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Visual Analysis for Detection and Quantification of Pseudomonas cichorii Disease Severity in Tomato Plants
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  • Visual Analysis for Detection and Quantification of Pseudomonas cichorii Disease Severity in Tomato Plants
저자명
Dhinesh Kumar Rajendran, Eunsoo Park, Rajalingam Nagendran, Nguyen Bao Hung, Byoung-Kwan Cho, Kyung-Hwan Kim, Yong Hoon Lee
간행물명
The Plant Pathology Journal KCI
권/호정보
2016년|32권 4호(통권140호)|pp.300-310 (11 pages)
발행정보
한국식물병리학회|한국
파일정보
정기간행물|ENG|
PDF텍스트(2.04MB)
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영문초록

Pathogen infection in plants induces complex responses ranging from gene expression to metabolic processes in infected plants. In spite of many studies on biotic stress-related changes in host plants, little is known about the metabolic and phenotypic responses of the host plants to Pseudomonas cichorii infection based on image-based analysis. To investigate alterations in tomato plants according to disease severity, we inoculated plants with different cell densities of P. cichorii using dipping and syringe infiltration methods. High-dose inocula (≥ 10 cfu/ml) induced evident necrotic lesions within one day that corresponded to bacterial growth in the infected tissues. Among the chlorophyll fluorescence parameters analyzed, changes in quantum yield of PSII (ΦPSII) and non-photochemical quenching (NPQ) preceded the appearance of visible symptoms, but maximum quantum efficiency of PSII (F;sub>v;/sub>/F;sub>m;/sub>) was altered well after symptom development. Visible/near infrared and chlorophyll fluorescence hyperspectral images detected changes before symptom appearance at low-density inoculation. The results of this study indicate that the P. cichorii infection severity can be detected by chlorophyll fluorescence assay and hyperspectral images prior to the onset of visible symptoms, indicating the feasibility of early detection of diseases. However, to detect disease development by hyperspectral imaging, more detailed protocols and analyses are necessary. Taken together, change in chlorophyll fluorescence is a good parameter for early detection of P. cichorii infection in tomato plants. In addition, image-based visualization of infection severity before visual damage appearance will contribute to effective management of plant diseases.

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