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On the left-top: picture of several olive trees plant with the electrodes; on the left-down corner an enlargement focused on one two electrodes inside a plant. On the right the model where the two wire resistance measurement schematic is shown: electrode 1a and 1b are shown based on the plant stem physiology (picture modified from Venturaes et al. 2017). Additional electrodes can be added controlled by a switch to monitor concurrently several plant as shown (2a and 2b) and a reference electrode is used as an offset adjustment reference (ref.). Legend: Cell wall capillary forces (Fc arrow), mesophyll (Mc), symplastic and transmembrane pathway (Sp), apoplastic pathway (Ap), root cells (Rc), endodermis (En), casparian strip (Cs), epidermis (Ep), H2O vapor loss (broken blue arrow) and CO2 uptake (broken brown arrow); (Venturas et al., 2017); digital multimeter (DMM), Voltage (VM). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).
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The analysis of the electrophysiological activity of plants permits a real-time information of the plant status (e.g. light availability and water stress). However, even though it is clear that the role of the electrical signals in plant is crucial, especially in processes involving the propagation of rapid signals, a systematic approach for the in...
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Context 1
... (respectively model PXI-1033; TB-2605; PXI-4065; National Instruments Corporation), which permits AC/DC voltage, and 2wires resistance measurements. In particular, during the data acquisition, each pair of electrodes has been maintained at a fixed distance of 0.9 cm using a plastic support and inserted at the base of the stem of each plant (Fig. 5). This distance is chosen based on the electrical signal measure and is influenced by the stem variability and how the electrodes is implanted, it needs to be previously calibrated to be in the range of the instruments to maintain enough resolution without go out of scale. This set-up has been chosen in order to simplify the complexity ...
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... signals oscillations (Vodeneev et al., 2015) and thus it is possible to hypothesize that water stress has affected part of the signaling mechanism. The physiological mechanism implied in this phenomenon is still unclear and the increase in the resistance is probably related to the amount of water present in the tissues or due to embolized tissues (Fig. 5), but the meaning of a signal variance deserves a better understanding. The electrodes (Fig. 5) are inserted in the stem and are in contact with several different cells and cells' compartments that could increase the interactions and complexities of observed phenomena. The electric resistance signal variability could be easily ...
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... stress has affected part of the signaling mechanism. The physiological mechanism implied in this phenomenon is still unclear and the increase in the resistance is probably related to the amount of water present in the tissues or due to embolized tissues (Fig. 5), but the meaning of a signal variance deserves a better understanding. The electrodes (Fig. 5) are inserted in the stem and are in contact with several different cells and cells' compartments that could increase the interactions and complexities of observed phenomena. The electric resistance signal variability could be easily influenced by the interruption of the water flow in the xylem caused be phenomena of cavitation or ...
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Climate change, currently taking place worldwide and also in the Mediterranean area, is leading to a reduction in water availability and to groundwater salinization. Olive represents one of the most efficient tree crops to face these scenarios, thanks to its natural ability to tolerate moderate salinity and drought. In the present work, four olive...
Citations
... Other investigations have analyzed the extracellular ES´s (EES´s) that plants generate under several stimuli as a systemic response [Fromm & Lautner, 2007]. EES´s measurements are used in diagnostic systems, for example, for determining the water conditions of plants, such as Persea americana, Prunus domestica, and Olea europea, this for developing irrigation systems that deliver water only when the plants need it, reducing the consume of water in crop [Rios-Rojas et al., 2014;Comparini et al., 2020]. EES´s measurements have been also used for the identi cation of the origin of a stimulus with the purpose of identifying risks as plagues or adverse environmental conditions in a remote mode just by sensing EES´s [Chatterjee et al., 2015;Pereira et al., 2018]. ...
... In 2021, Meder et al. demonstrated that a self-adhering electrode placed on the surface of a non-ligni ed plant tissue could measure ES´s with similar performance as the electrode insertion technique and its mechanical properties make it plausible to be placed on leaves. However, the insertion technique is most used for measuring EES´s in ligni ed and non-ligni ed plant research [Comparini et al., 2020;Volkov & Shtessel, 2018;Volkov et al., 2019;Saraiva et al., 2017]. It consists of the insertion of two or more electrodes, usually made of stainless steel, into the plant tissue to allow measuring its electrical properties, such as potential differences or impedance in the vascular tissue. ...
