Discrimination of yellow rust and powdery mildew in wheat at leaf level using spectral signatures

文献类型： 外文期刊

第一作者： Yuan, Lin

作者： Yuan, Lin;Zhang, Jingcheng;Zhao, Jinling;Du, Shizhou;Huang, Wenjiang;Wang, Jihua

作者机构：

关键词： yellow rust;powdery mildew;winter wheat;independent t-test;fisher linear discrimination analysis

期刊名称：2012 FIRST INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS)

ISSN： 2334-3168

年卷期： 2012 年

页码：

收录情况： SCI

摘要： Yellow rust (Puccinia struformis f. sp. Tritici) and powdery mildew (Blumeria graminis) are two serious diseases that severely intimidated yield and grain quality of winter wheat around the world. Since the preferable habitat conditions of them are similar, there is a high possibility that both diseases occurred in field simultaneously. To facilitate a differentiation of control procedures (i.e. using different fungicide), the discrimination of yellow rust and powdery mildew is a necessity. As a fast and non-destructive technique in obtaining the plant status information in real time, remote sensing has been successfully applied in the monitoring of crop diseases in several cases. However, studies addressing the discrimination of different crop diseases are rare. The aim of the present work was to assess the capability of remote sensing in discriminating yellow rust and powdery mildew at leaf level. For each disease, a total of 30 leaf samples were collected for spectral measurement, including both infected and non-infected leaves. Prior to the analysis, the spectral data were undertaken a normalization, to minimize the spectral difference caused by the cultivars. The spectra of normal leaves were compared with that of both infected ones (yellow rust and powdery mildew) through an independent t-test. Within the bands that were significantly different between normal and diseased leaves, a further band selection was conducted to differentiate powdery mildew from yellow rust using the same independent t-test. Only those disease sensitive bands that have the discriminative power were retained. Their discriminative capability was examined by a fisher linear discrimination analysis (FLDA). It turned out that the discrimination model yielded satisfactory estimation of sample categories, with an overall accuracy over 0.9. Therefore, it is evident that the hyperspectral remote sensing is a promising way to discriminate yellow rust and powdery mildew.

分类号：

  • 相关文献

[1]New Optimized Spectral Indices for Identifying and Monitoring Winter Wheat Diseases. Huang, Wenjiang,Guan, Qingsong,Guan, Qingsong,Zhao, Jinling,Liang, Dong,Huang, Linsheng,Zhang, Dongyan,Luo, Juhua,Zhang, Jingcheng. 2014

[2]Differentiation of Yellow Rust and Powdery Mildew in Winter Wheat and Retrieving of Disease Severity Based on Leaf Level Spectral Analysis. Yuan Lin,Zhang Jing-cheng,Zhao Jin-ling,Wang Ji-hua,Yuan Lin,Zhang Jing-cheng,Wang Ji-hua,Huang Wen-jiang. 2013

[3]Spectral analysis of winter wheat leaves for detection and differentiation of diseases and insects. Yuan, Lin,Nie, Chenwei,Wang, Jihua,Zhang, Jingcheng,Yuan, Lin,Nie, Chenwei,Wang, Jihua,Zhang, Jingcheng,Huang, Yanbo,Loraamm, Rebecca W.. 2014

[4]SELECTION OF SPECTRAL CHANNELS FOR SATELLITE SENSORS IN MONITORING YELLOW RUST DISEASE OF WINTER WHEAT. Yuan, Lin,Wang, Jihua,Yuan, Lin,Zhang, Jingcheng,Nie, Chenwei,Wei, Liguang,Yang, Guijun,Wang, Jihua,Yuan, Lin,Zhang, Jingcheng,Nie, Chenwei,Wei, Liguang,Yang, Guijun,Wang, Jihua. 2013

[5]Vertical features of yellow rust infestation on winter wheat using hyperspectral imaging measurements. Zhao, Jinling,Zhang, Dongyan,Huang, Linsheng,Zhang, Qing,Liu, Wenjing,Yang, Hao. 2016

[6]Comparison between wavelet spectral features and conventional spectral features in detecting yellow rust for winter wheat. Zhang, Jingcheng,Yuan, Lin,Yang, Guijun,Wang, Jihua,Zhang, Jingcheng,Yuan, Lin,Yang, Guijun,Wang, Jihua,Zhang, Jingcheng,Yuan, Lin,Yang, Guijun,Wang, Jihua,Zhang, Jingcheng,Pu, Ruiliang,Loraamm, Rebecca W.. 2014

