Plant "electrome" can be pushed toward a self-organized critical state by external cues: Evidences from a study with soybean seedlings subject to different environmental conditions

Common bean under different water availability reveals classifiable stimuli-specific signatures in plant electrome

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.

Ascent and Attachment in Pea Plants: A Matter of Iteration

Pea plants (Pisum sativum L.) can perceive the presence of potential supports in the environment and flexibly adapt their behavior to clasp them. How pea plants control and perfect this behavior during growth remains unexplored. Here, we attempt to fill this gap by studying the movement of the apex and the tendrils at different leaves using three-dimensional (3D) kinematical analysis. We hypothesized that plants accumulate information and resources through the circumnutation movements of each leaf. Information generates the kinematical coordinates for the final launch towards the potential support. Results suggest that developing a functional approach to grasp movement may involve an interactive trial and error process based on continuous cross-talk across leaves. This internal communication provides evidence that plants adopt plastic responses in a way that optimally corresponds to support search scenarios.

Evaluating Bacterial Nanocellulose Interfaces for Recording Surface Biopotentials from Plants

The study of plant electrophysiology offers promising techniques to track plant health and stress in vivo for both agricultural and environmental monitoring applications. Use of superficial electrodes on the plant body to record surface potentials may provide new phenotyping insights. Bacterial nanocellulose (BNC) is a flexible, optically translucent, and water-vapor-permeable material with low manufacturing costs, making it an ideal substrate for non-invasive and non-destructive plant electrodes. This work presents BNC electrodes with screen-printed carbon (graphite) ink-based conductive traces and pads. It investigates the potential of these electrodes for plant surface electrophysiology measurements in comparison to commercially available standard wet gel and needle electrodes. The electrochemically active surface area and impedance of the BNC electrodes varied based on the annealing temperature and time over the ranges of 50 °C to 90 °C and 5 to 60 min, respectively. The water vapor transfer rate and optical transmittance of the BNC substrate were measured to estimate the level of occlusion caused by these surface electrodes on the plant tissue. The total reduction in chlorophyll content under the electrodes was measured after the electrodes were placed on maize leaves for up to 300 h, showing that the BNC caused only a 16% reduction. Maize leaf transpiration was reduced by only 20% under the BNC electrodes after 72 h compared to a 60% reduction under wet gel electrodes in 48 h. On three different model plants, BNC-carbon ink surface electrodes and standard invasive needle electrodes were shown to have a comparable signal quality, with a correlation coefficient of >0.9, when measuring surface biopotentials induced by acute environmental stressors. These are strong indications of the superior performance of the BNC substrate with screen-printed graphite ink as an electrode material for plant surface biopotential recordings.

Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind

Each of us made the remarkable journey from mere matter to mind: starting life as a quiescent oocyte ("just chemistry and physics"), and slowly, gradually, becoming an adult human with complex metacognitive processes, hopes, and dreams. In addition, even though we feel ourselves to be a unified, single Self, distinct from the emergent dynamics of termite mounds and other swarms, the reality is that all intelligence is collective intelligence: each of us consists of a huge number of cells working together to generate a coherent cognitive being with goals, preferences, and memories that belong to the whole and not to its parts. Basal cognition is the quest to understand how Mind scales-how large numbers of competent subunits can work together to become intelligences that expand the scale of their possible goals. Crucially, the remarkable trick of turning homeostatic, cell-level physiological competencies into large-scale behavioral intelligences is not limited to the electrical dynamics of the brain. Evolution was using bioelectric signaling long before neurons and muscles appeared, to solve the problem of creating and repairing complex bodies. In this Perspective, I review the deep symmetry between the intelligence of developmental morphogenesis and that of classical behavior. I describe the highly conserved mechanisms that enable the collective intelligence of cells to implement regulative embryogenesis, regeneration, and cancer suppression. I sketch the story of an evolutionary pivot that repurposed the algorithms and cellular machinery that enable navigation of morphospace into the behavioral navigation of the 3D world which we so readily recognize as intelligence. Understanding the bioelectric dynamics that underlie construction of complex bodies and brains provides an essential path to understanding the natural evolution, and bioengineered design, of diverse intelligences within and beyond the phylogenetic history of Earth.

