YANG Feng,HUANG Shan,WU Xiao-ling,et al.Effects of Phytophthora Root Rot Stress on Canopy Spectra Reflectance and Chlorophyll Fluorescence Characteristics of Soybean[J].Soybean Science,2013,32(04):490-495,500.[doi:10.11861/j.issn.1000-9841.2013.04.0490]
根腐病胁迫对大豆光谱特征和叶绿素荧光特性的影响
- Title:
- Effects of Phytophthora Root Rot Stress on Canopy Spectra Reflectance and Chlorophyll Fluorescence Characteristics of Soybean
- Keywords:
- Disease stress; Vegetation index; Fluorescence characteristics; Hyperspectral remote sensing
- 分类号:
- TP79
- 文献标志码:
- A
- 摘要:
- ?为探讨根腐病胁迫下光谱特征指数和叶绿素荧光参数与光合色素的相关性,以大豆植株为研究对象,分析了不同程度根腐病胁迫下大豆叶片光合色素、叶绿素荧光特性以及冠层光谱特征的差异性。结果表明:随大豆根腐病病情的加重叶绿素a、叶绿素b、总叶绿素、类胡萝卜素以及叶绿素/类胡萝卜素降低。同时,光系统II最大光化学效率、光系统II光化学效率、非光化学淬灭系数以及PSII的量子产额等荧光参数显著低于正常植株。光谱反射率在近红外区域(700~1 000 nm)随病害程度的加重而降低,归一化深度变浅。通过对原始光谱进行微分变换,病害植株红边幅值降低,红边位置出现蓝移现象。除绿峰位置、幅值以及修正叶绿素吸收反射率指数外,红边幅值、红边位置、结构不敏感色素指数、光化学植被指数、简单植被指数、归一化差异指数、修正归一化差异指数、绿度指数以及荧光参数与根腐病胁迫下叶片光合色素相关性均达到显著水平。因此,选择适宜的光谱特征指数和叶绿素荧光参数,借助光合色素变化,可为利用高光谱遥感技术和荧光成像技术对大豆根腐病危害诊断提供理论支持。
- Abstract:
- ?Hyperspectral crop reflectance data for detecting plant pathological stress are vital for precision crop protection.To analyze the correlation of photosynthetic pigments,chlorophyll fluorescence parameters and spectral reflectance under root rot disease stress,taking soybean as material,the differences under different extent root rot stress were discussed.The results showed that photosynthetic pigment concentrations(chlorophyll a,chlorophyll b,carotenoid,total chlorophyll and chlorophyll/carotenoid)and fluorescence parameters decreased with increasing degree of disease stress.The reflectance of nearinfrared region and depth of normalized reflectance also appeared similar result.In addition,the amplitude of red edge decreased and the red edge position moved to blue band under disease stress compared to health plants.The correlations between spectral characteristics,chlorophyll fluorescence parameter and photosynthetic pigment concentrations were significant except position and amplitude of green peak and MCARI. This provided an insight for choosing appropriate spectral characteristics and fluorescence parameters to monitor soybean root rot status by following the dynamics of photosynthetic pigment concentrations.
相似文献/References:
[1]申晓慧,姜成,张敬涛,等.不同氮肥水平下大豆叶片光谱反射率与叶绿素含量的相关性研究[J].大豆科学,2012,31(01):73.[doi:10.3969/j.issn.1000-9841.2012.01.016]
SHEN Xiao-hui,JIANG Cheng,ZHANG Jing-tao,et al.Correlation between Spectrum Reflectance and Chlorophyll Content of Soybean Leaves under Different Nitrogen Level[J].Soybean Science,2012,31(04):73.[doi:10.3969/j.issn.1000-9841.2012.01.016]
[2]宋英博,贾立君,杜永生,等.利用叶片反射光谱预测大豆合交98-1667干物重模型[J].大豆科学,2010,29(03):429.[doi:10.11861/j.issn.1000-9841.2010.03.0429]
SONG Ying-bo,JIA Li-jun,DU Yong-sheng,et al.Predicting Model of Dry Matter Accumulation of Dwarf Soybean Hybrid 98-1667 by Leaf Reflectance Spectra[J].Soybean Science,2010,29(04):429.[doi:10.11861/j.issn.1000-9841.2010.03.0429]
[3]申晓慧,张敬涛,姜成,等.大豆叶片叶绿素含量与光谱的特征分析[J].大豆科学,2009,28(04):747.[doi:10.11861/j.issn.1000-9841.2009.04.0747]
SHEN Xiao-hui,ZHANG Jing-tao,JIANGCheng,et al.Correlation between Chlorophyll Content and Spectral Characteristics of Soybean Leaves[J].Soybean Science,2009,28(04):747.[doi:10.11861/j.issn.1000-9841.2009.04.0747]
[4]黄春燕,刘胜利,王登伟,等.大豆叶面积指数的高光谱估算模型研究[J].大豆科学,2008,27(02):228.[doi:10.11861/j.issn.1000-9841.2008.02.0228]
HUANG Chun-yan,LIU Sheng-li,WANG Deng-wei,et al.Models for Estimating Soybean Leaf Area Index Using Hyperspectral Data[J].Soybean Science,2008,27(04):228.[doi:10.11861/j.issn.1000-9841.2008.02.0228]
[5]陆国政,杨贵军,赵晓庆,等.基于多载荷无人机遥感的大豆地上鲜生物量反演[J].大豆科学,2017,36(01):41.[doi:10.11861/j.issn.1000-9841.2017.01.0041]
LU Guo-zheng,YANG Gui-jun,ZHAO Xiao-qing,et al.Inversion of Soybean Fresh Biomass Based on Multipayload Unmanned Aerial Vehicles (UAVs)[J].Soybean Science,2017,36(04):41.[doi:10.11861/j.issn.1000-9841.2017.01.0041]
[6]龚荣新,鲁向晖,张海娜,等.基于高光谱植被指数的大豆地上部生物量估算模型研究[J].大豆科学,2023,42(03):352.[doi:10.11861/j.issn.1000-9841.2023.03.0352]
备注/Memo
?基金项目:农业部公益性行业科研专项资金项目(201203096); 四川省教育厅重点项目(12ZA104); 四川省博士后基金(04310624)。