Determination of rice leaf blast disease level based on visible-near-infrared spectroscopy
A rapid determination of rice leaf blast disease based on visible-near-infrared spectroscopy was proposed. Chemometric analysis was executed on the spectra of the rice leaves with different disease level by using partial least square regression (PLSR). Three PLSR models were established based on ful...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Zhejiang University Press
2011-05-01
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| Series: | 浙江大学学报. 农业与生命科学版 |
| Subjects: | |
| Online Access: | https://www.academax.com/doi/10.3785/j.issn.1008-9209.2011.03.011 |
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| Summary: | A rapid determination of rice leaf blast disease based on visible-near-infrared spectroscopy was proposed. Chemometric analysis was executed on the spectra of the rice leaves with different disease level by using partial least square regression (PLSR). Three PLSR models were established based on full-range spectra (model 1), spectra at feature wavebands (model 2) and spectra at feature wavelengths (model 3). The determination correct rate of the disease detection level was 96.7% for model 1. By using the obtained regression coefficients of PLSR model, five feature wavebands were selected, which were at 552-558, 672-682, 719-726, 756-768 and 990-998 nm. The determination correct rate was 90% for model 2. The result showed that there was a good correlation between the disease detection level and the five selected feature wavebands. Five feature wavelengths were further selected based on the feature wavebands. The determination correct rate was 80% for model 3. It is concluded that the visible-near-infrared spectroscopy gives a good determination result and is a new way to fast determine rice leaf blast disease level. |
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| ISSN: | 1008-9209 2097-5155 |