Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance Imaging
Hyperspectral imaging is a non-destructive method for the detection of chilling injury in fruit. However, the limitation of this technique is the lacking of an appropriate working parameters and a feasible discriminating model for chilling on-line sorting. This research was aimed to select the optim...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-03-01
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| Series: | Applied Sciences |
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| Online Access: | http://www.mdpi.com/2076-3417/8/4/523 |
| _version_ | 1811212759447109632 |
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| author | Huanda Lu Xinjie Yu Lijuan Zhou Yong He |
| author_facet | Huanda Lu Xinjie Yu Lijuan Zhou Yong He |
| author_sort | Huanda Lu |
| collection | DOAJ |
| description | Hyperspectral imaging is a non-destructive method for the detection of chilling injury in fruit. However, the limitation of this technique is the lacking of an appropriate working parameters and a feasible discriminating model for chilling on-line sorting. This research was aimed to select the optimal spectral resolution, scanning speed, and classification model for green jujube chilling injury detection based on hyperspectral reflectance imaging. Criminisi algorithm was firstly carried out to reconstruct the specular reflection region in spectral images before deriving mean spectra, and thus the optimal wavelengths were selected by random frog. Results showed that the Criminisi algorithm presented a desirable ability of spectral image inpainting. The linear discriminant analysis (LDA) achieved overall accuracies of 98.3% and 93.3% for two-class and three-class classification, respectively, at the speed of 20 mm/s with the spectral resolution of 5.03 nm based on selected spectral features. The results demonstrated that 20 mm/s with the spectral resolution of 5.03 nm was more feasible for the detection of green jujube chilling injury in hyperspectral imaging system due to a higher scanning efficiency, but a less data size. |
| first_indexed | 2024-04-12T05:34:42Z |
| format | Article |
| id | doaj.art-9501407ff9ef4d98b6e6801ef16d8c17 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-04-12T05:34:42Z |
| publishDate | 2018-03-01 |
| publisher | MDPI AG |
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| series | Applied Sciences |
| spelling | doaj.art-9501407ff9ef4d98b6e6801ef16d8c172022-12-22T03:45:54ZengMDPI AGApplied Sciences2076-34172018-03-018452310.3390/app8040523app8040523Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance ImagingHuanda Lu0Xinjie Yu1Lijuan Zhou2Yong He3Ningbo Institute of Technology, Zhejiang University, Ningbo 315100, ChinaNingbo Institute of Technology, Zhejiang University, Ningbo 315100, ChinaNingbo Institute of Technology, Zhejiang University, Ningbo 315100, ChinaCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, ChinaHyperspectral imaging is a non-destructive method for the detection of chilling injury in fruit. However, the limitation of this technique is the lacking of an appropriate working parameters and a feasible discriminating model for chilling on-line sorting. This research was aimed to select the optimal spectral resolution, scanning speed, and classification model for green jujube chilling injury detection based on hyperspectral reflectance imaging. Criminisi algorithm was firstly carried out to reconstruct the specular reflection region in spectral images before deriving mean spectra, and thus the optimal wavelengths were selected by random frog. Results showed that the Criminisi algorithm presented a desirable ability of spectral image inpainting. The linear discriminant analysis (LDA) achieved overall accuracies of 98.3% and 93.3% for two-class and three-class classification, respectively, at the speed of 20 mm/s with the spectral resolution of 5.03 nm based on selected spectral features. The results demonstrated that 20 mm/s with the spectral resolution of 5.03 nm was more feasible for the detection of green jujube chilling injury in hyperspectral imaging system due to a higher scanning efficiency, but a less data size.http://www.mdpi.com/2076-3417/8/4/523green jujubechilling injuryhyperspectral reflectance imagingscanning speedspectral resolutionlinear discriminant analysis (LDA) |
| spellingShingle | Huanda Lu Xinjie Yu Lijuan Zhou Yong He Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance Imaging Applied Sciences green jujube chilling injury hyperspectral reflectance imaging scanning speed spectral resolution linear discriminant analysis (LDA) |
| title | Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance Imaging |
| title_full | Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance Imaging |
| title_fullStr | Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance Imaging |
| title_full_unstemmed | Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance Imaging |
| title_short | Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance Imaging |
| title_sort | selection of spectral resolution and scanning speed for detecting green jujubes chilling injury based on hyperspectral reflectance imaging |
| topic | green jujube chilling injury hyperspectral reflectance imaging scanning speed spectral resolution linear discriminant analysis (LDA) |
| url | http://www.mdpi.com/2076-3417/8/4/523 |
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