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Acta Agron Sin ›› 2013, Vol. 39 ›› Issue (08): 1469-1477.doi: 10.3724/SP.J.1006.2013.01469

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY • Previous Articles     Next Articles

Estimation of Severity Level of Wheat Powdery Mildew Based on Canopy Spectral Reflectance

FENG Wei,WANG Xiao-Yu,SONG Xiao,HE Li,WANG Yong-Hua,GUO Tian-Cai*   

  1. Henan Agricultural University / National Engineering Research Center for Wheat, Zhengzhou 450002, China
  • Received:2012-12-13 Revised:2013-04-22 Online:2013-08-12 Published:2013-05-20
  • Contact: 郭天财, E-mail: tcguo888@sina.com

Abstract:

Understanding spectrum characteristics and sensitive bands of wheat infected by Blumeria graminis f. sp. tritici (Bgt) and estimatiing the disease severity will provide a basis for monitoring and subsequently accurately controlling powdery mildew in wheat planted in large scales using aerial remote sensing. Canopy reflectance of winter wheat infected by artificial inoculationof Bgt with different severity levels was measured in disease nursery, field, and pot experiments, and the severity levels in different growth phases were also investigated at the same time. The results indicated that spectrum reflectance increased significantly in visible light region (350–710 nm) with the increase of disease severity level, and the light region between 580 nm to 710 nm was the sensitive bands to wheat powdery mildew, which varied greatly in near-infrared region (710–1100 nm) across treatments with different disease severity levels. However, the correlation between spectrum reflectance and traditional disease index (DI) was low. When the conventionalDI was replaced by modified DI, the correlation was improved significantly. An integrated linear regression equation of  disease severity level to red edge width (Lwidth) described the dynamic pattern of disease severity level in wheat, with R2 of 0.811 and relative error (RE) of 17.7%. Besides, correlation coefficients between spectral parameters (mND705, SIPI, CTR2, and TSAVI) and modified DI were higher than 0.6. No common integrated regression equation could be establishhed due to poor compatibility among experiments. The relative spectral indices (ΔMSAVI and ΔmND705) exhibited high correlations (R2 > 0.76) with the disease sensitive level, with RE values of 18.4% and 19.4%, respectively. The results suggested that the models with sensitive spectral indices could retrieve and forecast the disease severity level accurately in a large area.

Key words: Wheat powdery mildew, Hyperspectral remote sensing, Severity level, Retrieval model

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