Dong-Jie Zhao

High-resolution non-contact measurement of the electrical activity of plants in situ using optical recording.

The limitations of conventional extracellular recording and intracellular recording make high-resolution multisite recording of plant bioelectrical activity in situ challenging. By combining a cooled charge-coupled device camera with a voltage-sensitive dye, we recorded the action potentials in the stem of Helianthus annuus and variation potentials at multiple sites simultaneously with high spatial resolution. The method of signal processing using coherence analysis was used to determine the synchronization of the selected signals. Our results provide direct visualization of the phloem, which is the distribution region of the electrical activities in the stem and leaf of H. annuus, and verify that the phloem is the main action potential transmission route in the stems of higher plants. Finally, the method of optical recording offers a unique opportunity to map the dynamic bioelectrical activity and provides an insight into the mechanisms of long-distance electrical signal transmission in higher plants.

Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array

Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dynamic spatio-temporal electrical activities in higher plants. Here, we used an 8 × 8 MEA with a polar distance of 450 μm to measure electrical activities from numerous cells simultaneously. The mapping of the data that were recorded from the MEA revealed the transfer mode of the thermally induced VPs in the leaves of Helianthus annuus L. seedlings in situ. These results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress.

Recording extracellular signals in plants: A modeling and experimental study

a b s t r a c t The purpose of this work was to determine the relationship between intracellular and ex- tracellular potential in plant cells and clarify the characteristic of extracellular measure- ment. Importantly, we aimed to explain the interesting phenomenon that the results using extracellular recording were significantly different from those of many research groups. We proposed a model to describe the relationship between intracellular measurement and extracellular measurement. To verify the model, simulations and experiments were per- formed. In the experiments, intracellular and extracellular recordings were obtained from Vicia faba L. cells using a multi-channel electrophysiological recording system. The exper- imental results indicated that extracellular potential could be calculated using the model and the amplitude of observed signals, and for one cell this was dozens of microvolts, but complex for multi-cells. The spatiotemporal features of extracellular recording were also verified by the experimental results. The model revealed a quantity relationship with the intracellular and extracellular potential of plant cells, and the superposition characteristic was explained.

Visualization of synchronous propagation of plant electrical signals using an optical recording method

Abstract Optical recording is widely used in electrophysiology research of animal cells, providing a good reference for the measurement of plant electrical signals at the multi-cell level. The aim of this research is to develop a method for monitoring the dynamic synchronous electrical activity in plant cells. Using a leaf strip of Vicia faba L as the specimen, a voltage-sensitive dye (VSD) and a stereo fluorescent microscope were applied to acquire an optical image time series, considering the different biological nature of the plant cell from the animal cell. Subsequently, the synchronous variation trend of the dye fluorescence intensity was extracted and observed through image analysis using self-designed signal processing procedures. This proved the feasibility of a visualization method of synchronous propagation of plant electrical signals.

A Web-Based Monitoring System as a Measurement Tool in Greenhouses Using Wireless Sensor Networks

In this work, we propose a Web-based monitoring system using wireless sensor networks (WSNs) to measure plant parameters and environmental factors in greenhouses. To detect and send these variables, e.g. leaf temperature, air humidity, a ZigBee-based WSN collects data, which is transmitted by GPRS modules and the Internet to a central computer, and all information, including the dynamic topology of WSNs, can be published via the Web. The system provides flexible configuration options for sensor nodes and transport downlink commands, i.e. sensors can be added or removed flexibly in a node without changing the hardware interface and data center service software. Also, the variance of the received signal strength indicator and link quality indicator (LQI) under different distributions of the growing plants was considered to estimate the network link quality to ensure reliable data transmission in the WSNs. Experiments show that the system is reliable, flexible, convenient, and provides good real-time and scalability characteristics.

