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DC Field | Value | Language |
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dc.contributor.author | Wang, W | - |
dc.contributor.author | Yang, W | - |
dc.contributor.author | Li, M | - |
dc.contributor.author | Zhang, Z | - |
dc.contributor.author | Du, W | - |
dc.date.accessioned | 2023-08-30T15:23:26Z | - |
dc.date.available | 2023-08-30T15:23:26Z | - |
dc.date.issued | 2023-01-17 | - |
dc.identifier | ORCID iD: Maozhen Li https://orcid.org/0000-0002-0820-5487 | - |
dc.identifier | 6476 | - |
dc.identifier.citation | Wang, W. et al. (2023) 'A Novel Approach for Apple Freshness Prediction Based on Gas Sensor Array and Optimized Neural Network', Sensors, 23 (14), pp. 1 - 13. doi: 10.3390/s23146476. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/27093 | - |
dc.description | Data Availability Statement: Publicly available datasets were analyzed in this study. This data can be found here: s2005131@st.nuc.edu.cn (W.Y.). | en_US |
dc.description.abstract | Copyright © 2023 by the authors. Apple is an important cash crop in China, and the prediction of its freshness can effectively reduce its storage risk and avoid economic loss. The change in the concentration of odor information such as ethylene, carbon dioxide, and ethanol emitted during apple storage is an important feature to characterize the freshness of apples. In order to accurately predict the freshness level of apples, an electronic nose system based on a gas sensor array and wireless transmission module is designed, and a neural network prediction model using an improved Sparrow Search Algorithm (SSA) based on chaotic sequence (Tent) to optimize Back Propagation (BP) is proposed. The odor information emitted by apples is studied to complete an apple freshness prediction. Furthermore, by fitting the relationship between the prediction coefficient and the input vector, the accuracy benchmark of the prediction model is set, which further improves the prediction accuracy of apple odor information. Compared with the traditional prediction method, the system has the characteristics of simple operation, low cost, reliable results, mobile portability, and it avoids the damage to apples in the process of freshness prediction to realize non-destructive testing. | en_US |
dc.description.sponsorship | Shanxi Provincial Natural Science Foundation General Project, China, Project, grant number 202203021221117. Grantee: Wei Wang. | en_US |
dc.format.extent | 1 - 13 | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | MDPI | en_US |
dc.rights | Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | gas sensor array | en_US |
dc.subject | freshness prediction | en_US |
dc.subject | chaotic sequence | en_US |
dc.subject | sparrow search | en_US |
dc.title | A Novel Approach for Apple Freshness Prediction Based on Gas Sensor Array and Optimized Neural Network | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.3390/s23146476 | - |
dc.relation.isPartOf | Sensors | - |
pubs.issue | 14 | - |
pubs.publication-status | Published | - |
pubs.volume | 23 | - |
dc.identifier.eissn | 1424-8220 | - |
dc.rights.holder | The authors | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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