Plants generate electrical signals in response to mild and severe environmental stimuli to transmit physiological information and ultimately trigger defensive responses during stressful events. It has been proposed that detecting and characterizing such signals could allow researchers to mimic specific electrical stimuli and provoke desirable responses in crops. Nevertheless, manually inserting electrodes in plant tissues leads to irregular data records due to a lack of uniformity across insertion events. For this reason, we manufactured a prototype of an electrode/needle insertion mechanism built in aluminum and acrylic and used it to measure electrical signals caused by drought in Capsicum annum plants. As results the mechanism had a more consistent performance in the characteristics of the insertion as depth, alignment between electrodes and with plant stem. As well, the mechanism was used for obtaining electrical signals (ES) related to drought, which, through a convolutional neural network (CNN) could be differentiated from control ES´s with an 84.91% recognition rate. It was concluded that the mechanism reduced variations in the characteristics of the electrode insertion and that it could be implemented for ES´s analysis.
... 81 Further research has shown that distinct patterns of electrical activity, as measured by electrical resistance and variance of the olive tree stem, can serve as bioelectrical signatures representing varying intensities of water stress. 82 This study demonstrated the feasibility of automatically classifying electrical activity, enabling the differentiation between intense and moderate water stress from control groups (no water stress). Specifically, the use of binary classifiers allowed the identification of the control group with 93% accuracy, while the mid-stress group achieved 76%, and the high-stress group reached 80% accuracy. ...
... Specifically, the use of binary classifiers allowed the identification of the control group with 93% accuracy, while the mid-stress group achieved 76%, and the high-stress group reached 80% accuracy. 82 Our results align with the findings of Tran et al. 81 and Comparini et al.. 82 They indicate that variations in plant electrical activity in response to different levels and conditions of water availability or unavailability may serve as early indicators of plant water status compared to conventional devices currently used for monitoring, such as leaf turgor pressure probes (Yara water sensors). Importantly, these electrical activity alterations exhibit superior accuracy in distinguishing between conditions, even in scenarios where different stress types, like salt and osmotic stress with equivalent water potential, need differentiation. ...
... Specifically, the use of binary classifiers allowed the identification of the control group with 93% accuracy, while the mid-stress group achieved 76%, and the high-stress group reached 80% accuracy. 82 Our results align with the findings of Tran et al. 81 and Comparini et al.. 82 They indicate that variations in plant electrical activity in response to different levels and conditions of water availability or unavailability may serve as early indicators of plant water status compared to conventional devices currently used for monitoring, such as leaf turgor pressure probes (Yara water sensors). Importantly, these electrical activity alterations exhibit superior accuracy in distinguishing between conditions, even in scenarios where different stress types, like salt and osmotic stress with equivalent water potential, need differentiation. ...
Plant electrophysiology has unveiled the involvement of electrical signals in the physiology and behavior of plants. Spontaneously generated bioelectric activity can be altered in response to changes in environmental conditions, suggesting that a plant’s electrome may possess a distinct signature associated with various stimuli. Analyzing electrical signals, particularly the electrome, in conjunction with Machine Learning (ML) techniques has emerged as a promising approach to classify characteristic electrical signals corresponding to each stimulus. This study aimed to characterize the electrome of common bean (Phaseolus vulgaris L.) cv. BRS-Expedito, subjected to different water availabilities, seeking patterns linked to these stimuli. For this purpose, bean plants in the vegetative stage were subjected to the following treatments: (I) distilled water; (II) half-strength Hoagland’s nutrient solution; (III) −2 MPa PEG solution; and (IV) −2 MPa NaCl solution. Electrical signals were recorded within a Faraday’s cage using the MP36 electronic system for data acquisition. Concurrently, plant water status was assessed by monitoring leaf turgor variation. Leaf temperature was additionally measured. Various analyses were conducted on the electrical time series data, including arithmetic average of voltage variation, skewness, kurtosis, Probability Density Function (PDF), autocorrelation, Power Spectral Density (PSD), Approximate Entropy (ApEn), Fast Fourier Transform (FFT), and Multiscale Approximate Entropy (ApEn(s)). Statistical analyses were performed on leaf temperature, voltage variation, skewness, kurtosis, PDF µ exponent, autocorrelation, PSD β exponent, and approximate entropy data. Machine Learning analyses were applied to identify classifiable patterns in the electrical time series. Characterization of the electrome of BRS-Expedito beans revealed stimulus-dependent profiles, even when alterations in water availability stimuli were similar in terms of quality and intensity. Additionally, it was observed that the bean electrome exhibits high levels of complexity, which are altered by different stimuli, with more intense and aversive stimuli leading to drastic reductions in complexity levels. Notably, one of the significant findings was the 100% accuracy of Small Vector Machine in detecting salt stress using electrome data. Furthermore, the study highlighted alterations in the plant electrome under low water potential before observable leaf turgor changes. This work demonstrates the potential use of the electrome as a physiological indicator of the water status in bean plants.
