Research on Strawberry Cold Chain Transportation Quality Perception Method Based on BP Neural Network
Post-harvest strawberries are hard to store and can easily rot during cold chain transportation (CCT). This leads to considerable economic losses. This paper proposes a strawberry quality perception method used in CCT, based on the correlation between environmental parameters and strawberry quality...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/17/8872 |
| _version_ | 1797496146909724672 |
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| author | Jiping Qiao Meicen Guo Yuan Wu Jin Gao Zichen Yue |
| author_facet | Jiping Qiao Meicen Guo Yuan Wu Jin Gao Zichen Yue |
| author_sort | Jiping Qiao |
| collection | DOAJ |
| description | Post-harvest strawberries are hard to store and can easily rot during cold chain transportation (CCT). This leads to considerable economic losses. This paper proposes a strawberry quality perception method used in CCT, based on the correlation between environmental parameters and strawberry quality parameters. The proposed method constructs a shelf-life prediction model based on a back propagation (BP) neural network, using four kinds of environmental parameters, including temperature, humidity, oxygen, and carbon dioxide, to perceive the quality of post-harvest strawberries, and builds a cold chain transportation quality perception system (CCT-QPS) with the help of LabVIEW software for monitoring the cold chain environment and commodity quality constantly. The results showed that the proposed method could precisely predict the remaining shelf-life of post-harvest strawberries. In addition, the proposed system could reflect the vehicle operation in real time, such as commodity quality and the internal environment of transport carriages. Moreover, the quality perception approach can inform decision making for managers and effectively improve the related regulatory measures in the strawberry supply chain. |
| first_indexed | 2024-03-10T01:59:31Z |
| format | Article |
| id | doaj.art-160de2d3072d4c248c730892e4cbeae4 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T01:59:31Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-160de2d3072d4c248c730892e4cbeae42023-11-23T12:48:21ZengMDPI AGApplied Sciences2076-34172022-09-011217887210.3390/app12178872Research on Strawberry Cold Chain Transportation Quality Perception Method Based on BP Neural NetworkJiping Qiao0Meicen Guo1Yuan Wu2Jin Gao3Zichen Yue4College of Electrical & Power Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaCollege of Electrical & Power Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaCollege of Physics & Optoelectronics, Taiyuan University of Technology, Taiyuan 030024, ChinaCollege of Electrical & Power Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaCollege of Electrical & Power Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaPost-harvest strawberries are hard to store and can easily rot during cold chain transportation (CCT). This leads to considerable economic losses. This paper proposes a strawberry quality perception method used in CCT, based on the correlation between environmental parameters and strawberry quality parameters. The proposed method constructs a shelf-life prediction model based on a back propagation (BP) neural network, using four kinds of environmental parameters, including temperature, humidity, oxygen, and carbon dioxide, to perceive the quality of post-harvest strawberries, and builds a cold chain transportation quality perception system (CCT-QPS) with the help of LabVIEW software for monitoring the cold chain environment and commodity quality constantly. The results showed that the proposed method could precisely predict the remaining shelf-life of post-harvest strawberries. In addition, the proposed system could reflect the vehicle operation in real time, such as commodity quality and the internal environment of transport carriages. Moreover, the quality perception approach can inform decision making for managers and effectively improve the related regulatory measures in the strawberry supply chain.https://www.mdpi.com/2076-3417/12/17/8872cold chain transportationquality perceptioncorrelation analysisBP neural networkshelf-life prediction |
| spellingShingle | Jiping Qiao Meicen Guo Yuan Wu Jin Gao Zichen Yue Research on Strawberry Cold Chain Transportation Quality Perception Method Based on BP Neural Network Applied Sciences cold chain transportation quality perception correlation analysis BP neural network shelf-life prediction |
| title | Research on Strawberry Cold Chain Transportation Quality Perception Method Based on BP Neural Network |
| title_full | Research on Strawberry Cold Chain Transportation Quality Perception Method Based on BP Neural Network |
| title_fullStr | Research on Strawberry Cold Chain Transportation Quality Perception Method Based on BP Neural Network |
| title_full_unstemmed | Research on Strawberry Cold Chain Transportation Quality Perception Method Based on BP Neural Network |
| title_short | Research on Strawberry Cold Chain Transportation Quality Perception Method Based on BP Neural Network |
| title_sort | research on strawberry cold chain transportation quality perception method based on bp neural network |
| topic | cold chain transportation quality perception correlation analysis BP neural network shelf-life prediction |
| url | https://www.mdpi.com/2076-3417/12/17/8872 |
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