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Detection of Huanglongbing (citrus greening) based on hyperspectral image analysis and PCR
Kejian WANG, Dongmei GUO, Yao ZHANG, Lie DENG, Rangjin XIE, Qiang LV, Shilai YI, Yongqiang ZHENG, Yanyan MA, Shaolan HE
《农业科学与工程前沿（英文）》 2019年 第6卷 第2期 页码 172-180 doi: 10.15302/J-FASE-2019256
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.
Seyed Saeed HOSEINI, Mohammad Amin SOBATI
《能源前沿（英文）》 2019年 第13卷 第4期 页码 636-657 doi: 10.1007/s11708-019-0646-7
关键词： water in diesel emulsion fuel hydrophilic-lipophilic balance (HLB) response surface methodology (RSM) emulsion stability engine performance exhaust emission
标题 作者 时间 类型 操作
Detection of Huanglongbing (citrus greening) based on hyperspectral image analysis and PCR
Kejian WANG, Dongmei GUO, Yao ZHANG, Lie DENG, Rangjin XIE, Qiang LV, Shilai YI, Yongqiang ZHENG, Yanyan MA, Shaolan HE
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