Identification and Disease Index Inversion of Wheat Stripe Rust and Wheat Leaf Rust Based on Hyperspectral Data at Canopy Level

Hui Wang,Rui Wang,Liu Ruan,Zhanhong Ma,Qi Liu,Haiguang Wang,Pei Cheng,Xiaolong Li,Feng Qin

doi:10.1155/2015/651810

Hui Wang, Rui Wang + Show 7 more

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https://doi.org/10.1155/2015/651810

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Abstract

Stripe rust and leaf rust with similar symptoms are two important wheat diseases. In this study, to investigate a method to identify and assess the two diseases, the canopy hyperspectral data of healthy wheat, wheat in incubation period, and wheat in diseased period of the diseases were collected, respectively. After data preprocessing, three support vector machine (SVM) models for disease identification and six support vector regression (SVR) models for disease index (DI) inversion were built. The results showed that the SVM model based on wavelet packet decomposition coefficients with the overall identification accuracy of the training set equal to 99.67% and that of the testing set equal to 82.00% was better than the other two models. To improve the identification accuracy, it was suggested that a combination model could be constructed with one SVM model and two models built usingK-nearest neighbors (KNN) method. Using the DI inversion SVR models, the satisfactory results were obtained for the two diseases. The results demonstrated that identification and DI inversion of stripe rust and leaf rust can be implemented based on hyperspectral data at the canopy level.

Highlights

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) and leaf rust caused by P. recondita f. sp. tritici (Prt) are two devastating wheat diseases worldwide [1]
For wheat stripe rust and leaf rust, the canopy spectral reflectance of wheat in the incubation period and that of wheat in the diseased period relatively increased compared with that of healthy wheat in this spectral range. Both in the incubation period and in the diseased period, the canopy spectral reflectance of wheat infected with Pst relatively increased compared with that of wheat infected with Prt
The results described above indicated that the first group of spectral features reflected the differences between the spectra of wheat in the diseased period of stripe rust and that of wheat in the diseased period of leaf rust, that the second group of spectral features reflected the differences among the spectra of healthy wheat, that of wheat in the incubation period of stripe rust and that of wheat in the incubation period of leaf rust, and that the third group of spectral features reflected the differences between the spectra of healthy wheat and diseased wheat infected with Pst or Prt

Summary

Introduction

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) and leaf rust caused by P. recondita f. sp. tritici (Prt) are two devastating wheat diseases worldwide [1]. In China, a couple of severe epidemics of the two diseases occurred and destructive yield losses of wheat were caused [1,2,3]. These two diseases are confused with each other because of the similar disease symptoms. The identification and assessment of the two diseases mainly rely on the naked-eye field observation and investigation of the visible disease symptoms conducted by plant protection technical personnel. This method is labor-consuming and time-costing, and it results in errors. It is of great significance to explore a method for rapid and accurate identification and quantitative assessment of these two diseases

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