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Illumination/Darkness-Induced Changes in Leaf Surface Potential Linked With Kinetics of Ion Fluxes

文献类型： 外文期刊

作者： Li, Jinhai 1 ; Yue, Yang 1 ; Wang, Ziyang 1 ; Zhou, Qiao 1 ; Fan, Lifeng 1 ; Chai, Zhiqiang 1 ; Song, Chao 1 ; Dong, Hong 1 ;

作者机构： 1.China Agr Univ, Coll Informat & Elect Engn, Beijing, Peoples R China

2.Minist Educ, Key Lab Modern Precis Agr Syst Integrat Res, Beijing, Peoples R China

3.Minist Agr, Key Lab Agr Informat Acquisit Technol Beijing, Beijing, Peoples R China

4.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Intelligent Equipment Agr, Beijing, Peoples R China

关键词： electrical signal; light-induced bioelectrogenesis; periodic illumination; darkness; salt stimulation; ionic mechanisms; gray relational analysis

期刊名称：FRONTIERS IN PLANT SCIENCE （ 影响因子：5.753； 五年影响因子：6.612 ）

ISSN： 1664-462X

年卷期： 2019 年 10 卷

页码：

收录情况： SCI

摘要： A highly reproducible plant electrical signal-light-induced bioelectrogenesis (LIB) was obtained by means of periodic illumination/darkness stimulation of broad bean (Vicia faba L.) leaves. By stimulating the same position of the same leaf with different concentrations of NaCl, we observed that the amplitude and waveform of the LIB was correlated with the intensity of stimulation. This method allowed us to link dynamic ion fluxes induced by periodic illumination/darkness to salt stress. The self-referencing ion electrode technique was used to explore the ionic mechanisms of the LIB. Fluxes of H+, Ca2+, K+, and Cl- showed periodic changes under periodic illumination/darkness before and after 50 mM NaCl stimulation. Gray relational analysis was used to analyze correlations between each of these ions and LIB. The results showed that different ions are involved in surface potential changes at different stages under periodic illumination/darkness. The gray relational grade reflected the contribution of each ion to the change in surface potential at a certain time period. The ion fluxes data obtained under periodic illumination/darkness stimulation will contribute to the future development of a dynamic model for interpretation of electrophysiological events in plant cells.

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