoring and has more application potential in food quality predicting. Further studies on diffusion TTI are needed to develop its application in more field of food and make the diffusion TTI an intelligent mean for food quality monitoring and predicting.

A new method for matching gold nanoparticle-based time-temperature indicators with muffins without obtaining activation energy

Time-temperature indicators (TTIs) can monitor the quality and safety of food. A new temperature-time point comparison method was proposed to match TTIs with food. This method omits the step of calculating activation energy (E_a ). It only compares the difference between TTI response time and food shelf life to determine their matching degree. Taking gold nanoparticle-based TTIs and muffins as experimental objects, the new and the traditional matching methods were used to match the absorbance of TTI and the peroxide value of muffins. The two results are not significantly different. TTIs with gelatin solution and gold precursor solution concentration of 150.00  and 2.05 mg/mL, respectively, can show the quality of muffins. TTIs changed from light yellow to pink and finally appeared deep purple. The deep purple represented spoilage and inedibility of muffins. Comparing E_a of food and that of TTIs can preliminarily evaluate their matching degree, improving the experiment efficiency. Hence, it is reasonable to use the traditional matching method in most cases, and use the new method only when E_a of food cannot be obtained. PRACTICAL APPLICATION: The deterioration rate of food is usually calculated by developing kinetic models of characteristic quality parameters. When the reaction rate is unavailable or inaccurate, the activation energy of food cannot be obtained. In this case, it is impossible to match TTIs with food based on the traditional method. This research develops a new matching method and helps TTIs and food to be matched without considering activation energy. It will promote the application of TTIs in more products.

Practicability of TTI application to yogurt quality prediction in plausible scenarios of a distribution system with temperature variations

Yogurt has high temperature sensitivity, resulting in the temperature variations from production to consumption. Cooling capacity of cold chain facilities and product storage height are regarded as factors contributing to temperature variations in this study. To find an effective method to monitor temperature history of every yogurt product, three measurements were used: the set point of a cold chamber, a data logger, and a time-temperature integrator (TTI). The mean measured yogurt quality factor (acidity, °T) of 30 samples was 92.1 °T, and predicted values were 91.8 °T from the set point, 93.3 °T from the data logger, and 92.4 °T from the TTI. In terms of individual prediction, the SSE of the TTI showed the smallest difference (5.76) followed by 81.5 of the set point and 118.9 of the data logger. Thus, the TTI showed the best performance and can be used to monitor the time-temperature history of yogurt in the cold chain system.

Evaluation of Models for Temperature-Dependent Viscosity Changes in Dairy Protein Beverage Formulations During Thermal Processing

Rheological modeling as a function of temperature is a useful tool for describing products undergoing thermal processing. The rheological behavior of a range of dairy-based (4%, w/w) protein beverages was investigated for applicability to semi-empirical temperature-dependent viscosity equations. The viscosity at 16.8 rad/s of the beverages was measured during heating, holding, and cooling over a temperature range of 25 to 90 ^o C using a rheometer with starch pasting cell geometry. Five established fitting methods were applied based on the Arrhenius and Williams-Landel-Ferry (WLF) equations using nonlinear regression analysis. A two-parameter WLF (WLF₂ ) model, using viscosity at a reference temperature of 25 ^o C resulted in high R² values (0.974 to 0.988) and a statistically superior fit compared to the Arrhenius, Generalized Arrhenius, and exponential equations (P < 0.001). Deviation from the WLF₂ modeled equation was used to describe and investigate the effect formulation had on the changes in viscosity during thermal heating. This study successfully applied the WLF equation to a liquid protein system, proving that a consistent and close fit can be achieved across a range of formulations. A rapid, quantitative method for viscosity-temperature profile evaluation is presented, which can ease product development and optimization of product processing stability.

PRACTICAL APPLICATION

This study validated the use of the Williams-Landel-Ferry equation to describe the behavior of dairy beverages during thermal processing, providing a better fit to rheological data than the widely used Arrhenius-based equations. In conjunction with the WLF equation, a method was presented which reduced the complex rheological data to a single value, which can aid in the comparison of formulations for product development and optimization in both research and industry.

Shelf Life of Food Products: From Open Labeling to Real-Time Measurements

The labels currently used on food and beverage products only provide consumers with a rough guide to their expected shelf lives because they assume that a product only experiences a limited range of predefined handling and storage conditions. These static labels do not take into consideration conditions that might shorten a product's shelf life (such as temperature abuse), which can lead to problems associated with food safety and waste. Advances in shelf-life estimation have the potential to improve the safety, reliability, and sustainability of the food supply. Selection of appropriate kinetic models and data-analysis techniques is essential to predict shelf life, to account for variability in environmental conditions, and to allow real-time monitoring. Novel analytical tools to determine safety and quality attributes in situ coupled with modern tracking technologies and appropriate predictive tools have the potential to provide accurate estimations of the remaining shelf life of a food product in real time. This review summarizes the necessary steps to attain a transition from open labeling to real-time shelf-life measurements.