Use of plant woody species electrical potential for irrigation scheduling

Electrical Responses of Pinus halepensis Mill. as an Indicator of Wildfire Risk in Mediterranean Forests by Complementing Live Fuel Moisture

Pinus halepensis forests, as Mediterranean-type ecosystems, are subject to high levels of wildfire risk in times of drought, with meteorological conditions of water stress and very high temperatures, mainly in summer. Considering the difficulty of knowing the phenological state of this species, the objective of this research was to evaluate the possibility of implementing the electrical responses (voltage and short-circuit current) as a variable in fire risk management models, compared to live fuel moisture. On the one hand, the obtained results demonstrate non-significant differences between the moisture content of the different fractions of the living branches (base and half of the branch and live fuel), even in times of drought with hydric stress and very high temperatures. Live fuel moisture of Pinus halepensis does not show significant seasonal variations under the influence of extreme fire risk factors. For this reason, it should be complemented with other variables for fire risk management models. On the other hand, the differences registered in the electrical signal show oscillations with significant variations, which are strongly correlated with the periods of extremely favourable meteorological conditions for wildfires. So, the voltages measured show ranges that correspond with great accuracy to the FWI. Voltage variation is dependent on the hydraulic dynamic plant behaviour and a result of the physiological response of pine trees to abiotic stress of drought. It is an easy-to-measure electrical parameter as well as a very reliable indicator with a high correlation with wildfire risk. Thus, electrical responses could add more knowledge about the phenological state of the trees in dependence on stress climatic conditions, allowing integration of these variables in the preventive wildfire modelling and management.

Benchmarking organic electrochemical transistors for plant electrophysiology

Plants are able to sense and respond to a myriad of external stimuli, using different signal transduction pathways, including electrical signaling. The ability to monitor plant responses is essential not only for fundamental plant science, but also to gain knowledge on how to interface plants with technology. Still, the field of plant electrophysiology remains rather unexplored when compared to its animal counterpart. Indeed, most studies continue to rely on invasive techniques or on bulky inorganic electrodes that oftentimes are not ideal for stable integration with plant tissues. On the other hand, few studies have proposed novel approaches to monitor plant signals, based on non-invasive conformable electrodes or even organic transistors. Organic electrochemical transistors (OECTs) are particularly promising for electrophysiology as they are inherently amplification devices, they operate at low voltages, can be miniaturized, and be fabricated in flexible and conformable substrates. Thus, in this study, we characterize OECTs as viable tools to measure plant electrical signals, comparing them to the performance of the current standard, Ag/AgCl electrodes. For that, we focused on two widely studied plant signals: the Venus flytrap (VFT) action potentials elicited by mechanical stimulation of its sensitive trigger hairs, and the wound response of Arabidopsis thaliana. We found that OECTs are able to record these signals without distortion and with the same resolution as Ag/AgCl electrodes and that they offer a major advantage in terms of signal noise, which allow them to be used in field conditions. This work establishes these organic bioelectronic devices as non-invasive tools to monitor plant signaling that can provide insight into plant processes in their natural environment.

Plant Bioelectronics and Biohybrids: The Growing Contribution of Organic Electronic and Carbon-Based Materials

Life in our planet is highly dependent on plants as they are the primary source of food, regulators of the atmosphere, and providers of a variety of materials. In this work, we review the progress on bioelectronic devices for plants and biohybrid systems based on plants, therefore discussing advancements that view plants either from a biological or a technological perspective, respectively. We give an overview on wearable and implantable bioelectronic devices for monitoring and modulating plant physiology that can be used as tools in basic plant science or find application in agriculture. Furthermore, we discuss plant-wearable devices for monitoring a plant's microenvironment that will enable optimization of growth conditions. The review then covers plant biohybrid systems where plants are an integral part of devices or are converted to devices upon functionalization with smart materials, including self-organized electronics, plant nanobionics, and energy applications. The review focuses on advancements based on organic electronic and carbon-based materials and discusses opportunities, challenges, as well as future steps.

