The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
Linking microbial contamination to food spoilage and food waste: the role of smart packaging, spoilage risk assessments, and date labeling
Open accessAbstract
Ensuring a safe and adequate food supply is a cornerstone of human health and food security. However, a significant portion of the food produced for human consumption is wasted annually on a global scale. Reducing harvest and postharvest food waste, waste during food processing, as well as food waste at the consumer level, have been key objectives of improving and maintaining sustainability. These issues can range from damage during processing, handling, and transport, to the use of inappropriate or outdated systems, and storage and packaging-related issues. Microbial growth and (cross)contamination during harvest, processing, and packaging, which causes spoilage and safety issues in both fresh and packaged foods, is an overarching issue contributing to food waste. Microbial causes of food spoilage are typically bacterial or fungal in nature and can impact fresh, processed, and packaged foods. Moreover, spoilage can be influenced by the intrinsic factors of the food (water activity, pH), initial load of the microorganism and its interaction with the surrounding microflora, and external factors such as temperature abuse and food acidity, among others. Considering this multifaceted nature of the food system and the factors driving microbial spoilage, there is an immediate need for the use of novel approaches to predict and potentially prevent the occurrence of such spoilage to minimize food waste at the harvest, post-harvest, processing, and consumer levels. Quantitative microbial spoilage risk assessment (QMSRA) is a predictive framework that analyzes information on microbial behavior under the various conditions encountered within the food ecosystem, while employing a probabilistic approach to account for uncertainty and variability. Widespread adoption of the QMSRA approach could help in predicting and preventing the occurrence of spoilage along the food chain. Alternatively, the use of advanced packaging technologies would serve as a direct prevention strategy, potentially minimizing (cross)contamination and assuring the safe handling of foods, in order to reduce food waste at the post-harvest and retail stages. Finally, increasing transparency and consumer knowledge regarding food date labels, which typically are indicators of food quality rather than food safety, could also contribute to reduced food waste at the consumer level. The objective of this review is to highlight the impact of microbial spoilage and (cross)contamination events on food loss and waste. The review also discusses some novel methods to mitigate food spoilage and food loss and waste, and ensure the quality and safety of our food supply.
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The food waste hierarchy as a framework for the management of food surplus and food waste
Papargyropoulou, E., Lozano, R., K. Steinberger, J., Wright, N., & Ujang, Z. B. (2014) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2014.04.020 · Cited by 1,711
Listeria, Listeriosis, and Food Safety
(2007) · CRC Press eBooks · doi:10.1201/9781420015188 · Cited by 1,227
Internet of Things Strategic Research Roadmap
Vermesan, O., Friess, P., Guillemin, P., Gusmeroli, S., Sundmaeker, H., Bassi, A., Jubert, I. S., Mazura, M., Harrison, M., Eisenhauer, M., et al. (2022) · Internet of Things - Global Technological and Societal Trends from Smart Environments and Spaces to Green Ict · doi:10.1201/9781003338604-2 · Cited by 1,002
Big IoT data analytics: Architecture, opportunities, and open research challenges
(2017) · IEEE Access · doi:10.1109/access.2017.2689040 · Cited by 980
Intelligent food packaging: the next generation
Vanderroost, M., Ragaert, P., Devlieghere, F., & De Meulenaer, B. (2014) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2014.06.009 · Cited by 668
Harris, L. J., Farber, J. N., Beuchat, L. R., Parish, M. E., Suslow, T. V., Garrett, E. H., & Busta, F. F. (2003) · Comprehensive Reviews in Food Science and Food Safety · doi:10.1111/j.1541-4337.2003.tb00031.x · Cited by 605
Froning, G. (1995) · Poultry Science · doi:10.3382/ps.0742061 · Cited by 599
Microbial and biochemical spoilage of foods: an overview
Huis in't Veld, J. H. J. (1996) · International Journal of Food Microbiology · doi:10.1016/0168-1605(96)01139-7 · Cited by 556
Food Spoilage: Microorganisms and their prevention
Rawat, S. (2011) · HAL · Cited by 364
Cutting Food Waste through Cooperation along the Food Supply Chain
Göbel, C., Langen, N., Blumenthal, A., Teitscheid, P., & Ritter, G. (2015) · Sustainability · doi:10.3390/su7021429 · Cited by 335
Metadata
- Authors
- Karanth, S., Feng, S., Patra, D., & Pradhan, A. K.
- Venue
- Frontiers in Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2023-06-22
- Volume
- 14
- Pages
- 1198124-1198124
- ISSN
- 1664-302X (ISSN-L)
- OpenAlex
- W4381997202
- Cited by
- 404
- References
- 79
- FWCI
- 51.63
- Type
- journal article
- Language
- en
- Open access
- gold
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- Karanth, S., Feng, S., Patra, D., & Pradhan, A. K. (2023). Linking microbial contamination to food spoilage and food waste: the role of smart packaging, spoilage risk assessments, and date labeling. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2023.1198124
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.