Detection of Huanglongbing (citrus greening) based on hyperspectral image analysis and PCR |
| |
| Authors: | Kejian WANG Dongmei GUO Yao ZHANG Lie DENG Rangjin XIE Qiang LV Shilai YI Yongqiang ZHENG Yanyan MA Shaolan HE |
| |
| Institution: | 1. Southwest University/Citrus Research Institute of Chinese Academy of Agricultural Sciences, Chongqing 400712, China2. National Agricultural Technology Extension and Service Center, Beijing 100125, China3. Chengdu Plant Quarantine Station, Chengdu 610000, China4. Key Laboratory of Modern Precision Agriculture System Integration Research, China Agricultural University, Beijing 100083, China |
| |
| Abstract: | Huanglongbing (HLB, citrus greening) is one of the most serious quarantine diseases of citrus worldwide. To monitor in real-time, recognize diseased trees, and efficiently prevent and control HLB disease in citrus, it is necessary to develop a rapid diagnostic method to detect HLB infected plants without symptoms. This study used Newhall navel orange plants as the research subject, and collected normal color leaf samples and chlorotic leaf samples from a healthy orchard and an HLB-infected orchard, respectively. First, hyperspectral data of the upper and lower leaf surfaces were obtained, and then the polymerase chain reaction (PCR) was used to detect the HLB bacterium in each leaf. The PCR test results showed that all samples from the healthy orchard were negative, and a portion of the samples from the infected orchard were positive. According to these results, the leaf samples from the orchards were divided into disease-free leaves and HLB-positive leaves, and the least squares support vector machine recognition model was established based on the leaf hyperspectral reflectance. The effect on the model of the spectra obtained from the upper and lower leaf surfaces was investigated and different pretreatment methods were compared and analyzed. It was observed that the HLB recognition rate values of the calibration and validation sets based on upper leaf surface spectra under 9-point smoothing pretreatment were 100% and 92.5%, respectively. The recognition rate values based on lower leaf surface spectra under the second-order derivative pretreatment were also 100% and 92.5%, respectively. Both upper and lower leaf surface spectra were available for recognition of HLB-infected leaves, and the HLB PCR-positive leaves could be distinguished from the healthy by the hyperspectral modeling analysis. The results of this study show that early and nondestructive detection of HLB-infected leaves without symptoms is possible, which provides a basis for the hyperspectral diagnosis of citrus with HLB. |
| |
| Keywords: | citrus HLB hyperspectral identification PCR |
|
| 点击此处可从《》浏览原始摘要信息 |
| 点击此处可从《》下载免费的PDF全文 |
|
