Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat
In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectrosco...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/14/6600 |
| _version_ | 1797587454040997888 |
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| author | Kun Liang Jinpeng Song Rui Yuan Zhizhou Ren |
| author_facet | Kun Liang Jinpeng Song Rui Yuan Zhizhou Ren |
| author_sort | Kun Liang |
| collection | DOAJ |
| description | In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples. |
| first_indexed | 2024-03-11T00:40:07Z |
| format | Article |
| id | doaj.art-78f22942d35b4345805e66c67a5f0679 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T00:40:07Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-78f22942d35b4345805e66c67a5f06792023-11-18T21:19:59ZengMDPI AGSensors1424-82202023-07-012314660010.3390/s23146600Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight WheatKun Liang0Jinpeng Song1Rui Yuan2Zhizhou Ren3College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, ChinaCollege of Engineering, Nanjing Agricultural University, Nanjing 210031, ChinaCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, ChinaCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, ChinaIn this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples.https://www.mdpi.com/1424-8220/23/14/6600spectroscopic techniquesfusarium head blightfingerprint regiondata fusion |
| spellingShingle | Kun Liang Jinpeng Song Rui Yuan Zhizhou Ren Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat Sensors spectroscopic techniques fusarium head blight fingerprint region data fusion |
| title | Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat |
| title_full | Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat |
| title_fullStr | Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat |
| title_full_unstemmed | Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat |
| title_short | Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat |
| title_sort | mid level data fusion combined with the fingerprint region for classification don levels defect of fusarium head blight wheat |
| topic | spectroscopic techniques fusarium head blight fingerprint region data fusion |
| url | https://www.mdpi.com/1424-8220/23/14/6600 |
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