Roles of Physiological and Nonphysiological Information in Sun-Induced Chlorophyll Fluorescence Variations for Detecting Cotton Verticillium Wilt

被引:1
|
作者
Zhou, Junru [1 ,2 ]
Huang, Changping [1 ,2 ]
Gui, Yaohui [1 ,2 ]
Yang, Mi [3 ]
Zhang, Ze [3 ]
Huang, Wenjiang [4 ,5 ]
Zhang, Lifu [1 ]
Tong, Qingxi [1 ]
机构
[1] Chinese Acad Sci, Aerosp Informat Res Inst, Natl Engn Lab Satellite Remote Sensing Applicat, Beijing 100094, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Shihezi Univ, Coll Agr, Xinjiang Prod & Construction Crop Oasis Ecoagr Key, Shihezi 832003, Peoples R China
[4] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Aerosp Informat Res Inst, Beijing, Peoples R China
[5] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
关键词
Biomedical monitoring; Cotton; Stress; Vegetation mapping; Fluorescence; Reflectivity; Diseases; Cotton verticillium wilt (VW); nonphysiological; photosynthesis; sun-induced chlorophyll fluorescence (SIF); THERMAL IMAGERY; TEMPERATURE; PHOTOSYNTHESIS; DAHLIAE; WATER; REFLECTANCE; DISEASES; PLANTS;
D O I
10.1109/JSTARS.2024.3390546
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Sun-induced chlorophyll fluorescence (SIF) has been a promising indicator of plants' physiological status, but its response to physiological changes under the verticillium wilt (VW) stress of cotton plants is complicated by concurrent nonphysiological changes. The relative contributions of the above two components to SIF variations are unclear at different VW stress severities, hindering the accurate diagnosis of VW levels. Therefore, the objective of this study is to investigate the dynamic responses of SIF, physiological and nonphysiological factors, and to evaluate the contributions of the two factors to SIF variations under different VW stress degrees of cotton. We continuously observed the diurnal variation of the top-of-canopy reflectance and SIF on healthy and VW-infected cotton during the peak incidence period of VW disease. To accurately quantify the relative contribution of each component to SIF, we proposed a practical strategy to estimate unmeasurable parameter when using Lindeman, Merenda, and Gold method. The results demonstrated the dominant role of physiological factors in SIF with an arch diurnal change pattern at the early stages of VW development. As the VW severity increased, the contribution of physiological components declined, with the maximum contribution decreasing by 47.7%, and the diurnal pattern was disrupted, with the diurnal variation amplitude of the parameter declining by 63.4%, followed by a shift in the regulatory role toward nonphysiological factors. This study contributes to a further understanding of the roles of physiological and nonphysiological components in SIF variations of cotton under VW stress, thus advancing the accurate monitoring of VW stress severity.
引用
收藏
页码:8835 / 8850
页数:16
相关论文
共 50 条
  • [1] Exploring Physiological and Nonphysiological Responses of Sun-Induced Chlorophyll Fluorescence to Different Levels of Water Stress in Winter Wheat
    Lin, Jingyu
    Zhou, Litao
    Wu, Jianjun
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 17 : 5107 - 5120
  • [2] Exploring the physiological information of Sun-induced chlorophyll fluorescence through radiative transfer model inversion
    Celesti, Marco
    van der Tol, Christiaan
    Cogliati, Sergio
    Panigada, Cinzia
    Yang, Peiqi
    Pinto, Francisco
    Rascher, Uwe
    Miglietta, Franco
    Colombo, Roberto
    Rossini, Micol
    [J]. REMOTE SENSING OF ENVIRONMENT, 2018, 215 : 97 - 108
  • [3] Modeling of Cotton Yield Estimation Based on Canopy Sun-Induced Chlorophyll Fluorescence
    Wang, Hongyu
    Ding, Yiren
    Yao, Qiushuang
    Ma, Lulu
    Ma, Yiru
    Yang, Mi
    Qin, Shizhe
    Xu, Feng
    Zhang, Ze
    Gao, Zhe
    [J]. AGRONOMY-BASEL, 2024, 14 (02):
  • [4] The roles of radiative, structural and physiological information of sun-induced chlorophyll fluorescence in predicting gross primary production of a corn crop at various temporal scales
    Yang, Peiqi
    Liu, Xinjie
    Liu, Zhigang
    van der Tol, Christiaan
    Liu, Liangyun
    [J]. AGRICULTURAL AND FOREST METEOROLOGY, 2023, 342
  • [5] Effect of canopy structure on sun-induced chlorophyll fluorescence
    Fournier, A.
    Daumard, F.
    Champagne, S.
    Ounis, A.
    Goulas, Y.
    Moya, I.
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2012, 68 : 112 - 120
  • [6] Dynamics of sun-induced chlorophyll fluorescence and reflectance to detect stress-induced variations in canopy photosynthesis
    Pinto, Francisco
    Celesti, Marco
    Acebron, Kelvin
    Alberti, Giorgio
    Cogliati, Sergio
    Colombo, Roberto
    Juszczak, Radoslaw
    Matsubara, Shizue
    Miglietta, Franco
    Palombo, Angelo
    Panigada, Cinzia
    Pignatti, Stefano
    Rossini, Micol
    Sakowska, Karolina
    Schickling, Anke
    Schuttemeyer, Dirk
    Strozecki, Marcin
    Tudoroiu, Marin
    Rascher, Uwe
    [J]. PLANT CELL AND ENVIRONMENT, 2020, 43 (07): : 1637 - 1654
  • [7] AIRBORNE BASED SPECTROSCOPY TO MEASURE SUN-INDUCED CHLOROPHYLL FLUORESCENCE
    Damn, Alexander
    Rossini, Micol
    Colombo, Roberto
    Rascher, Uwe
    Schaepman, Michael E.
    [J]. 2014 6TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2014,
  • [8] REMOTE SENSING OF SUN-INDUCED CHLOROPHYLL FLUORESCENCE AT DIFFERENT SCALES
    Colombo, R.
    Alonso, L.
    Celesti, M.
    Cogliati, S.
    Damm, A.
    Drusch, M.
    Guanter, L.
    Julitta, T.
    Kokkalis, P.
    Kraft, S.
    Moreno, J.
    Panigada, C.
    Pinto, F.
    Rascher, U.
    Rossini, M.
    Schickling, A.
    Schuttemeyer, D.
    Verhoef, W.
    Zemek, F.
    [J]. 2014 6TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2014,
  • [9] Difference and Potential of the Upward and Downward Sun-Induced Chlorophyll Fluorescence on Detecting Leaf Nitrogen Concentration in Wheat
    Jia, Min
    Zhu, Jie
    Ma, Chunchen
    Alonso, Luis
    Li, Dong
    Cheng, Tao
    Tian, Yongchao
    Zhu, Yan
    Yao, Xia
    Cao, Weixing
    [J]. REMOTE SENSING, 2018, 10 (08)
  • [10] Decoupling physiological and non-physiological responses of sugar beet to water stress from sun-induced chlorophyll fluorescence
    Wang, Na
    Yang, Peiqi
    Clevers, Jan G. P. W.
    Wieneke, Sebastian
    Kooistra, Lammert
    [J]. REMOTE SENSING OF ENVIRONMENT, 2023, 286