Zhong-Yi Wang

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.

Moisture content prediction of porcine meat by bioelectrical impedance spectroscopy

Abstract Moisture content is one of the most important elements influencing the quality of porcine meat. However, in recent years, illegally water-injected meat has been discovered repeatedly in the Chinese market. It is well known that high moisture content allows microbes to multiply easily, which can affect people’s health and causes major problems for the meat storage and processing industry. This research developed a rapid, low-cost method for measuring moisture content in porcine meat using bioelectrical impedance spectroscopy. Forty-four pieces of porcine longissimus dorsi muscle (LDM) were evaluated with a four-terminal electrode portable bioimpedance spectroscopy system. The samples were divided into a training set and a test set. Thirty samples were selected to be the training set to establish the model for the experiment. The results show good correlation (coefficient of determination R 2 = 0.802 ) between the impedance parameters and the moisture content value determined by standard chemical methods. Based on the model established using a linear prediction equation, we calculated the moisture content for the test set samples. Promising results were obtained for moisture content prediction of the samples, with R 2 = 0.879 for the test set. The method is thus shown to be feasible for moisture content prediction in porcine LDM, and is potentially useful for assessment and discrimination of meat quality.

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.

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.

Monitoring and analysis of electrical signals in water-stressed plants

Abstract A multi‐channel system was developed for simultaneous monitoring of multiple environmental factors and electrical signals in greenhouse grown cucumber plants. Using this system, electrical signals in response to water stress were recorded in the laboratory and in the greenhouse. Application to the roots of a 30% polyethylene glycol 6000 solution (‐0.84 MPa water potential) caused a significant decrease in the amplitude of an electrical signal induced by a dark/light change. The amplitude of the mean value of the signal in the transition from dark to light (40–50 min at dawn) was used to reflect the status of the plant under water stress, at which time the soil water content was reduced to 27%. The system was able to provide a long‐term stable tool to measure and analyse changes in electrical signals in plants in response to environmental changes.

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.

A THEORY MODEL FOR DESCRIPTION OF THE ELECTRICAL SIGNALS IN PLANT PART I

The ion mechanism for membrane potential of higher plant was discussed in this paper. A modified Hodgkin and Huxley model was developed for description of the electrical signals in plant. Three individual components of ionic current were formulated in terms of Hodgkin and Huxley model. It include potassium current IK, calcium current ICa, and anion current ICl-. It model will provide a useful tool to simulate the electrical activity in cell of higher plants, which respond to environmental changes.

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.

Developing a Penetrometer-Based Mapping System for Visualizing Silage Bulk Density from the Bunker Silo Face

For silage production, high bulk density (BD) is critical to minimize aerobic deterioration facilitated by oxygen intrusion. To precisely assess packing quality for bunker silos, there is a desire to visualize the BD distribution within the silage. In this study, a penetrometer-based mapping system was developed. The data processing included filtering of the penetration friction component (PFC) out of the penetration resistance (PR), transfer of the corrected penetration resistance (PRc) to BD, incorporation of Kriged interpolation for data expansion and map generation. The experiment was conducted in a maize bunker silo (width: 8 m, middle height: 3 m). The BD distributions near the bunker silo face were represented using two map groups, one related to horizontal- and the other to vertical-density distribution patterns. We also presented a comparison between the map-based BD results and core sampling data. Agreement between the two measurement approaches (RMSE = 19.175 kg·m−3) demonstrates that the developed penetrometer mapping system may be beneficial for rapid assessment of aerobic deterioration potential in bunker silos.

Feature Selection and Recognition Methods for Discovering Physiological and Bioinformatics RESTful Services

Many physiology and bioinformatics research institutions and websites have opened their own data analysis services and other related Web services. It is therefore very important to be able to quickly and effectively select and extract features from the Web service pages to learn about and use these services. This facilitates the automatic discovery and recognition of Representational State Transfer or RESTful services. However, this task is still challenging. Following the description feature pattern of a RESTful service, the authors proposed a Feature Pattern Search and Replace (FPSR) method. First, they applied a regular expression to perform a matching lookup. Then, a custom string was used to substitute the relevant feature pattern to avoid the segmentation of its feature pattern and the loss of its feature information during the segmentation process. Experimental results showed in the visualization that FPSR obtained a clearer and more obvious boundary with fewer overlaps than the test without using FPSR, thereby enabling a higher accuracy rate. Therefore, FPSR allowed the authors to extract RESTful service page feature information and achieve better classification results.