Shelf-life variations in pallet unit loads during perishable food supply chain distribution

Evaluation of Temperature Uniformity in a Middle-Refrigerated Truck Loaded with Pig Carcasses

In this study, we constructed a calculation model to determine the internal temperature field distribution in a medium-sized refrigeration truck with the dimensions of 4.1 m × 2.2 m × 2.2 m. Wind speed, air temperature, and carcass temperature were designated as the initial conditions. The k-ε model of computational fluid dynamics was used to simulate different wind speeds and ventilation duct settings on the carriage. Additionally, under specific boundary conditions, the speed of the air outlet, the types of ventilation ducts, and the carcass loads were all varied to determine the uniformity of the temperature field. The results showed that, when the air outlet speed was 5 m/s, the temperature field in the refrigerated truck was relatively more uniform. The simulated results were in good agreement with the measured results. The average absolute error was 0.35 °C, and the average relative error was 9.23%.

A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks

The unexpected emergence of the COVID-19 pandemic has changed how grocery shopping is done. The grocery retail stores need to ensure hygiene, quality, and safety concerns in-store shopping by providing "no-touch" smart packaging solutions for agri-food products. The benefit of smart packaging is to inform consumers about the freshness level of a packaged product without having direct contact. This paper proposes a data-driven decision support system that uses smart packaging as a smart product-service system to manage the sustainable grocery store supply chain during outbreaks to prevent food waste. The proposed model dynamically updates the price of a packaged perishable product depending on freshness level while reducing food waste and the number of rejected customers and maximising profit by increasing the inventory turnover rate of grocery stores. The model was tested on a hypothetical but realistic case study of a single product. The results of this study showed that stock capacities, freshness discount rate, freshness period, and quantity discounts significantly affect the performance of a grocery store supply chain during outbreaks.

In-transit interventions using real-time data in Australian berry supply chains

Purpose

The objective of this paper is to contribute to Australian berry supply chains with a relevant identification regarding the possible data driven interventions that stakeholders can take while the berries are in transit.

Design/methodology/approach

An exploratory series of semi-structured interviews was conducted through six Australian experts in the industry with more than 20 years of experience in Australian berry supply chains and the Australian perishable food industry, to identify key possible in-transit interventions that could be implemented in the Australian berry industry.

Findings

The analysis of the interviews revealed a total of 18 possible in-transit interventions. An important finding is that in-transit interventions are made possible by the use of real-time data gathered through IoT devices such as Active Radio Frequency Identification, Time and Temperature Indicators interacting with Wireless Sensor Networks. Another key finding is that Australian berry growers and retailers do possess the technologies and the resources necessary to make in-transit interventions possible, however they have yet applied these technologies to operational decision-making and interventions based on the product, rather focussing on supply chain transactions and events.

Research limitations/implications

Since the research focusses on an Australian context, its findings may or may not be applicable to other countries. The research is exploratory in nature, and its findings should be verified by future research, in particular to test whether the in-transit interventions proposed here can be implemented in a cost-efficient way.

Originality/value

To the authors' knowledge, this publication is the first known academic article to provide a clear understanding of the Australian berry industry from a supply chain and logistics perspective, and the first to explore possible data driven in-transit interventions in perishable food supply chains.

Veterinary and sanitary assessment and disinfection of refrigerator chambers of meat processing enterprises

The results of microbiological studies of air samples of refrigerating chambers of meat processing enterprises are presented. The quantitative composition of the air microbiota of the chambers of the refrigerating shop was studied. It has been established that the technological regimes for cooling meat in cooled chambers (t = +4 °C) and deep freezing chambers (t = -18 °C and -22 °C) have no bacteriostatic effect on the life activity of mold fungi. The developed disinfecting preparation (hydrogen peroxide (8.0 - 10%), acetic acid (10%), peracetic acid (5.0 - 7.0%), stabilizing additives, water) ensures the destruction of sanitary-indicative microorganisms in cold rooms meat processing plants when applied at a concentration of 0.05% - 60 minutes, 0.1% - 30 minutes, 0.15% - 10 minutes and does not have a toxic effect on meat raw materials that are stored in chambers of the refrigeration shop after disinfection.

A Procedure for Tracing Supply Chains for Perishable Food Based on Blockchain, Machine Learning and Fuzzy Logic

One of the essential points of food manufacturing in the industry and shelf life of the products is to improve the food traceability system. In recent years, the food traceability mechanism has become one of the emerging blockchain applications in order to improve the anti-counterfeiting area’s quality. Many food manufacturing systems have a low level of readability, scalability, and data accuracy. Similarly, this process is complicated in the supply chain and needs a lot of time for processing. The blockchain system creates a new ontology in the traceability system supply chain to deal with these issues. In this paper, a blockchain machine learning-based food traceability system (BMLFTS) is proposed in order to combine the new extension in blockchain, Machine Learning technology (ML), and fuzzy logic traceability system that is based on the shelf life management system for manipulating perishable food. The blockchain technology in the proposed system has been developed in order to address light-weight, evaporation, warehouse transactions, or shipping time. The blockchain data flow is designed to show the extension of ML at the level of food traceability. Finally, reliable and accurate data are used in a supply chain to improve shelf life.

