Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Assessment of the severity of bacterial leaf blight in rice using canopy hyperspectral reflectance

  • Published:
Precision Agriculture Aims and scope Submit manuscript

Abstract

Bacterial leaf blight (BLB) is an important vascular disease of irrigated rice and serious infestations may cause a significant loss of yield. This study analyzed hyperspectral canopy reflectance spectra of two rice cultivars with different susceptibilities to BLB to establish spectral models for assessing disease severity for future site-specific management. The results indicated that wavebands from 757 to 1039 nm were the most sensitive region of the spectrum for the moderately susceptible cultivar TNG 67, whereas most narrow bands showed a significant relationship for the highly susceptible cultivar TCS 10. All the spectral indices (SIs) calculated had significant relationships with proportions of infested area in cultivar TCS 10, but only two SIs correlated significantly with cultivar TNG 67. The relation between the severity of the disease and spectral reflectance for the less susceptible cultivar TNG 67 can be improved by using a multiple linear regression approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Adhikari, T. B., Mew, T. W., & Teng, P. S. (1994). Progress of bacterial blight on rice cultivars carrying different Xa genes for resistance in the field. Plant Disease, 78, 73–77.

    Google Scholar 

  • Aldakheel, Y. Y., & Danson, F. M. (1997). Spectral reflectance of dehydrating leaves: measurements and modeling. International Journal of Remote Sensing, 18, 3683–3690. doi:10.1080/014311697216883.

    Article  Google Scholar 

  • Asner, G. P. (1998). Biophysical and biological sources of variability in canopy reflectance. Remote Sensing Environmental, 64, 234–253. doi:10.1016/S0034-4257(98)00014-5.

    Article  Google Scholar 

  • Barrett, E. C., & Curtis, L. F. (1992). Introduction to environmental remote sensing (3rd ed.). London: Chapman & Hall.

    Google Scholar 

  • Carter, G. A., & Knapp, A. K. (2001). Leaf optical properties in higher plants: Linking spectral characteristics to stress and chlorophyll concentration. American Journal of Botany, 88, 677–684. doi:10.2307/2657068.

    Article  CAS  PubMed  Google Scholar 

  • Elings, A., Reddy, P. R., Marimuthu, T., Rossing, W. A. H., Jansen, M. J. W., & Teng, P. S. (1997). Rice bacterial leaf blight: Field experiments, systems analysis and damage coefficients. Field Crops Research, 51, 113–131. doi:10.1016/S0378-4290(96)01036-2.

    Article  Google Scholar 

  • Fei, F.-W., & Wang, Y.-M. (2002). Plant protection handbook. Taichung Hsien, Taiwan, ROC: Taiwan Agricultural Chemicals and Toxic Substances Research Institute. 791 pp.

  • Forestry Images. (2008). Trees, plants, and stand types-bacterial leaf blight of rice. http://www.forestryimages.org/browse/detail.cfm?imgnum=0162039. Accessed 18 Jan 2008.

  • GER 2600 User Manual. (1996). Version 1.1. Millbrook, New York: Geophysical & Environmental Research Corporation.

  • Hall, A., Lamb, D. W., Holzapfel, B., & Louis, J. (2002). Optical remote sensing applications for viticulture—a review. Australian Journal of Grape and Wine Research, 8, 36–47. doi:10.1111/j.1755-0238.2002.tb00209.x.

    Article  Google Scholar 

  • Hsieh, S.-P.-Y. (1991). Recent status and future prospects on bacterial blight in Taiwan. In Proceedings of symposium on research of rice diseases in Taiwan. Special report no. 32 (pp. 117–130). Taichung Hsien, Taiwan, ROC: Taiwan Agricultural Research Institute.

  • Invasive Species. (2008). Invasive and exotic diseases-bacterial leaf blight of rice. No. 0162037-0162039. http://www.invasive.org/browse/subject.cfm?sub=11182. Accessed 18 Jan 2008.

  • Kauffman, H. E., Reddy, A. P. K., Hsieh, S. P. Y., & Merca, S. D. (1973). An improved technique for evaluating resistance of rice varieties to Xanthomonas oryzae pv. oryzae. Plant Dis Rep, 57, 537–541.

    Google Scholar 

  • Khush, G. S. (2005). What it will take to feed 5 billion rice consumers in 2030. Plant Molecular Biology, 59, 1–6. doi:10.1007/s11103-005-2159-5.

