Skip to main navigation Skip to search Skip to main content

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

Wenjiang Huang, David Lamb, Zheng Niu, Yongjiang Zhang, Liangyun Liu, Jihua Wang

Research output: Contribution to journalArticlepeer-review

370 Citations (Scopus)

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 (r² = 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 r² = 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 r² = 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.
Original languageEnglish
Pages (from-to)187-197
JournalPrecision Agriculture
Volume8
Issue number4-5
DOIs
Publication statusPublished - 31 Dec 2007

Keywords

  • Crop and Pasture Protection (Pests, Diseases and Weeds)

Fingerprint

Dive into the research topics of 'Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging'. Together they form a unique fingerprint.

Cite this