Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce
| Autor: | Daniel I. Onwude, Abraham Kabutey, Barbara Sturm, Guangnan Chen, Alfadhl Yahya Khaled, Nnanna Eke-emezie |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Industry 4.0
Emerging technologies Computer science Supply chain media_common.quotation_subject Bioengineering Agricultural engineering food quality lcsh:Chemical technology 01 natural sciences lcsh:Chemistry 0404 agricultural biotechnology food distribution Chemical Engineering (miscellaneous) Quality (business) lcsh:TP1-1185 Agricultural productivity Cold chain media_common Food security Process Chemistry and Technology 010401 analytical chemistry 04 agricultural and veterinary sciences food security 040401 food science 0104 chemical sciences lcsh:QD1-999 agricultural production Food quality crop storage and processing smart digital technology |
| Zdroj: | Processes, Vol 8, Iss 1431, p 1431 (2020) |
| ISSN: | 2227-9717 |
| Popis: | Fruits and vegetables are highly nutritious agricultural produce with tremendous human health benefits. They are also highly perishable and as such are easily susceptible to spoilage, leading to a reduction in quality attributes and induced food loss. Cold chain technologies have over the years been employed to reduce the quality loss of fruits and vegetables from farm to fork. However, a high amount of losses (≈50%) still occur during the packaging, pre-cooling, transportation, and storage of these fresh agricultural produce. This study highlights the current state-of-the-art of various advanced tools employed to reducing the quality loss of fruits and vegetables during the packaging, storage, and transportation cold chain operations, including the application of imaging technology, spectroscopy, multi-sensors, electronic nose, radio frequency identification, printed sensors, acoustic impulse response, and mathematical models. It is shown that computer vision, hyperspectral imaging, multispectral imaging, spectroscopy, X-ray imaging, and mathematical models are well established in monitoring and optimizing process parameters that affect food quality attributes during cold chain operations. We also identified the Internet of Things (IoT) and virtual representation models of a particular fresh produce (digital twins) as emerging technologies that can help monitor and control the uncharted quality evolution during its postharvest life. These advances can help diagnose and take measures against potential problems affecting the quality of fresh produce in the supply chains. Plausible future pathways to further develop these emerging technologies and help in the significant reduction of food losses in the supply chain of fresh produce are discussed. Future research should be directed towards integrating IoT and digital twins for multiple shipments in order to intensify real-time monitoring of the cold chain environmental conditions, and the eventual optimization of the postharvest supply chains. This study gives promising insight towards the use of advanced technologies in reducing losses in the postharvest supply chain of fruits and vegetables. |
| Databáze: | OpenAIRE |
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