The Electrome of a Parasitic Plant in a Putative State of Attention Increases the Energy of Low Band Frequency Waves: A Comparative Study with Neural Systems

Selective attention is an important cognitive phenomenon that allows organisms to flexibly engage with certain environmental cues or activities while ignoring others, permitting optimal behaviour. It has been proposed that selective attention can be present in many different animal species and, more recently, in plants. The phenomenon of attention in plants would be reflected in its electrophysiological activity, possibly being observable through electrophytographic (EPG) techniques. Former EPG time series obtained from the parasitic plant Cuscuta racemosa in a putative state of attention towards two different potential hosts, the suitable bean (Phaseolus vulgaris) and the unsuitable wheat (Triticum aestivum), were revisited. Here, we investigated the potential existence of different band frequencies (including low, delta, theta, mu, alpha, beta, and gamma waves) using a protocol adapted from neuroscientific research. Average band power (ABP) was used to analyse the energy distribution of each band frequency in the EPG signals, and time dispersion analysis of features (TDAF) was used to explore the variations in the energy of each band. Our findings indicated that most band waves were centred in the lower frequencies. We also observed that C. racemosa invested more energy in these low-frequency waves when suitable hosts were present. However, we also noted peaks of energy investment in all the band frequencies, which may be linked to extremely low oscillatory electrical signals in the entire tissue. Overall, the presence of suitable hosts induced a higher energy power, which supports the hypothesis of attention in plants. We further discuss and compare our results with generic neural systems.

Decision-Making Underlying Support-Searching in Pea Plants

Finding a suitable support is a key process in the life history of climbing plants. Those that find a suitable support have greater performance and fitness than those that remain prostrate. Numerous studies on climbing plant behavior have elucidated the mechanistic details of support-searching and attachment. Far fewer studies have addressed the ecological significance of support-searching behavior and the factors that affect it. Among these, the diameter of supports influences their suitability. When the support diameter increases beyond some point, climbing plants are unable to maintain tensional forces and therefore lose attachment to the trellis. Here, we further investigate this issue by placing pea plants (Pisum sativum L.) in the situation of choosing between supports of different diameters while their movement was recorded by means of a three-dimensional motion analysis system. The results indicate that the way pea plants move can vary depending on whether they are presented with one or two potential supports. Furthermore, when presented with a choice between thin and thick supports, the plants showed a distinct preference for the former than the latter. The present findings shed further light on how climbing plants make decisions regarding support-searching and provide evidence that plants adopt one of several alternative plastic responses in a way that optimally corresponds to environmental scenarios.

Systemic Signals Induced by Single and Combined Abiotic Stimuli in Common Bean Plants

To survive in a dynamic environment growing fixed to the ground, plants have developed mechanisms for monitoring and perceiving the environment. When a stimulus is perceived, a series of signals are induced and can propagate away from the stimulated site. Three distinct types of systemic signaling exist, i.e., (i) electrical, (ii) hydraulic, and (iii) chemical, which differ not only in their nature but also in their propagation speed. Naturally, plants suffer influences from two or more stimuli (biotic and/or abiotic). Stimuli combination can promote the activation of new signaling mechanisms that are explicitly activated, as well as the emergence of a new response. This study evaluated the behavior of electrical (electrome) and hydraulic signals after applying simple and combined stimuli in common bean plants. We used simple and mixed stimuli applications to identify biochemical responses and extract information from the electrical and hydraulic patterns. Time series analysis, comparing the conditions before and after the stimuli and the oxidative responses at local and systemic levels, detected changes in electrome and hydraulic signal profiles. Changes in electrome are different between types of stimulation, including their combination, and systemic changes in hydraulic and oxidative dynamics accompany these electrical signals.

Simulated Analysis of Influence of Changes in H+-ATPase Activity and Membrane CO2 Conductance on Parameters of Photosynthetic Assimilation in Leaves

