Spectroscopy and Spectral Analysis, Volume. 42, Issue 10, 3226(2022)
Early Detection of Tomato Gray Mold Disease With Multi-Dimensional Random Forest Based on Hyperspectral Image
Fig. 2. Comparisons of reflectance of different ROIs after inoculation
(a): Tomato leaf on the 6th day after infection; (b): Different ROIs selection;(c): Comparisons of reflectivity of different ROIs; (d): Comparisons of reflectivity of leaf on the 1st and 9th day after infection
Fig. 4. Changes of spectral reflectance of samples observed for 7 consecutive data
Fig. 8. Hyperspectral curve of diseased and healthy leaves for 7 consecutive observations
(a): Consecutive 7-day reflectivity of infected leaf 1; (b): Consecutive 7-day reflectivity of infected leaf 2; (c): Consecutive 7-day reflectivity of healthy leaf 1; (b): Consecutive 7-day reflectivity of healthy leaf 2
Fig. 10. Recognition results of MDSS-SAX-SFA-MRF model
(a): SFA multidimensional spectrum; (b): SAX multidimensional spectrum; (c): SAX+SFA multidimensional spectrum
Fig. 11. Comparison results of MDSS-SAX-SFA-MRF model and SDSS-SAX-SFA-MRF model
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Rong-hua GAO, Lu FENG, Yue ZHANG, Ji-dong YUAN, Hua-rui WU, Jing-qiu GU. Early Detection of Tomato Gray Mold Disease With Multi-Dimensional Random Forest Based on Hyperspectral Image[J]. Spectroscopy and Spectral Analysis, 2022, 42(10): 3226
Category: Research Articles
Received: Aug. 11, 2021
Accepted: Mar. 28, 2022
Published Online: Nov. 23, 2022
The Author Email: Rong-hua GAO (gaorh@nercita.org.cn)