    Article  CAS  PubMed  Google Scholar 

  • Knippling, E. B. (1970). Physical and physiological basis for differences in reflectance of visible and near-infrared radiation from vegetation. Remote Sensing Environmental, 1, 155–159. doi:10.1016/S0034-4257(70)80021-9.

    Article  Google Scholar 

  • Kobayashi, T., Kanda, E., Kitada, K., Ishiguro, K., & Torigoe, Y. (2001). Detection of rice panicle blast with multispectral radiometer and the potential of using airborne multispectral scanners. Phytopathology, 91, 316–323. doi:10.1094/PHYTO.2001.91.3.316.

    Article  PubMed  Google Scholar 

  • Kumar, L., Schmidt, K. S., Dury, S., & Skidmore, A. K. (2001). Review of hyperspectral remote sensing and vegetation science. In F. D. Van, S. M. der Meer, & De. Jong (Eds.), Imaging spectrometry: Basic principles and prospective applications (pp. 111–155). Dordrecht, The Netherlands: Kluwer Academic Press.

    Google Scholar 

  • Lee, Y.-J., Yang, C.-M., Chang, K.-W., & Shen, Y. (2008). A simple spectral index using reflectance of 735 nm to assess nitrogen status of rice canopy. Agronomy Journal, 100, 205–212. doi:10.2134/agrojnl2007.0018.

    Article  CAS  Google Scholar 

  • Lorenzen, B., & Jensen, A. (1989). Changes in spectral properties induced in barley by cereal Powdery Mildew. Remote Sensing Environmental, 27, 201–209. doi:10.1016/0034-4257(89)90018-7.

    Article  Google Scholar 

  • Malthus, T. J., & Madeira, A. C. (1993). High resolution spectroradiometry: spectral reflectance of field bean leaves infected by Botrytis fabae. Remote Sensing Environmental, 45, 107–116. doi:10.1016/0034-4257(93)90086-D.

    Article  Google Scholar 

  • Mew, T. W. (1987). Current status and future prospects of research on bacterial blight of rice. Annual review of Phytopathology, 25, 359–382. doi:10.1146/annurev.py.25.090187.002043.

    Article  Google Scholar 

  • Muko, H., Kusaba, T., Watanabe, M., Tabei, H., & Tsuchiya, Y. (1957). Effect of major environmental factors on the development of bacterial leaf blight of rice. Annals of the Phytopathological Society of Japan, 29, 13–19.

    Google Scholar 

  • Nilsson H. E. (1985a). Remote Sensing of 2-row Barley Infected by Net Blotch Disease. Växtskyddsrapporter–Jordbruk, 34. Uppsala, Sweden: Swedish Agricultureal University, SLU.

  • Nilsson H. E. (1985b). Remote Sensing of 6-row Barley Infected by Net Blotch Disease. Växtskyddsrapporter–Jordbruk, 36. Uppsala, Sweden: Swedish Agricultureal University, SLU.

  • Ogawa, T., Tabien, R. E., Yamamoto, T., Bustro, G. A., Jr., & Ikeda, R. (1991). Breeding of near-isogenic lines for resistance to rice bacterial blight. In S. J. Banta & G. S. Argosino (Eds.), Rice genetics II (pp. 742–743). Los Banos, Philippines: International Rice Research Institute.

    Google Scholar 

  • Ou, S. H. (1985). Rice diseases (2nd ed.). Kew, England: Commonwealth Mycological Institute.

    Google Scholar 

  • Rollin, E. M., & Milton, E. J. (1998). Processing of high spectral resolution reflectance data for the retrieval of canopy water content information. Remote Sensing Environmental, 65, 86–92. doi:10.1016/S0034-4257(98)00013-3.

    Article  Google Scholar 

  • SAS Institute. (1998). SAS/STAT user’s guide, Version 8.1. Cary, NC: SAS Institute.

    Google Scholar 

  • Seager, S., Turner, E. L., Schafer, J., & Ford, E. B. (2005). Vegetation’s red edge: A possible spectroscopic biosignature of extraterrestrial plants. Astrobiology, 5, 372–390. doi:10.1089/ast.2005.5.372.

