ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2014
Quality tracing in meat supply chains.
Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Ambient Parameter Monitoring in Fresh Fruit and Vegetable Supply Chains Using Internet of Things-Enabled Sensor and Communication Technology.Foods (Basel, Switzerland) · 2022Review
- Mitigating spread of contamination in meat supply chain management using deep learning.Scientific reports · 2022Article
- A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains.Foods (Basel, Switzerland) · 2021Article
- Can the coronavirus disease be transmitted from food? A review of evidence, risks, policies and knowledge gaps.Environmental chemistry letters · 2021Review
- Implementation of Time Temperature Indicators to Improve Temperature Monitoring and Support Dynamic Shelf Life in Meat Supply Chains.Journal of packaging technology and research · 2020Article
- Reducing food losses by intelligent food logistics.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2014Article
- Communication techniques and challenges for wireless food quality monitoring.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.