Spectroscopic Leaf Level Detection of Powdery Mildew for Winter Wheat Using Continuous Wavelet Analysis

文献类型： 外文期刊

第一作者： Zhang Jing-cheng

作者： Zhang Jing-cheng;Yuan Lin;Wang Ji-hua;Huang Wen-jiang;Chen Li-ping;Zhang Dong-yan;Zhang Jing-cheng;Yuan Lin;Wang Ji-hua;Zhang Dong-yan;Huang Wen-jiang

作者机构：

关键词： powdery mildew;disease severity;continuous wavelet analysis;partial least square regression

期刊名称：JOURNAL OF INTEGRATIVE AGRICULTURE （ 影响因子：2.848； 五年影响因子：2.979 ）

ISSN： 2095-3119

年卷期： 2012 年 11 卷 9 期

页码：

收录情况： SCI

摘要： Powdery mildew (Blumeria graminis) is one of the most destructive crop diseases infecting winter wheat plants, and has devastated millions of hectares of farmlands in China. The objective of this study is to detect the disease damage of powdery mildew on leaf level by means of the hyperspectral measurements, particularly using the continuous wavelet analysis. In May 2010, the reflectance spectra and the biochemical properties were measured for 114 leaf samples with various disease severity degrees. A hyperspectral imaging system was also employed for obtaining detailed hyperspectral information of the normal and the pustule areas within one diseased leaf. Based on these spectra data, a continuous wavelet analysis (CWA) was carried out in conjunction with a correlation analysis, which generated a so-called correlation scalogram that summarizes the correlations between disease severity and the wavelet power at different wavelengths and decomposition scales. By using a thresholding approach, seven wavelet features were isolated for developing models in determining disease severity. In addition, 22 conventional spectral features (SFs) were also tested and compared with wavelet features for their efficiency in estimating disease severity. The multivariate linear regression (MLR) analysis and the partial least square regression (PLSR) analysis were adopted as training methods in model development. The spectral characteristics of the powdery mildew on leaf level were found to be closely related with the spectral characteristics of the pustule area and the content of chlorophyll. The wavelet features performed better than the conventional SFs in capturing this spectral change. Moreover, the regression model composed by seven wavelet features outperformed (R-2=0.77, relative root mean square error RRMSE=0.28) the model composed by 14 optimal conventional SFs (R-2=0.69, RRMSE=0.32) in estimating the disease severity. The PLSR method yielded a higher accuracy than the MLR method. A combination of CWA and PLSR was found to be promising in providing relatively accurate estimates of disease severity of powdery mildew on leaf level.

分类号：

  • 相关文献

[1]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

[2]Estimating leaf SPAD values of freeze-damaged winter wheat using continuous wavelet analysis. Wang, Hui-fang,Huo, Zhi-guo,Zhou, Guang-sheng,Wu, Li,Wang, Hui-fang,Liao, Qin-hong,Feng, Hai-kuan,Liao, Qin-hong.

[3]Evaluation of spectral indices and continuous wavelet analysis to quantify aphid infestation in wheat. Luo, Juhua,Huang, Wenjiang,Yuan, Lin,Zhao, Chunjiang,Zhang, Jingcheng,Zhao, Jinling,Du, Shizhou.

[4]Threshold Microsclerotial Inoculum for Cotton Verticillium Wilt Determined Through Wet-Sieving and Real-Time Quantitative PCR. Feng Wei,Rong Fan,Haitao Dong,Wenjing Shang,Xiangming Xu,Heqin Zhu,Jiarong Yang,Xiaoping Hu.

[5]Pathogenic analysis of Borrelia garinii strain SZ isolated from northeastern China. Luo, Jianxun. 2013

[6]Recombinant pseudorabies virus expressing P12A and 3C of FMDV can partially protect piglets against FMDV challenge. Zhang, Keshan,Wang, Qingang,He, Yannan,Xu, Zhuofei,Xiang, Min,Wu, Bin,Chen, Huanchun,Zhang, Keshan,Huang, Jiong.

[7]Estimating rice brown spot disease severity based on principal component analysis and radial basis function neural network. Liu Zhan-yu,Huang Jing-feng,Tao Rong-xiang,Zhang Hong-zhi. 2008

[8]Estimating Severity Level of Cotton Infected Verticillium Wilt Based on Spectral Indices of TM Image. Chen, Bing,Wang, Keru,Li, Shaokun,Xiao, Chunhua,Chen, Jianglu,Jin, Xiulinag,Wang, Keru,Li, Shaokun,Chen, Bing.