... A shortage of water in the leaves affects chlorophyll production, stimulates chlorophyll breakdown, and accelerates leaf yellowing. Precipitation has a direct impact on the amount of chlorophyll a in leaves, which increases dramatically during the rainy season, as seen in the WP ecosystem (Comparini et al., 2020). The quantity of chlorophyll pigments in the leaf is connected to physiological stress caused by interstitial salinity, inundation periods, water availability, variations in the incidence of solar irradiance, humidity, and climatic impact, all of which influence leaf development (Castellanos-Basto et al., 2021). ...
Coastline ecosystems are resilient, and the mangrove species that inhabit them are well-suited to deal with harsh environmental stresses. Mangrove leaves are specialised plant structures that enable them to preserve their photosynthetic capability and functionality despite frequent changes in their habitats. Along the coastline of Guyana, we studied the morphological characteristics and chlorophyll content of 400 leaves taken from Laguncularia racemosa (L.) C.F. Gaertn., 1807 (Myrtales Combretaceae) trees found in Number 6 Village and Wellington Park mangrove ecosystems. The nearest individual sampling method was utilised to sample leaves throughout the wet and dry seasons. Our results demonstrate that Laguncularia racemosa leaves are mesophyllous, and leaf characteristics such as length, width, area, perimeter, mass, leaf specific area, and relative water content differed between the two ecosystem types, in both seasons. Significant correlations between leaf parameters were documented (p < 0.05, R > 0.75), with the Number 6 Village ecosystem during the dry season and the Wellington Park ecosystem during the wet season having greater values. Differences in chlorophyll content were also seen in the two types of ecosystems, but not seasonally. The results of our study suggest, to some extent, that plant structures can exhibit site-specific characteristics to preserve their survivability in different ecosystem types.
... In this study, the degraded mangrove ecosystem possessed the highest chlorophyll a and b, as well as the total overall chlorophyll content, followed by the natural to some extent, the productiveness of the mangrove ecosystem. In mangrove forests, photoinhibition and other leaf-damaging effects are more likely to occur when there is an increased frequency of light saturation (Comparini et al., 2020). Thus, the physiological stress caused by inundating periods, the changes in solar intensity, available water, interstitial salinity, climate impact, and moisture content is affiliated with the quantity of photosynthetic pigments in the leaf, which affects the leaf's development concurrently over time (Floresde-Santiago et al., 2016). ...
Mangrove leaves have unique features that enable them to cope with shifting environmental conditions while preserving their general functionality and efficiency. We examined the morphological characteristics and chlorophyll content (spectroscopically) of 600 mature Avicennia germinans leaves selected from 30 trees located in one degraded, one restored, and one natural mangrove ecosystem along Guyana's coastline. Systematic sampling was carried out using the closest individual sampling method in the wet and dry seasons. We hypothesized that both habitat type and seasonality influence the leaf traits and chlorophyll content of A. germinans. Our findings showed that A. germinans leaves are mesophyllous, and traits such as leaf perimeter, area, length, width, dry mass, wet mass, turgid mass, leaf‐specific area, and relative water content showed fluctuations in ecosystems (one‐way ANOVA, p < .05) as well as seasonally (paired t ‐test, p < .05). Substantial, positive correlations ( p < .05, R > .75) were also established for over 10 leaf parameters in both seasons while PCA and multiple regression analyses further confirmed the strong relationships between leaf morphological features and their respective locations. Changes in chlorophyll concentration were most noticeable in the degraded ecosystem while variations in leaf traits were more pronounced in the restored mangrove area. This may be due to the various disturbances found in each ecosystem coupled with fluctuations in the seasons. Our results demonstrate that mangroves, to some extent, alter their plant structures to cope with environmental stressors present in the various ecosystems they thrive in to maintain their survival.
... Similarly, inverse modeling using system identification approach for light stimulus has been studied in [22]. Water stress in different intensities in the form of high and medium drought and its correlation with plant electrical response has been used for classification in olive trees [23]. Wavelet transform based analyses have also been reported on plant signals and photosynthetic activities in [24]. ...
