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| Diagnosis and Monitoring of Sclerotinia Stem Rot of Oilseed Rape Using Thermal Infrared Imaging |
| CHEN Xin-xin1, 3, 4, LIU Zi-yi1, 3, 4, Lü Mei-qiao2*, ZHANG Chu1, 3, 4, YAO Jie-ni1, 2, HE Yong1, 3, 4* |
1. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
2. Jinhua Polytechnic, Jinhua 321017, China
3. Key Laboratory of Spectroscopy, Ministry of Agriculture and Rural Affairs, Hangzhou 310058，China
4. State Key Laboratory of Modern Optical Instrumentation, Zhejiang University，Hangzhou 310058, China |
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Abstract The early identification of sclerotinia sclerotiorum rot of oilseed rape was observed from the canopy and leaf scale by using the thermal infrared imager based on the UAV simulation platform. The thermal infrared image data were obtained from the canopy scale, and the temperature values of the canopy scale were extracted, and the rape leaves were monitored for acquiring the physiological index. Then, the average temperature and the maximum temperature difference were used to compare the healthy and diseased samples and one-way ANOVA was also used. The results showed that the difference in the maximum temperature difference between healthy and diseased plants was obvious, and the difference in the average temperature between healthy and diseased plants was obvious with the number of days. The single factor analysis of variance showed that there was significant difference (p<0.01) between the maximum temperature difference at the first day after rape infection. Furthermore, the physiological indexes (stomatal conductance, photosynthetic rate, carbon dioxide concentration and transpiration rate) of rapeseed were analyzed with the number of days. The changes could be used to detect the correlation between physiological index and temperature Sexual analysis. The results showed that there was a significant correlation between photosynthetic rate, carbon dioxide concentration and transpiration rate and temperature. The temperature information of the healthy and diseased areas in the diseased leaves of the samples was obtained. The thermal infrared image could visually identify the disease infection process and use the pixel value to estimate temperature difference between the health and the affected area. The healthy and diseased samples were identified by maximum temperature, minimum temperature, average temperature and maximum temperature difference. The results were compared with the single factor analysis of variance (ANOVA), showing that the maximum temperature, the minimum temperature, the maximum temperature difference and the average temperature in the healthy and infected areas were significantly different, and the lesion area temperature was higher than that of the healthy area. The single factor analysis of variance showed that there was significant difference (p<0.01) in the maximum temperature difference at the first day, and the early identification of sclerotinia sclerotiorum could be realized.
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Received: 2017-07-29
Accepted: 2018-01-12
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Corresponding Authors:
Lü Mei-qiao, HE Yong
E-mail: 421795699@qq.com；yhe@zju.edu.cn
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