Seasonal variations of electrical signals of Pinus halepensis Mill. in Mediterranean forests in dependence on climatic conditions

The temporal evolution of the electrical signal generated by Pinus halepensis was measured in a sample of 15 trees. Weekly experiments were carried out during a long-term campaign lasting over a year, while trials with a high frequency of measurements were also performed during several days. In the latter case, day-night oscillations of the electrical magnitudes were observed. Additionally, punctual meteorological events such as rainfall and electrical storms affect the electrical signal as well.The measured electrical intensity grows exponentially with the voltage. In fact, no electrical intensity that exceeds the threshold of 0.01 μA is gathered when voltage values are lower than 0.6 V. In general, higher electrical signals were gathered during the rainy seasons with moderate temperatures; while very low signals, including few measures of zero intensity, were obtained during the most stressful periods over the year, mainly by mid-summer.There is a strong correlation between the rainfall and the electrical signal. The rain-intensity correlation, together with sustained intensity values during the reproductive period in spring, suggests that this electrical magnitude could be an indicator of the physiological state of the tree and thus used for in situ and minimally invasive forest monitoring.

Variations of electric potential in the xylem of tree trunks associated with water content rhythms

Instantaneous electrical responses in plants have been widely studied, but the mechanism of spontaneous, periodic electric potential alternations in the xylem of tree trunks remains controversial. The generation of the electric potential can be explained by the electrode potential, which depends on ion concentrations near electrodes. However, several different hypotheses about its periodic variations have been proposed, including streaming potential, ion diffusion, charge transport, and oxygen turnover. Here, we performed long-term measurements on the electric potential and water content in the xylem of trees, and observed changes in the electric potential and transpiration rate in response to varied numbers of leaves, light radiation, temperature, and relative air humidity. The electric potential showed a distinct seasonal trend, combined with daily rhythms, and could be affected by environmental changes. Rapid changes in the electric potential routinely lagged behind those of the transpiration rate, but their ranges of change were proportional. Both annual and diurnal patterns of the electric potential were synchronous with the trees' water content. Moreover, we found potential function relationships between the electric potential and water content. Accordingly, we propose a new perspective, that the variations of the electric potential in tree xylem could be associated with water content rhythms.

Evaluation of electrical signals in pine trees in a mediterranean forest ecosystem

Electric potential differences in living plants are explained by theories based on sap flow. In order to acquire more advanced knowledge about the spatial distribution of these electric potential measures in trees, this research aims to analyze electrical signals in a population of Aleppo pines (Pinus halepensis Mill.) in a representative Mediterranean forest ecosystem. The specific research objective is to assess some of the most significant factors that influence the distribution pattern of those electric signals: tree age, measurement type and electrode placement. The research has been conducted in representative forest stands, obtaining measurements of different representative trees. After a statistical evaluation of the obtained results, the main conclusions of our research are: A.Tree maturity influences directly on electric potential. B.Maximum electrical signals can be measured in young pines showing values of 0.6 V and 0.6 µA for voltage and current, respectively. C.The distribution patterns of both voltage and short-circuit current depending on electrode placement are uniform.

Electrophysiological assessment of plant status outside a Faraday cage using supervised machine learning

Living organisms have evolved complex signaling networks to drive appropriate physiological processes in response to changing environmental conditions. Amongst them, electric signals are a universal method to rapidly transmit information. In animals, bioelectrical activity measurements in the heart or the brain provide information about health status. In plants, practical measurements of bioelectrical activity are in their infancy and transposition of technology used in human medicine could therefore, by analogy provide insight about the physiological status of plants. This paper reports on the development and testing of an innovative electrophysiological sensor that can be used in greenhouse production conditions, without a Faraday cage, enabling real-time electric signal measurements. The bioelectrical activity is modified in response to water stress conditions or to nycthemeral rhythm. Furthermore, the automatic classification of plant status using supervised machine learning allows detection of these physiological modifications. This sensor represents an efficient alternative agronomic tool at the service of producers for decision support or for taking preventive measures before initial visual symptoms of plant stress appear.