Plant Electrical Signal Classification Based on Waveform Similarity

(1) Background: Plant electrical signals are important physiological traits which reflect plant physiological state. As a kind of phenotypic data, plant action potential (AP) evoked by external stimuli—e.g., electrical stimulation, environmental stress—may be associated with inhibition of gene expression related to stress tolerance. However, plant AP is a response to environment changes and full of variability. It is an aperiodic signal with refractory period, discontinuity, noise, and artifacts. In consequence, there are still challenges to automatically recognize and classify plant AP; (2) Methods: Therefore, we proposed an AP recognition algorithm based on dynamic difference threshold to extract all waveforms similar to AP. Next, an incremental template matching algorithm was used to classify the AP and non-AP waveforms; (3) Results: Experiment results indicated that the template matching algorithm achieved a classification rate of 96.0%, and it was superior to backpropagation artificial neural networks (BP-ANNs), supported vector machine (SVM) and deep learning method; (4) Conclusion: These findings imply that the proposed methods are likely to expand possibilities for rapidly recognizing and classifying plant action potentials in the database in the future.

Development of an electric-driven control system for a precision planter based on a closed-loop PID algorithm

Developed an electric-driven control system for the seed meter of a precision planter.A closed-loop PID algorithm was designed to control the seed plate rotation speed.Three PID tuning methods were studied for selecting the appropriate Ki, Kp, Kd parameter.Planting quality improved significantly by equipping with the developed electric-driven control system. This study presented the design of an electric-driven control system for the seed meter of a precision planter to avoid the issues of poor planting quality and low travel speed limitations associated with conventional ground wheel and chain driven planters. A closed-loop proportional-integral-derivative (PID) algorithm was deployed to control the seed plate rotation speed. The performance of three PID tuning methods (Ziegler-Nichols step response method (ZNM), Cohen-Coon method (CCM), and ChienHronesReswick method (CHRM)) was compared by Matlab-Simulink simulation, and results testified that the CCM had a better performance with smallest rise time of 0.018s, settling time of 0.082s and maximum overshoot of 26.1%. Field experiments indicated that a four-row planter equipped with the developed electric-driven control system had significantly better quality of feed index (QFI), miss index (MI), and precision index (PREC) values compared with those of a ground wheel and chain driven planter under equivalent working conditions. For a travel speed of 8.6km/h, the average values of the four rows for the QFI, MI, and the PREC were 98.62%, 1.29%, and 14.51%, respectively. For a high travel speed of 13.0km/h, the average QFI still achieved a value of 97.09%. Most of the components employed in the system were made in China, and the overall system cost was much less than similar systems obtained from abroad. As such, the proposed system is accessible to precision planters in developing countries.

Nondestructive In Situ Measurement Method for Kernel Moisture Content in Corn Ear

Moisture content is an important factor in corn breeding and cultivation. A corn breed with low moisture at harvest is beneficial for mechanical operations, reduces drying and storage costs after harvesting and, thus, reduces energy consumption. Nondestructive measurement of kernel moisture in an intact corn ear allows us to select corn varieties with seeds that have high dehydration speeds in the mature period. We designed a sensor using a ring electrode pair for nondestructive measurement of the kernel moisture in a corn ear based on a high-frequency detection circuit. Through experiments using the effective scope of the electrodes’ electric field, we confirmed that the moisture in the corn cob has little effect on corn kernel moisture measurement. Before the sensor was applied in practice, we investigated temperature and conductivity effects on the output impedance. Results showed that the temperature was linearly related to the output impedance (both real and imaginary parts) of the measurement electrodes and the detection circuit’s output voltage. However, the conductivity has a non-monotonic dependence on the output impedance (both real and imaginary parts) of the measurement electrodes and the output voltage of the high-frequency detection circuit. Therefore, we reduced the effect of conductivity on the measurement results through measurement frequency selection. Corn moisture measurement results showed a quadric regression between corn ear moisture and the imaginary part of the output impedance, and there is also a quadric regression between corn kernel moisture and the high-frequency detection circuit output voltage at 100 MHz. In this study, two corn breeds were measured using our sensor and gave R2 values for the quadric regression equation of 0.7853 and 0.8496.