    Article  CAS  PubMed  Google Scholar 

  • Sharp, E. L., Perry, C. R., Scharen, A. L., Boatwright, G. O., Sands, D. C., Lautenschlager, L. F., et al. (1985). Monitoring cereal rust development with a spectral radiometer. Phytopathology, 75, 936–939. doi:10.1094/Phyto-75-936.

    Article  Google Scholar 

  • Singh, S., Sidhu, J. S., Huang, N., Vikal, Y., Li, Z., Brar, D. S., et al. (2001). Pyramiding three bacterial blight resistance genes (xa5, xa13 and xa21) using marker-assisted selection into indica rice cultivar PR 106. Theoretical and Applied Genetics, 102, 1011–1015. doi:10.1007/s001220000495.

    Article  CAS  Google Scholar 

  • Singh, G. P., Srivastava, M. K., Singh, R. V., & Singh, R. M. (1977). Variation in quantitative and qualitative losses caused by bacterial blight in different rice varieties. Indian Phytopathology, 3, 180–185.

    Google Scholar 

  • Srivastava, D. N. (1972). Bacterial blight of rice. Indian Phytopathology, 25, 1–16.

    Google Scholar 

  • Steven, M. D., Malthus, T. J., Demetriades-Shah, T. H., Danson, F. M., & Clark, J. A. (1990). High resolution spectral indices for crop stress. In M. D. Steven & J. A. Clark (Eds.), Applications of remote sensing in agriculture (pp. 209–227). London, UK: Butterworth.

    Google Scholar 

  • Texas Plant Disease Handbook. (2008). Rice, Oryza sativa. Bacterial Leaf Blight Symptoms on Rice. http://plantpathology.tamu.edu/Texlab/Grains/Rice/riceblb.html. Accessed 19 Jan 2008.

  • Tsai, W.-H. (1991). Prediction of rice leaf blast. In C.-C. Tu et al. (Eds.), Proceedings of symposium on research of rice diseases in Taiwan. Special report no. 32 (pp. 15–30). Taichung Hsien, Taiwan, ROC: Taiwan Agricultural Research Institute.

  • Tu, C.-C., & Chang, Y.-C. (1991). Ecology and control of sheath blight of rice. In C.-C. Tu et al. (Eds.), Proceedings of symposium on research of rice diseases in Taiwan. Special report no. 32 (pp. 65–81). Taichung Hsien, Taiwan, ROC: Taiwan Agricultural Research Institute.

  • West, J. S., Bravo, C., Oberti, R., Lemaire, D., Moshou, D., & McCartney, H. A. (2003). The potential of optical canopy measurement for targeted control of field crop disease. Annual Review of Phytopathology, 41, 593–614. doi:10.1146/annurev.phyto.41.121702.103726.

    Article  CAS  PubMed  Google Scholar 

  • Wooley, J. T. (1971). Reflectance and transmittance of light by leaves. Plant Physiology, 47, 656–662. doi:10.1104/pp.47.5.656.

    Article  Google Scholar 

  • Yang, C.-M., & Chen, R.-K. (2004). Modeling rice growth using hyperspectral reflectance data. Crop Science, 44, 1283–1290.

    Article  Google Scholar 

  • Yang, C.-M., Cheng, C.-H., & Chen, R.-K. (2007). Changes in spectral characteristics of rice canopy infested by leaf folder and brown planthopper. Crop Science, 47, 329–335. doi:10.2135/cropsci2006.05.0335.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The author wish to give thanks to Council of Agriculture (90AS-8.1.1-CI-C1 and 94AS-8.2.1.-CI-C1), Executive Yuan, Taiwan ROC for the financial support and Mr. Yih-Chang Chang, Plant Pathologist of Taiwan Agricultural Research Institute, for the assistance in identification of disease severity. The technical assistance in spectral measurements provided by Dr. Yuh-Jyuan Lee of TARI is also gratefully appreciated.

Author information

Authors and Affiliations

  1. Crop Science Division, Taiwan Agricultural Research Institute, Wufeng, Taichung Hsien, 41301, Taiwan, ROC

    Chwen-Ming Yang

Authors
  1. Chwen-Ming Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chwen-Ming Yang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yang, CM. Assessment of the severity of bacterial leaf blight in rice using canopy hyperspectral reflectance. Precision Agric 11, 61–81 (2010). https://doi.org/10.1007/s11119-009-9122-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11119-009-9122-4

Keywords

Search

Navigation