The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Reducing food losses by intelligent food logistics
Open accessAbstract
The need to feed an ever-increasing world population makes it obligatory to reduce the millions of tons of avoidable perishable waste along the food supply chain. A considerable share of these losses is caused by non-optimal cold chain processes and management. This Theme Issue focuses on technologies, models and applications to monitor changes in the product shelf life, defined as the time remaining until the quality of a food product drops below an acceptance limit, and to plan successive chain processes and logistics accordingly to uncover and prevent invisible or latent losses in product quality, especially following the first-expired-first-out strategy for optimized matching between the remaining shelf life and the expected transport duration. This introductory article summarizes the key findings of this Theme Issue, which brings together research study results from around the world to promote intelligent food logistics. The articles include three case studies on the cold chain for berries, bananas and meat and an overview of different post-harvest treatments. Further contributions focus on the required technical solutions, such as the wireless sensor and communication system for remote quality supervision, gas sensors to detect ethylene as an indicator of unwanted ripening and volatile components to indicate mould infections. The final section of this introduction discusses how improvements in food quality can be targeted by strategic changes in the food chain.
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Cites
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Food waste within food supply chains: quantification and potential for change to 2050
Parfitt, J., Barthel, M., & Macnaughton, S. (2010) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2010.0126 · Cited by 3,197 · cited 4×
“Oversupply plays an important role in affluent economies [14], where people can afford to throw food away.”
BackgroundInfluentialvan der Vorst, J. G. A. J., Tromp, S.-O., & Zee, D.-J. V. D. (2009) · International Journal of Production Research · doi:10.1080/00207540802356747 · Cited by 457
Applicability of Time‐Temperature Indicators as Shelf Life Monitors of Food Products
TAOUKIS, P. S., & LABUZA, T. P. (1989) · Journal of Food Science · doi:10.1111/j.1365-2621.1989.tb07882.x · Cited by 387
Postharvest treatments of fresh produce
Mahajan, P. V., Caleb, O. J., Singh, Z., Watkins, C. B., & Geyer, M. (2014) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2013.0309 · Cited by 386
Creating sustainable fresh food supply chains through waste reduction
Kaipia, R., Dukovska‐Popovska, I., & Loikkanen, L. (2013) · International Journal of Physical Distribution & Logistics Management · doi:10.1108/ijpdlm-11-2011-0200 · Cited by 244
Food Losses and Waste in China and Their Implication for Water and Land
Liu, J., Lundqvist, J., Weinberg, J., & Gustafsson, J. (2013) · Environmental Science & Technology · doi:10.1021/es401426b · Cited by 241
Strategic supply chain management : the five disciplines for top performance
Cohen, S., & Roussel, J. (2005) · Cited by 233
Development of a Safety Monitoring and Assurance System for chilled food products
Koutsoumanis, K., Taoukis, P., & Nychas, G. E. (2004) · International Journal of Food Microbiology · doi:10.1016/j.ijfoodmicro.2004.10.024 · Cited by 153
Shelf life modelling for first-expired-first-out warehouse management
Hertog, M., Uysal, I., McCarthy, U., VERLINDEN, B. E., & Nicolaï, B. M. (2014) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2013.0306 · Cited by 152
Self-citation
Cited by
Internet of things and supply chain management: A literature review
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019) · International Journal of Production Research · doi:10.1080/00207543.2017.1402140 · Cited by 1,501
Global food security – Issues, challenges and technological solutions
Mc Carthy, U., Uysal, I., Badia-Melis, R., Mercier, S., O'Donnell, C., & Ktenioudaki, A. (2018) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2018.05.002 · Cited by 432
Self-citationPorat, R., Lichter, A., Terry, L. A., Harker, R., & Buzby, J. (2018) · Postharvest Biology and Technology · doi:10.1016/j.postharvbio.2017.11.019 · Cited by 420
Karanth, S., Feng, S., Patra, D., & Pradhan, A. K. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1198124 · Cited by 404
Time-temperature abuse in the food cold chain: Review of issues, challenges, and recommendations
Ndraha, N., Hsiao, H.-I., Vlajic, J., Yang, M.-F., & Lin, H.-T. V. (2018) · Food Control · doi:10.1016/j.foodcont.2018.01.027 · Cited by 396
Metadata
- Authors
- Jedermann, R., Nicometo, M., Uysal, I., & Lang, W.
- Venue
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
- Publisher
- The Royal Society
- Published
- 2014-06-13
- Volume
- 372
- Issue
- 2017
- Pages
- 20130302
- ISSN
- 1364-503X (ISSN-L)
- 1471-2962
- OpenAlex
- W2133852638
- Cited by
- 323
- References
- 20
- FWCI
- 26.40
- Type
- journal article
- Language
- en
- Open access
- green
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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.
