Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems
Hyperspectral imaging covering the spectral range of 384–1034 nm combined with chemometric methods was used to detect Sclerotinia sclerotiorum (SS) on oilseed rape stems by two sample sets (60 healthy and 60 infected stems for each set). Second derivative spectra and PCA loadings were used to select...
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MDPI AG
2018-01-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/1/123 |
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| author | Wenwen Kong Chu Zhang Weihao Huang Fei Liu Yong He |
| author_facet | Wenwen Kong Chu Zhang Weihao Huang Fei Liu Yong He |
| author_sort | Wenwen Kong |
| collection | DOAJ |
| description | Hyperspectral imaging covering the spectral range of 384–1034 nm combined with chemometric methods was used to detect Sclerotinia sclerotiorum (SS) on oilseed rape stems by two sample sets (60 healthy and 60 infected stems for each set). Second derivative spectra and PCA loadings were used to select the optimal wavelengths. Discriminant models were built and compared to detect SS on oilseed rape stems, including partial least squares-discriminant analysis, radial basis function neural network, support vector machine and extreme learning machine. The discriminant models using full spectra and optimal wavelengths showed good performance with classification accuracies of over 80% for the calibration and prediction set. Comparing all developed models, the optimal classification accuracies of the calibration and prediction set were over 90%. The similarity of selected optimal wavelengths also indicated the feasibility of using hyperspectral imaging to detect SS on oilseed rape stems. The results indicated that hyperspectral imaging could be used as a fast, non-destructive and reliable technique to detect plant diseases on stems. |
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| language | English |
| last_indexed | 2024-04-14T01:50:50Z |
| publishDate | 2018-01-01 |
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| spelling | doaj.art-83a023880aae472590550584287418cc2022-12-22T02:19:22ZengMDPI AGSensors1424-82202018-01-0118112310.3390/s18010123s18010123Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape StemsWenwen Kong0Chu Zhang1Weihao Huang2Fei Liu3Yong He4School of Information Engineering, Zhejiang A & F University, 666 Wusu Street, Hangzhou 311300, ChinaCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, ChinaCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, ChinaCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, ChinaCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, ChinaHyperspectral imaging covering the spectral range of 384–1034 nm combined with chemometric methods was used to detect Sclerotinia sclerotiorum (SS) on oilseed rape stems by two sample sets (60 healthy and 60 infected stems for each set). Second derivative spectra and PCA loadings were used to select the optimal wavelengths. Discriminant models were built and compared to detect SS on oilseed rape stems, including partial least squares-discriminant analysis, radial basis function neural network, support vector machine and extreme learning machine. The discriminant models using full spectra and optimal wavelengths showed good performance with classification accuracies of over 80% for the calibration and prediction set. Comparing all developed models, the optimal classification accuracies of the calibration and prediction set were over 90%. The similarity of selected optimal wavelengths also indicated the feasibility of using hyperspectral imaging to detect SS on oilseed rape stems. The results indicated that hyperspectral imaging could be used as a fast, non-destructive and reliable technique to detect plant diseases on stems.http://www.mdpi.com/1424-8220/18/1/123oilseed rape stemSclerotinia sclerotiorumsecond derivative spectradiscriminant models |
| spellingShingle | Wenwen Kong Chu Zhang Weihao Huang Fei Liu Yong He Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems Sensors oilseed rape stem Sclerotinia sclerotiorum second derivative spectra discriminant models |
| title | Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems |
| title_full | Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems |
| title_fullStr | Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems |
| title_full_unstemmed | Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems |
| title_short | Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems |
| title_sort | application of hyperspectral imaging to detect sclerotinia sclerotiorum on oilseed rape stems |
| topic | oilseed rape stem Sclerotinia sclerotiorum second derivative spectra discriminant models |
| url | http://www.mdpi.com/1424-8220/18/1/123 |
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