渗透胁迫下玉米叶片电位波动边际谱的变化与意义

植物叶片电位波动是来自于活细胞的生命信息。为了解读植物叶片电位波动的频谱特征及其意义,该文采用HHT（Hilbert-Huang transform）方法研究了渗透势为？0.1 MPa的渗透胁迫下玉米幼苗叶片电位波动边际谱的变化规律及其意义,计算了边际谱特征参数边缘频率SEF（spectral edge frequency）、重心频率SCF（spectral center frequency）、边际谱熵MSE（marginal spectrum entropy）和动作电位灵敏指数Q。结果表明,玉米幼苗叶片电位波动的边际谱是分布在0.5 Hz以内的连续谱,在渗透胁迫下,SEF和SCF呈现出先减小...

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Bibliographic Details
Published in农业工程学报 Vol. 33; no. 1; pp. 199 - 205
Main Author 刘锴 习岗 贺瑞瑞 余宁梅
Format Journal Article
LanguageChinese
Published 西安理工大学理学院应用物理系,西安,710054%西安理工大学自动化与信息工程学院,西安,710048 2017
Subjects
Hilbert-Huang
transform
作物
渗透
玉米
电位波动
胁迫
边际谱
电位波动
玉米
stresses
作物
marginal spectrum
边际谱
crops
potential fluctuations
maize
Hilbert-Huang transform
osmosis
渗透
胁迫
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Summary:植物叶片电位波动是来自于活细胞的生命信息。为了解读植物叶片电位波动的频谱特征及其意义,该文采用HHT（Hilbert-Huang transform）方法研究了渗透势为？0.1 MPa的渗透胁迫下玉米幼苗叶片电位波动边际谱的变化规律及其意义,计算了边际谱特征参数边缘频率SEF（spectral edge frequency）、重心频率SCF（spectral center frequency）、边际谱熵MSE（marginal spectrum entropy）和动作电位灵敏指数Q。结果表明,玉米幼苗叶片电位波动的边际谱是分布在0.5 Hz以内的连续谱,在渗透胁迫下,SEF和SCF呈现出先减小后增加再减小的变化趋势,动作电位灵敏指数Q的变化与之相反,MSE表现出先增加再下降的变化趋势。通过与叶片生理指标MDA（malondialdehyde）和叶绿素含量变化的对比研究,发现MSE的峰值时间可以作为叶片细胞对渗透胁迫自我调节和适应性反应限度的标志,Q值的大小可以作为玉米叶片细胞对渗透胁迫反应灵敏度的标志,依据渗透胁迫下玉米幼苗叶片电位波动边际谱特征参数的变化,有可能对玉米叶片细胞的功能状态进行实时、在位和无损伤检测。
Bibliography:Leaf potential fluctuation comes from the changes of membrane potential in leaf cells, it caused by ion transporting across cell membranes and related to electrical coupling between cells. Understanding the life information behind leaf potential fluctuation is of great significance in study plant signal transduction, stress resistance evaluation, ecological and environmental monitoring, growth regulation, precision agriculture and many other fields. However, the leaf potential fluctuation of plant shows a very complex and non-stationary property. This complexity of the leaf potential fluctuation is the characteristic of life activities, but it brings great difficulties to analyze the information from the leaf potential fluctuation. Traditional signal analysis methods based Fourier Transform are only suitable for linear non-stationary signal processing. Different signal length leads to different results. Wavelet transform needs to pre-selected wavelet basis function, different wavelet basis will produce differ
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2017.01.027