[7]Mapping of powdery mildew using multi-spectral HJ-CCD image in Beijing suburban area. Yuan, Lin,Zhang, Jingcheng,Zhao, Jinling,Huang, Linsheng,Yang, Xiaodong,Wang, Jihua,Yuan, Lin,Zhang, Jingcheng,Wang, Jihua,Huang, Linsheng. 2013

[8]Comparison of conventional, flood irrigated, flat planting with furrow irrigated, raised bed planting for winter wheat in China. Fahong, W,Wang, X,Sayre, K. 2004

[9]CHARACTERIZATION OF POWDERY MILDEW IN WINTER WHEAT USING MULTI-ANGULAR HYPERSPECTRAL MEASUREMENTS. Zhao, Jinling,Yuan, Lin,Zhang, Dongyan,Zhang, Jingcheng,Gu, Xiaohe,Huang, Linsheng,Zhang, Dongyan. 2013

[10]Forecasting of Powdery Mildew disease with multi-sources of remote sensing information. Zhang, Jingcheng,Yuan, Lin,Nie, Chenwei,Wei, Liguang,Yang, Guijun,Zhang, Jingcheng,Yang, Guijun,Zhang, Jingcheng,Yang, Guijun,Zhang, Jingcheng,Yuan, Lin. 2014

[11]Using high spatial resolution satellite imagery for mapping powdery mildew at a regional scale. Yuan, Lin,Zhang, Jingcheng,Wang, Jihua,Yang, Hao,Pu, Ruiliang.

[12]Damage Mapping of Powdery Mildew in Winter Wheat with High-Resolution Satellite Image. Yuan, Lin,Zhang, Jingcheng,Nie, Chenwei,Wei, Liguang,Wang, Jihua,Zhang, Jingcheng,Wang, Jihua,Zhang, Jingcheng,Wang, Jihua,Yuan, Lin,Zhang, Jingcheng,Wang, Jihua,Shi, Yeyin. 2014

[13]Comparative Research on Estimating the Severity of Yellow Rust in Winter Wheat. Wang Jing,Jing Yuan-shu,Zhao Juan,Wang Jing,Huang Wen-jiang,Zhang Qing,Wang Li,Zhang Jing-cheng. 2015

[14]CONTINUOUS WAVELET ANALYSIS BASED SPECTRAL FEATURE SELECTION FOR WINTER WHEAT YELLOW RUST DETECTION. Zhang Jingcheng,Wang Jihua,Zhang Jingcheng,Luo Juhua,Huang Wenjiang,Wang Jihua,Luo Juhua. 2011

[15]Seedling and slow rusting resistance to stripe rust in Chinese common wheats. Xia, X. C.,Zhou, X. C.,Niu, Y. C.,He, Z. H.,Zhang, Y.,Li, G. Q.,Wan, A. M.,Wang, D. S.,Chen, X. M.,Lu, Q. L.,Singh, R. P.. 2006

[16]Comparison of Methods for Forecasting Yellow Rust in Winter Wheat at Regional Scale. Nie, Chenwei,Yuan, Lin,Yang, Xiaodong,Wei, Liguang,Yang, Guijun,Zhang, Jingcheng. 2015

[17]Using in-situ hyperspectral data for detecting and discriminating yellow rust disease from nutrient stresses. Zhang, Jingcheng,Huang, Wenjiang,Yuan, Lin,Luo, Juhua,Wang, Jihua,Zhang, Jingcheng,Pu, Ruiliang,Zhang, Jingcheng,Yuan, Lin,Wang, Jihua,Huang, Wenjiang. 2012

[18]Analysis of spectral difference between the foreside and backside of leaves in yellow rust disease detection for winter wheat. Yuan, Lin,Zhang, Jing-Cheng,Wang, Ke,Wang, Ji-Hua,Yuan, Lin,Zhang, Jing-Cheng,Wang, Ji-Hua,Zhao, Jin-Ling,Loraamm, Rebecca-W.,Huang, Wen-Jiang.

[19]Transgressive segregation, heritability, and number of genes controlling durable resistance to stripe rust in one Chinese and two Italian wheat cultivars. Zhang, ZJ,Yang, GH,Li, GH,Jin, SL,Yang, XB. 2001

[20]Comparative virulence phenotypes and molecular genotypes of Puccinia striiformis f. sp tritici, the wheat stripe rust pathogen in China and the United States. Zhan, Gangming,Chen, Xianming,Wang, Meinan,Wan, Anmin,Cheng, Peng,Zhan, Gangming,Kang, Zhensheng,Huang, Lili,Wang, Meinan,Chen, Xianming,Chen, Xianming,Cao, Shiqin,Jin, Shelin. 2012

作者其他论文 更多>>

微信小程序