Table of Contents Author Guidelines Submit a Manuscript
Journal of Spectroscopy
Volume 2015, Article ID 651810, 10 pages
http://dx.doi.org/10.1155/2015/651810
Research Article

Identification and Disease Index Inversion of Wheat Stripe Rust and Wheat Leaf Rust Based on Hyperspectral Data at Canopy Level

1College of Agriculture and Biotechnology, China Agricultural University, Beijing 100193, China
2Kaifeng Experimental Station of China Agricultural University, Kaifeng 475004, China

Received 9 March 2015; Accepted 8 June 2015

Academic Editor: Gianfranco Giubileo

Copyright © 2015 Hui Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Z. Q. Li and S. M. Zeng, Wheat Rust in China, China Agriculture Press, Beijing, China, 2002.
  2. A. M. Wan, X. M. Chen, and Z. H. He, “Wheat stripe rust in China,” Australian Journal of Agricultural Research, vol. 58, no. 6, pp. 605–619, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. W. Chen, C. Wellings, X. Chen, Z. Kang, and T. Liu, “Wheat stripe (yellow) rust caused by Puccinia striiformis f. sp. tritici,” Molecular Plant Pathology, vol. 15, no. 5, pp. 433–446, 2014. View at Publisher · View at Google Scholar · View at Scopus
  4. R. L. Pu and P. Gong, Hyperspectral Remote Sensing and Its Applications, Higher Education Press, Beijing, China, 2000.
  5. J. S. West, C. Bravo, R. Oberti, D. Lemaire, D. Moshou, and H. A. McCartney, “The potential of optical canopy measurement for targeted control of field crop diseases,” Annual Review of Phytopathology, vol. 41, pp. 593–614, 2003. View at Publisher · View at Google Scholar · View at Scopus
  6. T. Mewes, J. Franke, and G. Menz, “Spectral requirements on airborne hyperspectral remote sensing data for wheat disease detection,” Precision Agriculture, vol. 12, no. 6, pp. 795–812, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. H. G. Wang, J. B. Guo, and Z. H. Ma, “Monitoring wheat stripe rust using remote sensing technologies in China,” in Computer and Computing Technologies in Agriculture V, vol. 370 of IFIP Advances in Information and Communication Technology, pp. 163–175, Springer, Berlin, Germany, 2012. View at Publisher · View at Google Scholar
  8. M. Y. Huang, W. J. Huang, L. Y. Liu et al., “Spectral reflectance feature of winter wheat single leaf infected with stripe rust and severity level inversion,” Transactions of the CSAE, vol. 20, no. 1, pp. 176–180, 2004. View at Google Scholar
  9. H. An, H. G. Wang, R. Y. Liu, C. J. Cai, and Z. H. Ma, “Preliminary study on spectral characteristics of single leaf infected by Puccinia striiformis,” China Plant Protection, vol. 25, no. 11, pp. 8–11, 2005. View at Google Scholar
  10. J. L. Zhao, L. S. Huang, W. J. Huang et al., “Hyperspectral measurements of severity of stripe rust on individual wheat leaves,” European Journal of Plant Pathology, vol. 139, no. 2, pp. 401–411, 2014. View at Publisher · View at Google Scholar · View at Scopus
  11. D. Moshou, C. Bravo, J. West, S. Wahlen, A. McCartney, and H. Ramon, “Automatic detection of ‘yellow rust’ in wheat using reflectance measurements and neural networks,” Computers and Electronics in Agriculture, vol. 44, no. 3, pp. 173–188, 2004. View at Publisher · View at Google Scholar · View at Scopus
  12. J. B. Jiang, Y. H. Chen, and W. J. Huang, “Using hyperspectral derivative indices to diagnose severity of winter wheat stripe rust,” Optical Technique, vol. 33, no. 4, pp. 620–623, 2007. View at Google Scholar · View at Scopus
  13. J. Zhang, L. yuan, R. Pu, R. W. Loraamm, G. Yang, and J. Wang, “Comparison between wavelet spectral features and conventional spectral features in detecting yellow rust for winter wheat,” Computers and Electronics in Agriculture, vol. 100, pp. 79–87, 2014. View at Publisher · View at Google Scholar · View at Scopus
  14. L. Y. Liu, M. Y. Huang, W. J. Huang et al., “Monitoring stripe rust disease of winter wheat using multi-temporal hyperspectral airborne data,” Journal of Remote Sensing, vol. 8, no. 3, pp. 275–281, 2004. View at Google Scholar
  15. W. J. Huang, D. W. Lamb, Z. Niu, Y. J. Zhang, L. Y. Liu, and J. H. Wang, “Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging,” Precision Agriculture, vol. 8, no. 4-5, pp. 187–197, 2007. View at Publisher · View at Google Scholar · View at Scopus
  16. W. F. Leng, H. G. Wang, Y. Xu, and Z. H. Ma, “Preliminary study on monitoring wheat stripe rust with using UAV,” Acta Phytopathologica Sinica, vol. 42, no. 2, pp. 202–205, 2012. View at Google Scholar
  17. L. Y. Liu, X. Y. Song, C. J. Li, L. Qi, W. J. Huang, and J. H. Wang, “Monitoring and evaluation of the diseases of and yield winter wheat from multi-temporal remotely-sensed data,” Transactions of the Chinese Society of Agricultural Engineering, vol. 25, no. 1, pp. 137–143, 2009. View at Google Scholar · View at Scopus
  18. J. B. Guo, C. Huang, H. G. Wang, and Z. H. Ma, “Preliminary study on remote sensing monitoring wheat stripe rust based on SPOT5 image,” Acta Phytophylacica Sinica, vol. 36, no. 5, pp. 473–474, 2009. View at Google Scholar
