高光谱的病害棉叶光合参数提取  

Extraction of Photosynthetic Parameters of Cotton Leaves under Disease Stress by Hyperspectral Remote Sensing

作　　者：陈兵[1] 王刚[2] 刘景德[1] 马占鸿[3] 王静[4] 李天南[1,3] CHEN Bing;WANG Gang;LIU Jing-de;MA Zhan-hong;WANG Jing;LI Tian-nan(Cotton Institute, Xinjiang Academy Agricultural and Reclamation Science/Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding, Shihezi 832000, China;College of Plant Protection, China Agricultural University, Beijing 100083, China;Institute of Water Conservation and Architectural Engineering, Xinjiang Shihezi Vocational College, Shihezi 832003, China4. Xinjiang Academy of Agricutural and Reclamation Science, Shihezi 832000, China)

机构地区：[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,新疆石河子832000 [2]新疆农垦科学院,新疆石河子832000 [3]中国农业大学植保学院,北京100083 [4]新疆石河子职业技术学院水利建筑工程分院,新疆石河子832003

出　　处：《光谱学与光谱分析》2018年第6期1834-1838,共5页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(41161068); 新疆农垦科学院科技引导计划项目(YYD201102)资助

摘　　要：应用高光谱遥感监测黄萎病胁迫下棉花叶片光合参数。在350~2 500nm光谱波段获取207个不同时期不同病情严重度的棉叶样本光谱数据,同步利用光合仪测量样本光合参数。采用单因素方差和相关分析研究光合参数特征,提取样本叶片光合参数的敏感波段并筛选光谱特征参数,采用线性和非线性回归方法建立预测模型并检验。结果表明:随病情严重度增加,棉叶净光合速率、气孔导度、蒸腾速率均下降,胞间CO_2浓度先降后增,差异显著;病情严重度与光合参数均达到显著相关,与净光合速率、蒸腾速率、气孔导度、胞间CO_2浓度相关系数分别为-0.97,-0.957,-0.886和0.715。选择与光合参数相关性最好的光谱敏感波段R704,R706,R699,R690,FD688,FD732,FD690,FD731,FD681组建新的光谱特征参数并与传统参数一起对净光合速率、蒸腾速率、气孔导度和胞间CO_2浓度进行反演,其中是以光谱参数PRI[FD732,FD688]),R706,RVI[890,670]),R690为自变量建立的净光合速率、蒸腾速率、气孔导度和胞间CO_2浓度反演方程精度最高,预测R^2分别为0.827,0.810,0.658,0.573;RMSE分别为5.466,2.801,109.500,63.500;RE分别为0.041,0.137,0.158,0.021。表明通过高光谱遥感可以实现棉花黄萎病叶片光合生理参数的提取。Hyperspectra remote sensing technique was applied to detect photosynthetic parameters （PP） in cotton leaf defected Verticillium wilt. The reflectance data about 207 was acquired in 350～2 500 nm bands in different dates and severity level of cotton leaves, and PP were measured by photosynthetic instrument. Analysis of variance and relationship analysis were used to process the PP character, extra spectral sensitive bands and selected character parameters of spectra with PP linear and nor-linear models were applied to product PP of cotton leaf of disease and tested. The result showed： with the disease condition increase, the data was increased to leaf net photosynthetic rate （A）, transpiration rate （E）, stomatal conductance （GH2O）, howeverintercellular CO2 （CI） firstly decreased and then up, and the difference was significant between severity levels and PP. The relationship became better between severity level and PP, which r were -0.97, -0.957, -0.886, 0.715, respectively. New spectral parameters,R704, R706, R699, R690, FD688, FD732, FD690, FD731, FD681 were built on the base of sensitive bands together with tradition spectral parameters to established revise models of A, E, GH2O, CI of cotton leaves with disease. Those models as PRI[FD732, FD688]）, R706, RVI[890, 670]）, R690 for the independent variable had the highest accuracy to estimate A, E, GH2O, CI, R2 of prediction, which were 0.827, 0.810, 0.658 and 0.573 respectively; RMSE were 5.466, 2.801, 109.500 and 63.500 respectively; RE were 0.041, 0.137, 0.158 and 0.021 respectively, which can realize the inversion of photosynthetic physiological parameters of cotton by remote sensing.

关 键 词：棉花 黄萎病 叶片 光合参数 高光谱 模型 

分 类 号：O657.3[理学—分析化学]