Plant electrophysiological response contains useful signature of its environment and health which can be utilized using suitable statistical analysis for developing an inverse model to classify the stimulus applied to the plant. In this paper, we have presented a statistical analysis pipeline to tackle a multiclass environmental stimuli classification problem with unbalanced plant electrophysiological data. The objective here is to classify three different environmental chemical stimuli, using fifteen statistical features, extracted from the plant electrical signals and compare the performance of eight different classification algorithms. A comparison using reduced dimensional projection of the high dimensional features via principal component analysis (PCA) has also been presented. Since the experimental data is highly unbalanced due to varying length of the experiments, we employ a random under-sampling approach for the two majority classes to create an ensemble of confusion matrices to compare the classification performances. Along with this, three other multi-classification performance metrics commonly used for unbalanced data viz. balanced accuracy, F1-score and Matthews correlation coefficient have also been analyzed. From the stacked confusion matrices and the derived performance metrics, we choose the best feature-classifier setting in terms of the classification performances carried out in the original high dimensional vs. the reduced feature space, for this highly unbalanced multiclass problem of plant signal classification due to different chemical stress. Difference in the classification performances in the high vs. reduced dimensions are also quantified using the multivariate analysis of variance (MANOVA) hypothesis testing. Our findings have potential real-world applications in precision agriculture for exploring multiclass classification problems with highly unbalanced datasets, employing a combination of existing machine learning algorithms. This work also advances existing studies on environmental pollution level monitoring using plant electrophysiological data.
... It is worth noting that, still, many aspects of plant responses are not sufficiently well-elaborated and understood. Plant electrostimulations, response to external physical quantities and stress, intracellular measurements, and depolarizing currents and fluxes (i.e., Cl − and Ca 2+ ) are fundamental points which involve the electrophysiology of plants, vegetal organisms, and the study of health and applied stress in plants through electrical signals generated by the plant itself [25][26][27]. It thus becomes apparent how plants are able to generate electrical responses as a function of external physical quantities. ...
This research activity regards the development of a sensor based on a Sansevieria cylindrica plant for the measurement of visible radiation. The proposed solution, based on the adoption of a soil-plant system as a chemo-electrical transducer, goes beyond “classical” silicon-based approaches that are not biodegradable nor eco-friendly and that produce CO2 from the production step to the disposal phase. It is worth noting that no toxicity can be associated with plants and, due to the natural process of photosynthesis, these systems, used as living sensors, are even able to absorb carbon dioxide from the environment. The working principle of the proposed device based on the metabolic processes of the natural organisms present in the living system, soil and plant, as a function of visible radiation will be presented here. Particular emphasis will be also given to the analysis of the visible radiation spectrum, the metrological characterization, the performance of the device, and the analyses in terms of insensitivity to other external physical quantities. The obtained results evince the suitability of the proposed device which presents the prerogative of being environmentally friendly, self-generating, battery-less, simple, mimetic, low-cost, non-toxic, and biodegradable. The aforementioned features pave the road for a disruptive technological approach for an ecological transition which can impact the variegated applied field, including in the security, cultural heritage, smart home, and smart agriculture aspects.
... VW transmission often coincides with the transpiration rate of the plants. The production of VW requires a certain level of stress before it can be transmitted between plant tissues for a longer period [46]. VW transmission resulted in changes in Fv/Fm and SPAD parameters, thus reflecting changes in transpiration in strawberry seedlings. ...
Drought area expansion has a great impact on the growth and development of plants. To contribute to the water management of strawberry, this work aims to study the chronological relationship between the electrical signals and representative physiological parameters of strawberry seedlings under drought stress. This study analyzed the characteristic variables of the electrical signals; physiological parameters under drought; and control treatments. Moreover, we compared the chronological sequence of the appearance of significant differences between drought and control treatment in terms of their physiological parameters and electrical signals. The results showed that with the increase of drought treatment, the time domain parameters (peak-to-peak value, standard deviation) and frequency domain parameters (spectral of central gravity, power spectrum entropy) of the drought-treated electrical signals showed significant differences from the control on Day 2 and Day 6, respectively (p < 0.05). The root vitality of the drought treatment was significantly different from the control on Day 4 (p < 0.05); the Fv/Fm and the SPAD were significantly different (p < 0.05) on Day 7. Electrical signals first start to show a significant difference between drought and control treatment, followed by physiological parameters. Therefore, the electrical signal can be used as an early indicator of drought stress conditions. This will provide a scientific basis for the actual water management of strawberry seedlings. It also provides a methodological and theoretical basis for other studies analyzing the relationship between plant physiological parameters and electrical signals under other stress conditions.