  19. S. Dutta, S. K. Singh, and M. Khullar, “A case study on forewarning of yellow rust affected areas on wheat crop using satellite data,” Journal of the Indian Society of Remote Sensing, vol. 42, no. 2, pp. 335–342, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. D. Ashourloo, M. R. Mobasheri, and A. Huete, “Developing two spectral disease indices for detection of wheat leaf rust (Pucciniatriticina),” Remote Sensing, vol. 6, no. 6, pp. 4723–4740, 2014. View at Publisher · View at Google Scholar · View at Scopus
  21. D. Ashourloo, M. R. Mobasheri, and A. Huete, “Evaluating the effect of different wheat rust disease symptoms on vegetation indices using hyperspectral measurements,” Remote Sensing, vol. 6, no. 6, pp. 5107–5123, 2014. View at Google Scholar
  22. R. Devadas, D. W. Lamb, S. Simpfendorfer, and D. Backhouse, “Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves,” Precision Agriculture, vol. 10, no. 6, pp. 459–470, 2009. View at Publisher · View at Google Scholar · View at Scopus
  23. L. Yuan, J. C. Zhang, J. L. Zhao, W. J. Huang, and J. H. Wang, “Differentiation of yellow rust and powdery mildew in winter wheat and retrieving of disease severity based on leaf level spectral analysis,” Spectroscopy and Spectral Analysis, vol. 33, no. 6, pp. 1608–1614, 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. H. B. Qiao, B. Xia, X. M. Ma, D. F. Cheng, and Y. L. Zhou, “Identification of damage by diseases and insect pests in winter wheat,” Journal of Triticeae Crops, vol. 30, no. 4, pp. 770–774, 2010. View at Google Scholar
  25. X. L. Li, Z. H. Ma, L. L. Zhao, J. H. Li, and H. G. Wang, “Early diagnosis of wheat stripe rust and wheat leaf rust using near infrared spectroscopy,” Spectroscopy and Spectral Analysis, vol. 33, no. 10, pp. 2661–2665, 2013. View at Publisher · View at Google Scholar · View at Scopus
  26. A. A. Gitelson, M. N. Merzlyak, and O. B. Chivkunova, “Optical properties and nondestructive estimation of anthocyanin content in plant leaves,” Photochemistry and Photobiology, vol. 74, no. 1, pp. 38–45, 2001. View at Publisher · View at Google Scholar · View at Scopus
  27. M. S. Kim, C. S. T. Daughtry, E. W. Chappelle, J. E. McMurtrey, and C. L. Walthall, “The use of high spectral resolution bands for estimating absorbed photosynthetically active radiation (APAR),” in Proceedings of the 6th International Symposium on Physical Measurements and Signatures in Remote Sensing, pp. 299–306, Val-d'Isère, France, 1994.
  28. J. A. Gamon, L. Serrano, and J. S. Surfus, “The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels,” Oecologia, vol. 112, no. 4, pp. 492–501, 1997. View at Publisher · View at Google Scholar · View at Scopus
  29. M. N. Merzlyak, A. A. Gitelson, O. B. Chivkunova, and V. Y. Rakitin, “Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening,” Physiologia Plantarum, vol. 106, no. 1, pp. 135–141, 1999. View at Publisher · View at Google Scholar · View at Scopus
  30. D. Haboudane, J. R. Miller, E. Pattey, P. J. Zarco-Tejada, and I. B. Strachan, “Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture,” Remote Sensing of Environment, vol. 90, no. 3, pp. 337–352, 2004. View at Publisher · View at Google Scholar · View at Scopus
  31. J. Peñuelas, J. Piñol, R. Ogaya, and I. Filella, “Estimation of plant water concentration by the reflectance Water Index WI (R900/R970),” International Journal of Remote Sensing, vol. 18, no. 13, pp. 2869–2875, 1997. View at Publisher · View at Google Scholar · View at Scopus
  32. X. C. Zhang, J. Z. Wu, and Y. Xu, Near-Infrared Spectroscopy and Its Application in Modern Agriculture, Publishing House of Electronics Industry, Beijing, China, 2012.
  33. A. Quinquis, “A few practical applications of wavelet packets,” Digital Signal Processing, vol. 8, no. 1, pp. 49–60, 1998. View at Publisher · View at Google Scholar · View at Scopus
  34. R. W. Kennard and L. A. Stone, “Computer aided design of experiments,” Technometrics, vol. 11, no. 1, pp. 137–148, 1969. View at Publisher · View at Google Scholar
  35. C. Cortes and V. Vapnik, “Support-vector networks,” Machine Learning, vol. 20, no. 3, pp. 273–297, 1995. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  36. C. C. Chang and C. J. Lin, “LIBSVM: a library for support vector machines,” ACM Transactions on Intelligent Systems and Technology, vol. 2, no. 3, article 27, 2011. View at Publisher · View at Google Scholar · View at Scopus
  37. T. M. Cover and P. E. Hart, “Nearest neighbor pattern classification,” IEEE Transactions on Information Theory, vol. 13, no. 1, pp. 21–27, 1967. View at Publisher · View at Google Scholar
  38. R. F. Line, “Stripe rust of wheat and barley in North America: a retrospective historical review,” Annual Review of Phytopathology, vol. 40, pp. 75–118, 2002. View at Publisher · View at Google Scholar · View at Scopus
  39. J. Kuckenberg, I. Tartachnyk, and G. Noga, “Detection and differentiation of nitrogen-deficiency, powdery mildew and leaf rust at wheat leaf and canopy level by laser-induced chlorophyll fluorescence,” Biosystems Engineering, vol. 103, no. 2, pp. 121–128, 2009. View at Publisher · View at Google Scholar · View at Scopus