The Plant Pathology Journal

The Korean Society of Plant Pathology (한국식물병리학회)
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Visual Analysis for Detection and Quantification of Pseudomonas cichorii Disease Severity in Tomato Plants

  • Rajendran, Dhinesh Kumar (Division of Biotechnology, Chonbuk National University) ;
  • Park, Eunsoo (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Nagendran, Rajalingam (Division of Biotechnology, Chonbuk National University) ;
  • Hung, Nguyen Bao (Division of Biotechnology, Chonbuk National University) ;
  • Cho, Byoung-Kwan (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Kim, Kyung-Hwan (Molecular Breeding Division, National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Lee, Yong Hoon (Division of Biotechnology, Chonbuk National University)
  • Received : 2016.01.31
  • Accepted : 2016.03.13
  • Published : 2016.08.01
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Abstract

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 (${\geq}10^6cfu/ml$) 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 (${\Phi}PSII$) and non-photochemical quenching (NPQ) preceded the appearance of visible symptoms, but maximum quantum efficiency of PSII ($F_v/F_m$) 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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References

  1. Belin, E., Rousseau. D., Boureau, T. and Caffier, V. 2013. Thermography versus chlorophyll fluorescence imaging for detection and quantification of apple scab. Comput. Electron. Agric. 90:159-163. https://doi.org/10.1016/j.compag.2012.09.014
  2. Berger, S., Papadopoulos, M., Schreiber, U., Kaiser, W. and Roitsch T. 2004. Complex regulation of gene expression, photosynthesis and sugar levels by pathogen infection in tomato. Physiol. Plant. 122:419-428. https://doi.org/10.1111/j.1399-3054.2004.00433.x
  3. Berger, S., Sinha, A. K. and Roitsch, T. 2007. Plant physiology meets phytopathology: plant primary metabolism and plantpathogen interactions. J. Exp. Bot. 58:4019-4026. https://doi.org/10.1093/jxb/erm298
  4. Bilgin, D. D., Zavala, J. A., Zhu, J., Clough, S. J., Ort, D. R. and DeLucia, E. H. 2010. Biotic stress globally downregulates photosynthesis genes. Plant Cell Environ. 33:1597-1613. https://doi.org/10.1111/j.1365-3040.2010.02167.x
  5. Bonfig, K. B., Schreiber, U., Gabler, A., Roitsch, T. and Berger, S. 2006. Infection with virulent and avirulent P. syringae strains differentially affects photosynthesis and sink metabolism in Arabidopsis leaves. Planta 225:1-12. https://doi.org/10.1007/s00425-006-0303-3
  6. Chaerle, L., Hagenbeek, D., De Bruyne, E., Valcke, R. and Van Der Straeten, D. 2004. Thermal and chlorophyll-fluorescence imaging distinguish plant-pathogen interactions at an early stage. Plant Cell Physiol. 45:887-896. https://doi.org/10.1093/pcp/pch097
  7. Delalieux, S., Van Aardt, J., Keulemans, W., Schrevens, E. and Coppin, P. 2007. Detection of biotic stress (Venturia inaequalis) in apple trees using hyperspectral data: non-parametric statistical approaches and physiological implications. Eur. J. Agron. 27:130-143. https://doi.org/10.1016/j.eja.2007.02.005
  8. Dempsey, D. A. and Klessig, D. F. 2012. SOS: too many signals for systemic acquired resistance? Trends Plant Sci. 17:538-545. https://doi.org/10.1016/j.tplants.2012.05.011
  9. Ehness, R., Ecker, M., Godt, D. E. and Roitsch, T. 1997. Glucose and stress independently regulate source and sink metabolism and defense mechanisms via signal transduction pathways involving protein phosphorylation. Plant Cell 9:1825-1841. https://doi.org/10.1105/tpc.9.10.1825
  10. Farissi, M., Ghoulam, C. and Bouizgaren, A. 2013. Changes in water deficit saturation and photosynthetic pigments of alfalfa populations under salinity and assessment of proline role in salt tolerance. Agric. Sci. Res. J. 3:29-35.
  11. Furbank, R. T. and Tester, M. 2011. Phenomics technologies to relieve the phenotyping bottleneck. Trends Plant Sci. 16:635-644. https://doi.org/10.1016/j.tplants.2011.09.005
  12. Hung, N. B., Ramkumar, G. and Lee, Y. H. 2014. An effector gene hopA1 influences on virulence, host specificity, and lifestyles of Pseudomonas cichorii JBC1. Res. Microbiol. 165:620-629. https://doi.org/10.1016/j.resmic.2014.08.001
  13. Kangasjarvi, S., Neukermans, J., Li, S., Aro, E. M. and Noctor, G. 2012. Photosynthesis, photorespiration, and light signaling in defense responses. J. Exp. Bot. 63:1619-1636. https://doi.org/10.1093/jxb/err402
  14. Kolber, Z., Klimov, D., Ananyev, G., Rascher, U., Berry, J. and Osmond, B. 2005. Measuring photosynthetic parameters at a distance: laser induced fluorescence transient (LIFT) method for remote measurements of photosynthesis in terrestrial vegetation. Photosynth. Res. 84:121-129. https://doi.org/10.1007/s11120-005-5092-1
