Noise reduction and analysis of leaf electrical signals of strap-leaved plants based on VMD-EWT

IF 7.7 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
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Abstract

Plant electrical signals are rapid responses of plants to external stimuli, and their characteristic changes are closely associated with plant life activities. However, due to their weak and low-frequency nature, the collected signals often suffer from significant noise interference. Therefore, investigating appropriate denoising methods is crucial for subsequent data analysis. In this study, a plant electrical signal synchronous acquisition system based on a 16-channel array electrode was employed to collect and store surface potentials of maize leaves under no stimulation, light stimulation, and electrical stimulation conditions. To address the issue of excessive noise in raw plant electrical signals, we propose a denoising method (VMD-EWT) that combines Variational Mode Decomposition (VMD) with Empirical Wavelet Transform (EWT). Based on the denoised multi-channel data obtained through these methods, we analyze the transmission characteristics and variation patterns of plant leaf electrical signals. The results demonstrate that traditional wavelet hard and soft thresholding-based denoising methods as well as VMD+EWT were utilized to remove noise from the plant surface potential data under electrical stimulation.The comprehensive evaluation indicators included the energy ratio and waveform analysis of the denoised signal in the time, frequency, and time–frequency domains. Based on a comprehensive assessment, it was determined that the VMD+EWT method exhibited superior denoising performance compared to the other two methods investigated in this study. Furthermore, further analysis of the surface potential of maize leaves under electrical stimulation revealed that the signal frequency primarily ranged from 0-30 Hz, with significant energy concentration observed particularly within the 0–1 Hz frequency range. Additionally, when action potentials were generated under electrical stimulation, there was a high concentration of energy. Further investigation into the transmission characteristics of surface potential in maize leaves exposed to electrical stimulation indicated a leaf potential transmission speed ranging from 29 mm/s to 51 mm/s.
基于 VMD-EWT 的带叶植物叶电信号降噪与分析
植物电信号是植物对外界刺激的快速反应,其特征变化与植物生命活动密切相关。然而,由于信号微弱且频率较低,采集到的信号往往会受到严重的噪声干扰。因此,研究适当的去噪方法对于后续的数据分析至关重要。本研究采用基于 16 通道阵列电极的植物电信号同步采集系统,采集并存储玉米叶片在无刺激、光刺激和电刺激条件下的表面电位。针对原始植物电信号噪声过大的问题,我们提出了一种去噪方法(VMD-EWT),该方法结合了变异模式分解(VMD)和经验小波变换(EWT)。基于通过这些方法获得的去噪多通道数据,我们分析了植物叶电信号的传输特性和变化规律。结果表明,传统的基于小波硬阈值和软阈值的去噪方法以及 VMD+EWT 均能去除电刺激下植物表面电位数据中的噪声。综合评价指标包括去噪信号在时域、频域和时频域的能量比和波形分析。通过综合评估,确定 VMD+EWT 方法与本研究中的其他两种方法相比,具有更优越的去噪性能。此外,对电刺激下玉米叶片表面电位的进一步分析表明,信号频率主要在 0-30 Hz 之间,尤其在 0-1 Hz 频率范围内观察到显著的能量集中。此外,在电刺激下产生动作电位时,能量高度集中。对受到电刺激的玉米叶片表面电位传输特性的进一步研究表明,叶片电位传输速度介于 29 毫米/秒至 51 毫米/秒之间。
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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