Developing an Index for Detection and Identification of Disease Stages

作者：Ashourloo Davoud^*; Matkan Ali Akbar; Huete Alfredo; Aghighi Hossein; Mobasheri Mohammad Reza

来源：IEEE Geoscience and Remote Sensing Letters, 2016, 13(6): 851-855.

DOI：10.1109/LGRS.2016.2550529

• Disease stages
• disease symptoms
• hyperspectral reflectance
• leaf rust
• spectral disease index (SDI)
• wheat

Spectral data have been widely used to estimate the disease severity (DS) levels of different plants. However, such data have not been evaluated to estimate the disease stages of the plant. This study aimed at developing a spectral disease index (SDI) that is able to identify the stages of wheat leaf rust disease at various DS levels. To meet the aim of the study, the reflectance spectra (350-2500 nm) of infected leaves with different symptom fractions and DS levels were measured with a spectroradiometer. Then, pure spectra of the different disease symptoms at the leaf scale were analyzed, and a new function was developed to find the wavelengths most sensitive to disease symptom fraction. The reflectance spectra with highest sensitivity were found at 675 and 775 nm. Finally, the normalized difference of DS and the ratio rho(675)/rho(775) was used as a new SDI to discriminate three different levels of the disease stage at the canopy level. The suggested SDI showed a promising performance to improve the detection disease stages in precision plant protection.

• 出版日期2016-6