  15. Lee, W. H., Kim, M. S., Lee, H. S., Delwiche, S. R., Bae, H. H., Kim, D. Y. and Cho, B. K. 2014. Hyperspectral near-infrared imaging for the detection of physical damages of pear. J. Food Eng. 130:1-7. https://doi.org/10.1016/j.jfoodeng.2013.12.032
  16. Looseley, M. E. and Newton, A. C. 2014. Assessing the consequences of microbial infection in field trials: seen, unseen, beneficial, parasitic and pathogenic. Agronomy 4:302-321. https://doi.org/10.3390/agronomy4020302
  17. Murchie, E. H. and Lawson, T. 2013. Chlorophyll fluorescence analysis: a guide to good practice and understanding some new applications. J. Exp. Bot. 64:3983-3998. https://doi.org/10.1093/jxb/ert208
  18. Nagendran, R. and Lee, Y. H. 2015. Green and red light reduces the disease severity by Pseudomonas cichorii JBC1 in tomato plants via upregulation of defense-related gene expression. Phytopathology 105:412-418. https://doi.org/10.1094/PHYTO-04-14-0108-R
  19. Pauwelyn, E., Vanhouteghem, K., Cottyn, B., De Vos, P., Maes, M., Bleyaert, P. and Hofte, M. 2011. Epidemiology of Pseudomonas cichorii, the cause of lettuce midrib rot. J. Phytopathol. 159:298-305. https://doi.org/10.1111/j.1439-0434.2010.01764.x
  20. Perez-Bueno, M. L., Pineda, M., Diaz-Casado, E. and Baron, M. 2015. Spatial and temporal dynamics of primary and secondary metabolism in Phaseolus vulgaris challenged by Pseudomonas syringae. Physiol. Plant. 153:161-174. https://doi.org/10.1111/ppl.12237
  21. Pineda, M., Olejnickova, J., Csefalvay, L. and Baron, M. 2011. Tracking viral movement in plants by means of chlorophyll fluorescence imaging. J. Plant Physiol. 168:2035-2040. https://doi.org/10.1016/j.jplph.2011.06.013
  22. Purcell, D. E., O'Shea, M. G., Johnson, R. A. and Kokot, S. 2009. Near-infrared spectroscopy for the prediction of disease ratings for Fiji leaf gall in sugarcane clones. Appl. Spectrosc. 63:450-457. https://doi.org/10.1366/000370209787944370
  23. Refshauge, S. J., Nayudu, M., Vranjic, J. and Bock, C. H. 2010. Infection and dispersal processes of Pseudomonas syringae pv. coriandricola on coriander. Phytopathol. Mediterr. 49:42-50.
  24. Rodriguez-Moreno, L., Pineda, M., Soukupova, J., Macho, A. P., Beuzon, C. R., Baron, M. and Ramos, C. 2008. Early detection of bean infection by Pseudomonas syringae in asymptomatic leaf areas using chlorophyll fluorescence imaging. Photosynth. Res. 96:27-35. https://doi.org/10.1007/s11120-007-9278-6
  25. Rojas, C. M., Senthil-Kumar, M., Tzin, V. and Mysore, K. S. 2014. Regulation of primary plant metabolism during plantpathogen interactions and its contribution to plant defense. Front. Plant Sci. 5:17.
  26. Stromberg, K. D., Kinkel, L. L. and Leonard, K. J. 1999. Relationship between phyllosphere population sizes of Xanthomonas translucens pv. translucens and bacterial leaf streak severity on wheat seedlings. Phytopathology 89:131-135. https://doi.org/10.1094/PHYTO.1999.89.2.131
  27. Tao, Y., Xie, Z., Chen, W., Glazebrook, J., Chang, H. S., Han, B., Zhu, T., Zou, G. and Katagiri, F. 2003. Quantitative nature of Arabidopsis responses during compatible and incompatible interactions with the bacterial pathogen Pseudomonas syringae. Plant Cell 15:317-330. https://doi.org/10.1105/tpc.007591
  28. Uppalapati, S. R., Ishiga, Y., Wangdi, T., Urbanczyk-Wochniak, E., Ishiga, T., Mysore, K. S. and Bender, C. L. 2008. Pathogenicity of Pseudomonas syringae pv. tomato on tomato seedlings: phenotypic and gene expression analyses of the virulence function of coronatine. Mol. Plant-Microbe Interact. 21:383-395. https://doi.org/10.1094/MPMI-21-4-0383
  29. Wagner, A., Michalek, W. and Jamiokowska, A. 2006. Chlorophyll fluorescence measurements as indicators of fusariosis severity in tomato plants. Agron. Res. 4:461-464.
  30. Wang, M., Xiong, Y., Ling, N., Feng, X., Zhong, Z., Shen, Q. and Guo, S. 2013. Detection of the dynamic response of cucumber leaves to fusaric acid using thermal imaging. Plant Physiol. Biochem. 66:68-76. https://doi.org/10.1016/j.plaphy.2013.02.004
  31. Yu, S. M. and Lee, Y. H. 2012. First report of Pseudomonas cichorii associated with leaf spot on soybean in South Korea. Plant Dis. 96:142.
  32. Zou, J., Rodriguez-Zas, S., Aldea, M., Li, M., Zhu, J., Gonzalez, D. O., Vodkin, L. O., DeLucia, E. and Clough, S. J. 2005. Expression profiling soybean response to Pseudomonas syringae reveals new defense-related genes and rapid HR-specific downregulation of photosynthesis. Mol. Plant-Microbe Interact. 18:1161-1174. https://doi.org/10.1094/MPMI-18-1161

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