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

Albrecht, Antonia; Ibald, Rolf; Raab, V.; Reichstein, Werner; Haarer, D.; Kreyenschmidt, Judith

doi:10.1007/s41783-019-00080-x

Cited by 35 publications

(17 citation statements)

References 46 publications

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“…Wu et al [ 58 ] also considered the proper tracking system as a prerequisite in striking a balanced trade-off between the quality of products in a cold supply chain and the energy requirement and emissions. Albrecht et al [ 59 ] advocated the usage of Time Temperature Indicators (TTI) so that shelf life might be predicted in the light of microbial shelf life of the product.…”

Section: Inhibitors To Cold Supply Chain Operationsmentioning

confidence: 99%

Modelling the inhibitors of cold supply chain using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

Sharma

Abbas²,

Siddiqui

2021

PLoS ONE

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The Cold Supply Chain (CSC) is an integral part of the supply chain of perishable products. The aim of this research is to examine the inhibitors that have a major impact on the performance of CSC operations in the United Arab Emirates (UAE). This study provides a synthesis and suggests a hierarchical model among CSC inhibitors and their respective relevance. The hierarchical synthesis of twelve (12) primary CSC inhibitors is achieved through a comprehensive literature review and consultation with academics and CSC professionals. This study used semi-structured interviews, a fuzzy interpretive structural modeling (FISM) and a Fuzzy-MICMAC (FMICMAC) analysis to explore and establish the relationship between and among identified inhibitors. FISM is used to examine the interaction between inhibitors, while FMICMAC analysis is used to examine the nature of inhibitors on the basis of their dependence and driving power. The results of the FISM and FMICMAC analysis show the inter-relationships and relative dominance of identified inhibitors. The results show that some inhibitors are of high strategic importance due to their high driving power and low dependence. These inhibitors seek more management attention in order to improve their effectiveness. The result of a hierarchical model helps to understand the influence of a particular inhibitor on others. ‘Higher capital and operating costs’ occupy the highest level in the FISM model. The ‘fragmented cold supply chains’, ‘lack of skilled labor’, ‘inadequate information system infrastructure’ and ‘lack of commitment by top level management’ had strong driving power but weak dependence, which characterizes them as independent inhibitors. Management should be extra careful when dealing with these inhibitors as they influence the effects of other variables at the top of the FISM hierarchy in the overall management of the cold supply chain. The study also suggests a number of recommendations for addressing these inhibitors in cold supply chains operating in the UAE. With due attention and care for these inhibitors, the operation of the cold supply chains is likely to be even more successful.

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Section: Inhibitors To Cold Supply Chain Operationsmentioning

confidence: 99%

Modelling the inhibitors of cold supply chain using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

Sharma

Abbas²,

Siddiqui

2021

PLoS ONE

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“…Since most indicators are designed to respond to color changes, the advantages are clear; color responses are directly visible. With the emerging of image processing and optical techniques, color investigation of TTIs and GIs can be recognized using portable devices and smartphones; as a result, it helps to improve the online system and calculate the product's dynamic shelf life (Albrecht et al., 2020); thus, color‐based responses have more factor selections for model fitting. In contrast, there are some limitations and drawback.…”

Section: The Benefits Limitations Drawbacks and Accuracy Of Tti Anmentioning

confidence: 99%

Smart monitoring of gas/temperature changes within food packaging based on natural colorants

Mohammadian

Sani

Jafari

2020

Comp Rev Food Sci Food Safe

100

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The development of smart packaging and innovation in common food packaging technology will greatly help to meet market needs, including consumer preference for "safe" foods, high-quality products and mitigate the negative environmental impacts of food packaging. In addition, consumers' tendency to use natural ingredients such as pigments and biopolymers has provided the basis for their application in the food industry, including smart food packaging. Hence, smart packaging in addition to protecting food products against environmental damage can also reveal a sign (colorimetric, chemical, electric, etc.) in real time in response to any changes in the packaging conditions and food quality. This comprehensive review emphasizes on the gas/temperature-sensitive smart films based on natural colorants and their key applications in the food packaging systems. Technological considerations associated with the natural colorantresponsive films, smart packaging, biopolymers, and importance of natural colorants versus synthetic dyes are investigated. In practice, the most common designed colorimetric indicators for monitoring gas and temperature changes and application of relevant smart films in real food models have also been discussed. Gas and time-temperature indicators provide a rapid, reliable, and online assessment and a visual indication of the food product quality level, usually through a color change, which is directly related to gas and temperature conditions during distribution and storage of relevant food products. However, future studies need to consider main points such as cost, consumers' acceptance, and confidence, regulatory aspects (i.e., labeling) and multifunctionality of smart packaging to be commercially sustainable.

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“…Thus, the combination of sensor data and predictive models is one innovative strategy to support cold chain management and reduce food waste [2]. This is mainly performed by optimizing logistic decisions, display rotation at the retailer site, dynamic pricing, and an efficient use of the sales window [3][4][5]. The need to reduce food waste is urgent for perishable products with a high use of resources, such as meat.…”

Section: Introductionmentioning

confidence: 99%

“…For dynamic shelf-life predictions in real-time, an accurate modeling of the microbial growth of spoilage organisms as function of environmental parameters such as temperature is required [2,16]. This dynamic growth modeling approach provides successful predictions of the remaining shelf-life, shown for example, for aerobe packed products such as fresh pork and poultry filets under real chain conditions [5,14,17]. For achieving this goal, the identification and modeling of a specific spoilage organism (SSO) is crucial for the accuracy of the predictions because these organisms dominate the microbial growth and thus determine the deterioration and spoilage kinetics of the product [7].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains

Albrecht

Mittler

Hebel

et al. 2021

Foods

Self Cite

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The high perishability of fresh meat results in short sales and consumption periods, which can lead to high amounts of food waste, especially when a fixed best-before date is stated. Thus, the aim of this study was the development of a real-time dynamic shelf-life criterion (DSLC) for fresh pork filets based on a multi-model approach combining predictive microbiology and sensory modeling. Therefore, 647 samples of ma-packed pork loin were investigated in isothermal and non-isothermal storage trials. For the identification of the most suitable spoilage predictors, typical meat quality parameters (pH-value, color, texture, and sensory characteristics) as well as microbial contamination (total viable count, Pseudomonas spp., lactic acid bacteria, Brochothrix thermosphacta, Enterobacteriaceae) were analyzed at specific investigation points. Dynamic modeling was conducted using a combination of the modified Gompertz model (microbial data) or a linear approach (sensory data) and the Arrhenius model. Based on these models, a four-point scale grading system for the DSLC was developed to predict the product status and shelf-life as a function of temperature data in the supply chain. The applicability of the DSLC was validated in a pilot study under real chain conditions and showed an accurate real-time prediction of the product status.

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

Cited by 35 publications

References 46 publications

Modelling the inhibitors of cold supply chain using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

Modelling the inhibitors of cold supply chain using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

Smart monitoring of gas/temperature changes within food packaging based on natural colorants

A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains

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