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利用光谱红边参数监测黄萎病棉叶叶绿素和氮素含量
引用本文:陈兵,韩焕勇,王方永,刘政,邓福军,林海,余渝,李少昆,王克如,肖春华. 利用光谱红边参数监测黄萎病棉叶叶绿素和氮素含量[J]. 作物学报, 2013, 39(2): 319-329. DOI: 10.3724/SP.J.1006.2013.00319
作者姓名:陈兵  韩焕勇  王方永  刘政  邓福军  林海  余渝  李少昆  王克如  肖春华
作者单位:1新疆农垦科学院棉花研究所 / 农业部西北内陆区棉花生物学与遗传育种重点实验室 / 国家棉花改良中心新疆生产建设兵团分中心, 新疆石河子 832003; 2中国农业科学院作物科学研究所 / 国家农作物基因资源与基因改良重大科学工程, 北京 100081; 3新疆兵团绿洲生态农业重点开放实验室 / 石河子大学, 新疆石河子 832000
基金项目:国家自然科学基金项目(41161068,30860139,31071371);新疆农垦科学院科技引导计划项目(YYD201102)资助
摘    要:以黄萎病胁迫下棉花叶片为试验材料, 分析感染病害棉叶叶绿素(Chl)含量和氮素含量(LNC)与光谱红边参数间的关系, 建立病害棉叶Chl含量和LNC的光谱红边参数诊断模型。结果表明:(1)随着病情加重, 棉叶Chl a、Chl b、Chl a+b和LNC逐渐减小, 其中Chl a下降最快, Chl b下降最慢;(2)黄萎病叶片光谱反射率在可见光区(400~700 nm), 近红外光区(700~1300 nm)和短波红外光区(1300~2500 nm)呈现逐渐上升趋势, 在520~680 nm间达极显著(P<0.01);光谱吸收率在可见光区和短波红外光区呈现逐渐下降的趋势, 达极显著(P<0.01), 在近红外光区呈现先升后降的趋势。(3)病害棉叶红边位置(REP)、红边振动幅(Dr)、红谷位置(Lo)、红边深度(Depth672)和红边面积(Area672)的值均减小, 红边宽度(Lwidth)的值增加, 且Area672减小的幅度最大, Dr减小的幅度最小, Lwidth增加的幅度较大;(4)病害棉叶Chl a含量、Chl b含量、Chl a+b含量和LNC均与红边参数REP、Lo、Depth672和Area672呈极显著正相关, 与Lwidth呈极显著负相关, 与Dr未达显著相关;(5)利用红边参数建立的棉叶Chl含量和LNC的诊断模型均达极显著(P<0.01), 其中以Area672为自变量建立的病害棉叶Chl a、Chl a+b和LNC的诊断模型和Lo为自变量建立的Chl b诊断模型的精度最高, 能很好的诊断病害棉叶Chl含量和LNC。

关 键 词:棉花  病害胁迫  高光谱  叶绿素含量  氮素含量  诊断模型
收稿时间:2012-06-20

Monitoring Chlorophyll and Nitrogen Contents in Cotton Leaf Infected by Verticillium wilt with Spectra Red Edge Parameters
CHEN Bing,HAN Huan-Yong,WANG Fang-Yong,LIU Zheng,DENG Fu-Jun,LIN Hai,YU Yu,LI Shao-Kun,WANG Ke-Ru,and XIAO Chun-Hua. Monitoring Chlorophyll and Nitrogen Contents in Cotton Leaf Infected by Verticillium wilt with Spectra Red Edge Parameters[J]. Acta Agronomica Sinica, 2013, 39(2): 319-329. DOI: 10.3724/SP.J.1006.2013.00319
Authors:CHEN Bing  HAN Huan-Yong  WANG Fang-Yong  LIU Zheng  DENG Fu-Jun  LIN Hai  YU Yu  LI Shao-Kun  WANG Ke-Ru  and XIAO Chun-Hua
Affiliation:2,3 1 Cotton Institute, Xinjiang Academy Agricultural and Reclamation Science / Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding, Ministry of Agriculture / Xinjiang Production & Construction Corps Subcenter of National Cotton Improvement Center, Shihezi 832000, China; 2 National Key Facility for Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 3 Key Laboratory of Oasis Ecology Agriculture of Xinjiang Corps / Shihezi University, Shihezi 832003, China
Abstract:The relationship between chlorophyll (Chl) content, leaf nitrogen content (LNC) and red edge parameters were analyzed, and diagnose models of spectra red edge parameters were established for cotton leaf infected by Verticillium wilt. Results showed that: (1) Chl a, Chl b, Chl a+b, and LNC decreased with increasing in severity level (SL) of Verticillium wilt in cotton leaves, in which Chl a showed the highest and Chl b showed the lowest decrement rate, respectively. (2) Spectrum reflectance increased with increasing severity of Verticillium wilt in the visible region (400–700 nm), near-infrared region (700–1300 nm) and short infrared region (1300–2500 nm), and significantly higher increment was detected in 525–680 nm region (P<0.01). Spectrum absorption decreased significantly with increasing SL of Verticillium wilt in the visible region and short infrared region (P<0.01), and which increased first and then decreased in near-infrared region. (3) Decrease of REP, Dr, Lo, Depth672, Area672 and increase of Lwidth was detected among red edge parameters, in which Area672 showed the highest and Dr showed the Lowest decrement rate, respectively. (4) There was significant positive correlation between Chl a, Chl b, Chl a+b, LNC of cotton leaves and REP, Lo, Depth672, Area672 of red edge parameters, significant negative correlation was found for Lwidth of red edge parameter, while no significant correlation was found for Dr of red edge parameter. (5) Diagnose models of Chl a, Chl a+b, and LNC for Verticillium wilt in cotton leaves with the independent variables Area672, and Chl b with the independent variables Lo reached the best estimated precision (P<0.01). This could diagnose severity level of Verticillium wilt in cotton leaves effectively.
Keywords:Cotton  Disease stress  Hyper spectra  Chlorophyll content  Nitrogen content  Diagnose models
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