Vehicle routing in cold food supply chain logistics: a literature review

Purpose

Cold supply chain (CSC) distribution systems are vital in preserving the integrity and freshness of transported temperature sensitive products. CSC is also known to be energy intensive with a significant emission footprint. As a result, CSC requires strict monitoring and control management system during storage and transportation to improve safety and reduce profit losses. In this research, a systematic review of recent literature related to the distribution of food CSC products is presented and possible areas to extend research in modeling and decision-making are identified.

Design/methodology/approach

The paper analyzes the content of 65 recent articles related to CSC and perishable foods. Several relevant keywords were used in the initial search, which generated a list of 214 articles. The articles were screened based on content relevance in terms of food vehicle routing modeling and quality. Selected articles were categorized and analyzed based on cost elements, modeling framework and solution approach. Finally, recommendations for future research are suggested.

Findings

The review identified several research gaps in CSC logistics literature, where more focused research is warranted. First, the review suggests that dynamic vehicle modeling and routing while considering products quality and environmental impacts is still an open area for research. Second, there is no consensus among researchers in terms of quality degradation models used to assess the freshness of transported cold food. As a result, an investigation of critical parameters and quality modeling is warranted. Third, and due to the problem complexity, there is a need for developing heuristics and metaheuristics to solve such models. Finally, there is a need for extending the single product single compartment CSC to multi-compartment multi-temperature routing modeling.

Originality/value

The article identified possible areas to extend research in CSC distribution modeling and decision-making. Modified models that reflect real applications will help practitioners, food authorities and researchers make timely and more accurate decisions that will reduce food waste and improve the freshness of transported food.

A Multi-Objective Model for Sustainable Perishable Food Distribution Considering the Impact of Temperature on Vehicle Emissions and Product Shelf Life

The food distribution process is responsible for significant quality loss in perishable products. However, preserving quality is costly and consumes a tremendous amount of energy. To tackle the challenge of minimizing transportation costs and CO2 emissions while also maximizing product freshness, a novel multi-objective model is proposed. The model integrates a vehicle routing problem with temperature, shelf life, and energy consumption prediction models, thereby enhancing its accuracy. Non-dominated sorting genetic algorithm II is adapted to solve the proposed model for the set of Solomon test data. The conflicting nature of these objectives and the sensitivity of the model to shelf life and shipping container temperature settings are analyzed. The results show that optimizing freshness objective degrade the cost and the emission objectives, and the distribution of perishable foods are sensible to the shelf life of the perishable foods and temperature settings inside the container.

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.

A Holistic Packaging Efficiency Evaluation Method for Loss Prevention in Fresh Vegetable cold chain

With the continuous push for improving packaging efficiency of current packaging practices to prevent losses in a real cold chain, a holistic evaluation method with improved indicators and a conceptual assessment framework to improve packaging efficiency continuously in a fresh vegetable cold chain was proposed. Based on two fresh leafy vegetables with typical packaging practices in a real cold chain in China, the evaluation method was performed and tested from a macro perspective, and then the packaging efficiency constitution with loss prevention perspective was better visualized. The results show that the method can be used for improving the performance of specific packaging efficiency in the fresh vegetable cold chain and improving the suggestions’ sustainability orientation, and systematically summarize their impacts on packaging efficiency; specifically as follows: (1) Since the correlation between the state of fresh vegetables and the environmental stress in the package, the performance of the micro-environment parameters should be given priority for packaging efficiency improvement in loss prevention. (2) Although the use of the packaging materials in current practices was relatively better, it still can improve in food safety and packaging sustainability of the packaging practices through the selection of packaging materials with better sustainability characteristics. (3) Via the visualization of targeted packaging efficiency in cold chain, the fluctuation of loss rates in the cold chain process are well perceived, and there are still room can be performed continuously to realize more efficient packaging for better loss prevention. (4) The method has drawbacks that the optimization of the weights to the given indicators and the indicators based on nutrition and quality of fresh produce was not considered in current research, and it should be strengthened in future research. (5) It is necessary that the perception of differences in targeted packaging efficiency and the consciousness to improve specific packaging efficiency in vegetable cold chain for sustainability.

Exposure Assessment and Sensitivity Analysis for Chilled Shrimp During Distribution: A Case Study of Home Delivery Services in Taiwan

In this study, we evaluated the temperature requirements for home delivery in Taiwan by considering food safety risks of chilled shrimp that may be contaminated with Vibrio parahaemolyticus. Pathogenic V. parahaemolyticus was chosen because it was the main cause of foodborne outbreaks originating from contaminated seafood in Taiwan. The risk of becoming ill due to consumption of raw shrimp was estimated to be 7.3 × 10^-3 per serving, estimated based on the real-time temperature profile. Lowering the maximum temperature to 7 °C during transit and cooking shrimps at 100 °C for 5 min could reduce the risk by more than 94%. These interventions, therefore, were suggested to be used as an integral part of temperature management control in the home delivery cold chain. These findings can help food authorities to institute temperature management policies and regulations to prevent broken cold chains and reduce food safety risks. PRACTICAL APPLICATION: This research may be applicable to home delivery services that deliver low-temperature food products, such as seafood products.