[9]Rapid screening of Musa species for resistance to Fusarium wilt in an in vitro bioassay. Wu, Y. L.,Yi, G. J.,Peng, X. X..

[10]Identification and validation of a major QTL conferring crown rot resistance in hexaploid wheat. Ma, J.,Li, H. B.,Zhang, C. Y.,Yang, X. M.,Liu, Y. X.,Liu, C. J.,Ma, J.,Yan, G. J.,Liu, C. J.,Yang, X. M.,Liu, Y. X..

[11]Winter wheat biomass estimation based on canopy spectra. Zheng Ling,Zhu Dazhou,Zhang Baohua,Wang Cheng,Zhao Chunjiang,Zheng Ling,Liang Dong. 2015

[12]Determination of Cr, Zn, As and Pb in Soil by X-Ray Fluorescence Spectrometry Based on a Partial Least Square Regression Model. Lu, Anxiang,Wang, Jihua,Pan, Ligang,Lu, Anxiang,Qin, Xiangyang,Wang, Jihua,Zhu, Dazhou,Sun, Jiang. 2011

[13]Band Depth Analysis and Partial Least Square Regression Based Winter Wheat Biomass Estimation Using Hyperspectral Measurements. Fu Yuan-yuan,Wang Ji-hua,Fu Yuan-yuan,Wang Ji-hua,Yang Gui-jun,Song Xiao-yu,Xu Xin-gang,Feng Hai-kuan,Fu Yuan-yuan,Wang Ji-hua,Yang Gui-jun,Song Xiao-yu,Xu Xin-gang,Feng Hai-kuan. 2013

[14]Determination of Soil Parameters in Apple-Growing Regions by Near- and Mid-Infrared Spectroscopy. Dong Yi-Wei,Xu Chun-Ying,Li Yu-Zhong,Li Qiao-Zhen,Dong Yi-Wei,Yang Shi-Qi,Fan Zhong-Nan,Wang Ya-Nan,Bai Wei. 2011

[15]ESTIMATION OF LEAF AREA INDEX BY USING MULTI-ANGULAR HYPERSPECTRAL IMAGING DATA BASED ON THE TWO-LAYER CANOPY REFLECTANCE MODEL. Liao, Qinhong,Zhao, Chunjiang,Yang, Guijun,Wang, Jihua,Zhang, Dongyan,Liao, Qinhong,Zhang, Dongyan,Coburn, Craig,Wang, Zhijie. 2013

[16]Molecular cloning, functional verification, and evolution of TmPm3, the powdery mildew resistance gene of Triticum monococcum L.. Zhao, C. Z.,Li, Y. H.,Dong, H. T.,Geng, M. M.,Liu, W. H.,Li, F.,Ni, Z. F.,Xie, C. J.,Sun, Q. X.,Zhao, C. Z.,Dong, H. T.,Geng, M. M.,Liu, W. H.,Li, F.,Ni, Z. F.,Xie, C. J.,Sun, Q. X.,Zhao, C. Z.,Wang, X. J.. 2016

[17]Two members of TaRLK family confer powdery mildew resistance in common wheat. Tingting Chen,Jin Xiao,Jun Xu,Wentao Wan,Bi Qin,Aizhong Cao,Wei Chen,Liping Xing,Chen Du,Xiquan Gao,Shouzhong Zhang,Ruiqi Zhang,Wenbiao Shen,Haiyan Wang,Xiue Wang. 2016

[18]Quantitative trait loci mapping of adult-plant resistance to powdery mildew in Chinese wheat cultivar Lumai 21. Caixia Lan,Xiaowen Ni,Jun Yan,Yong Zhang,Xianchun Xia,Xinmin Chen,Zhonghu He.

[19]Discrimination of yellow rust and powdery mildew in wheat at leaf level using spectral signatures. Yuan, Lin,Zhang, Jingcheng,Zhao, Jinling,Du, Shizhou,Huang, Wenjiang,Wang, Jihua. 2012

[20]Reaction to powdery mildew and stripe rust in related species and landraces of wheat. He, Danxia,Li, Hongjie,Xu, Shichang,Duan, Xiayu,Zhou, Yilin,Li, Lihui. 2007

作者其他论文 更多>>

微信小程序