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Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging

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Abstract

The aim of this study was to evaluate the accuracy of the spectro-optical, photochemical reflectance index (PRI) for quantifying the disease index (DI) of yellow rust (Biotroph Puccinia striiformis) in wheat (Triticum aestivum L.), and its applicability in the detection of the disease using hyperspectral imagery. Over two successive seasons, canopy reflectance spectra and disease index (DI) were measured five times during the growth of wheat plants (3 varieties) infected with varying amounts of yellow rust. Airborne hyperspectral images of the field site were also acquired in the second season. The PRI exhibited a significant, negative, linear, relationship with DI in the first season (r 2 = 0.91, n = 64), which was insensitive to both variety and stage of crop development from Zadoks stage 3–9. Application of the PRI regression equation to measured spectral data in the second season yielded a coefficient of determination of r 2 = 0.97 (n = 80). Application of the same PRI regression equation to airborne hyperspectral imagery in the second season also yielded a coefficient of determination of DI of r 2 = 0.91 (n = 120). The results show clearly the potential of PRI for quantifying yellow rust levels in winter wheat, and as the basis for developing a proximal, or airborne/spaceborne imaging sensor of yellow rust in fields of winter wheat.

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Acknowledgments

This work was subsidized by the National High Tech R&D Program of China (2006AA10Z203, 2007AA10Z201), the National Natural Science Foundation of China (40571118), and Special Funds for Major State Basic Research Projects (2007CB714406, 2005CB121103). This work was also supported by the foundation of the State Key Laboratory of Remote Sensing Science (KQ060006) and the Ministry of Agriculture (2006-G63). The authors are grateful to Mrs. Zhihong Ma, Mr. Weiguo Li and Mrs. Hong Chang for their assistance in data collection.

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Authors and Affiliations

  1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101, China

    Wenjiang Huang, Yongjiang Zhang, Liangyun Liu & Jihua Wang

  2. National Engineering Research Center for Information Technology in Agriculture, Beijing, 100097, China

    Wenjiang Huang & Zheng Niu

  3. Precision Agriculture Research Group, School of Science and Technology, University of New England, Armidale, NSW, 2351, Australia

    David W. Lamb

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  1. Wenjiang Huang
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  2. David W. Lamb
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  3. Zheng Niu
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  4. Yongjiang Zhang
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  6. Jihua Wang
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Correspondence to David W. Lamb.

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Huang, W., Lamb, D.W., Niu, Z. et al. Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging. Precision Agric 8, 187–197 (2007). https://doi.org/10.1007/s11119-007-9038-9

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  • DOI: https://doi.org/10.1007/s11119-007-9038-9

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