... Slow wave potentials are more widespread among the plant population and are related to responses to external stimuli (wounding, heat, etc.). 202,203 While these potentials also consist of transient changes in membrane potential, they differ from action potentials in their timing, being much slower with a delayed membrane repolarization, and in the variation of their amplitude, increasing in response with the stimulus intensity. 192,193 Furthermore, while slow wave potentials can be transmitted over long distances, their amplitude decays with distance, are not able to self-propagate as efficiently as action potentials, and they are known to be induced by the inhibition of the H + -ATPase, which is responsible for the slower kinetics of these signals when compared to voltage-gated calcium channels. ...
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.
... Finally, to identify the Drought stress intensity in Olea europaea L., they were exposed to three different irrigation regimes. Later ES was sensed and analyzed by a binary classifier method, achieving a complete plant water condition monitoring (Comparini et al. 2020). ...
... Nevertheless, the methodologies for the caption of the signals are not exactly practical; the most common technique consists of the insertion of electrodes in the plant (stem or branches); usually, plants are placed under a Faraday cage to avoid Herde et al. (1995Herde et al. ( , 1996 From and Spanswick (1993) Davies (1996, 1997) Ward (1996) Krol et al. (2006) Favre and Agosti (2007 The list is divided by the type of electrical stimuli applied: voltage (classified in low values under 2 V and high values above 3 V) and current (classified in low values under 300 mA and high values above 500 mA). The classification was made according the number of investigations that used similar ranges electrical interference and are used diverse hardware and software for the signal recording in succession as seen in Fig. 3a (Wildon et al. 1992;Stankovic and Davies 1996;Retivin et al. 1997;Stankovic et al. 1998;Lautner et al. 2005;Krol et al. 2006;Saraiva et al. 2017;Volkov and Shtessel 2017;Simmi et al. 2020;Comparini et al. 2020;Tinturier et al. 2020;Silva et al. 2021). The usual methodology presents the disadvantage of a complex assembly. ...
As plants are living forms that cannot communicate their condition (stress, requirements) as animals, they have been studied to find chemical or physical signals that could help understand the plant requirements for several purposes such as substances and food production. Different research supports electrical signals (ES) related to different stress conditions in plants as damage or drought. Some others have identified and classified these signals generated by stress condition using diverse Artificial intelligence (AI) techniques. Finally, some other researches have used electricity as a stimulator obtaining a response as chemical compounds production, gene expression and growth-promoting. In a few words, ES from plants can be interpreted, which could also be sent back to plants. Based on the bibliographic revision in this work, it is proposed that experiments and research, where the ES serves to activate chemical and physiological mechanisms or as elicitor, are required to consider the electrical signals as a possible communication pathway with plants.
... During prolonged periods of light and hydric stress, the photosynthetic activity of the leaf and the opening of the stoma decreases because of the reduction in the availability of reaction centers [17]. On the contrary, precipitation directly affect the concentration of Chl-a in leaves, increasing significantly during the rainy season [18,19]. ...
... Chl-a concentration significantly changes (p < 0.05) as a function of Ti, Si, fL of the MF, DBH of the trees, MF type, species, and seasonality. The results are consistent with various authors [17,35,45], who explained that the variability in Chl-a between R. mangle and A. germinans is due to the relationship to their DBH, BA, and the development of the tissue of their leaves according to the species, the presence of nearby water sources, local characteristics, and seasons. However, it seems that DBH, BA, and H are not exclusive constraints to estimate Chl-a. ...
The pigment content in leaves has commonly been used to characterize vegetation condition. However, few studies have assessed temporal changes of local biotic and abiotic factors on leaf pigments. Here, we evaluated the effect of local environmental variables and tree structural characteristics , in the chlorophyll-a leaf concentration (Chl-a) associated with temporal change in two mangrove species. Rhizophora mangle (R. mangle) and Avicennia germinans (A. germinans) trees of a fringe mangrove forest (FMF) and lower basin mangrove forest (BMF) were visited over a period of one year, to obtain radiometric readings at leaf level to estimate Chl-a. Measurements on tree characteristics included diameter at breast height (DBH), basal area (BA), and maximum height (H). Environmental variables included soil interstitial water temperature (Ti), salinity (Si), and dissolved oxygen (Oi), flood level (fL), ambient temperature (Tamb), and relative humidity (Hrel). Generalized linear models and covariance analysis showed that the variation of Chl-a is mainly influenced by the species, the interaction between species and mangrove forest type, DBH, seasonality and its influence on the species, soil conditions, and fL. Studies to assess spatial and temporal change on mangrove forests using the spectral characteristics of the trees should also consider the temporal variation of leave chlorophyll-a concentration.
