Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves

By R. Devadas, D. Lamb, S. Simpfendorfer, D. Backhouse. Precision Agriculture, 2008

215 citations recorded by the source corpus.

Subfields: Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/587151fc1a96bd643331e75b9a32e837d816b847

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Yanbo Huang
2. Jihua Wang
3. Chenwei Nie
4. Budiman Minasny
5. Werner B. Herppich
6. Elke Bauriegel
7. Sabine Grunwald
8. Tomislav Hengl

In Plant Science

1. Jihua Wang
2. Chenwei Nie
3. Werner B. Herppich
4. Elke Bauriegel

Citations in the corpus

• Spectral analysis of winter wheat leaves for detection and differentiation of diseases and insects (2014, background): “RVSI Red-edge vegetation stress index [(R712 + R752)/2]–R732 Merton (1998) SIPI Structural independent pigment index (R800 − R445)/(R800 + R680) Devadas et al. (2009) NPCI Normalized pigment chlorophyll ratio index (R680 − R430)/(R680 + R430) Devadas et al. (2009) WI Water index R900/R970 Naidu et a”
• Hyperspectral and Chlorophyll Fluorescence Imaging for Early Detection of Plant Diseases, with Special Reference to Fusarium spec. Infections on Wheat (2014, methodology): “on wheat, different vegetation indices were calculated from spectra recorded between 400 and 900 nm [56].”
• Mapping and identifying basal stem rot disease in oil palms in North Sumatra with QuickBird imagery (2011, background): “Yang (2010) analysed hyperspectral canopy reflectance spectra to assess the severity of bacterial leaf blight in rice, and Devadas et al. (2004) evaluated various vegetation indices obtained from a hyperspectral sensor to identify rust infection in individual wheat leaves.”