Photosynthesis is an important process in plants which influences their development and productivity. Many factors can control the efficiency of photosynthesis, including CO₂ conductance of leaf mesophyll, which affects the CO₂ availability for Rubisco. It is known that electrical stress signals can decrease this conductance, and the response is probably caused by inactivation of H⁺-ATPase in the plasma membrane. In the current work, we analyzed the influence of both CO₂ conductance in the plasma membrane, and chloroplast envelopes and H⁺-ATPase activity on photosynthetic CO₂ assimilation, using a two-dimensional mathematical model of photosynthesis in leaves. The model included a description of assimilation on the basis of the Farquhar-von Caemmerer-Berry model, ion transport through the plasma membrane, diffusion of CO₂ in the apoplast, and transport of CO₂ through the plasma membrane and chloroplast envelope. The model showed that the photosynthetic CO₂ assimilation rate was mainly dependent on the plasma membrane and chloroplast envelope conductance; direct influence of the H⁺-ATPase activity (through changes in pH and CO₂/HCO₃^- concentration ratio) on this rate was weak. In contrast, both changes in CO₂ conductance of the plasma membrane and chloroplast envelopes and changes in the H⁺-ATPase activity influenced spatial heterogeneity of the CO₂ assimilation on the leaf surface in the simulated two-dimensional system. These effects were also observed under simultaneous changes in the CO₂ conductance of the plasma membrane and H⁺-ATPase activity. Qualitatively similar influence of changes in the CO₂ conductance of the plasma membrane and chloroplast envelopes, and changes in the H⁺-ATPase activity on photosynthesis were shown for two different densities of stomata in the simulated leaf; however, lowering the density of stomata decreased the assimilation rate and increased the heterogeneity of assimilation. The results of the model analysis clarify the potential influence of H⁺-ATPase inactivation on photosynthesis, and can be the basis for development of new methods for remote sensing of the influence of electrical signals.

Classification of various nutrient deficiencies in tomato plants through electrophysiological signal decomposition and sample space reduction

Plants leave testimonies of undergoing physical state by depicting distinct variations in their electrophysiological data. Adequate nutrition of plants signifies their role in the growth and a plentiful harvest. Plant signal data carries enough information to detect and analyse nutrient deficiency. Classification of nutrient deficiencies through signal decomposition and bilevel measurements has not been reported earlier. The proposed work explores tomato plants in four-time cycles (Early Morning, Morning, After Noon, Night) of macronutrients Calcium (Ca), Nitrogen (N) and micronutrients Manganese (Mn), Iron (Fe). Using the Empirical Mode Decomposition method (EMD), signals are decomposed into Intrinsic Mode Functions (IMF) in 10-levels. Further, Intrinsic mode functions are grouped into two clusters to extract descriptive data statistics and bi-level measurements. Then a novel sample selection method is proposed to achieve a better classification rate by reducing sample space. A binary classification model is built to train and test 15 features individually using discriminant analysis and naïve-Bayes classifier variants. The reported results achieved a classification rate up to 98% after 5-fold cross-validation. Attained findings endorse novel pathways for detection and classification of nutrient deficiencies in the early stages, consequently promoting prevention and treatment approaches earliest to the appearance of symptoms, also helping to enhance plant growth.

Do plants pay attention? A possible phenomenological-empirical approach

Attention is the important ability of flexibly controlling limited cognitive resources. It ensures that organisms engage with the activities and stimuli that are relevant to their survival. Despite the cognitive capabilities of plants and their complex behavioural repertoire, the study of attention in plants has been largely neglected. In this article, we advance the hypothesis that plants are endowed with the ability of attaining attentive states. We depart from a transdisciplinary basis of philosophy, psychology, physics and plant ecophysiology to propose a framework that seeks to explain how plant attention might operate and how it could be studied empirically. In particular, the phenomenological approach seems particularly important to explain plant attention theoretically, and plant electrophysiology seems particularly suited to study it empirically. We propose the use of electrophysiological techniques as a viable way for studying it, and we revisit previous work to support our hypothesis. We conclude this essay with some remarks on future directions for the study of plant attention and its implications to botany.

Influence of Burning-Induced Electrical Signals on Photosynthesis in Pea Can Be Modified by Soil Water Shortage

Local damage to plants can induce fast systemic physiological changes through generation and propagation of electrical signals. It is known that electrical signals influence numerous physiological processes including photosynthesis; an increased plant tolerance to actions of stressors is a result of these changes. It is probable that parameters of electrical signals and fast physiological changes induced by these signals can be modified by the long-term actions of stressors; however, this question has been little investigated. Our work was devoted to the investigation of the parameters of burning-induced electrical signals and their influence on photosynthesis under soil water shortage in pea seedlings. We showed that soil water shortage decreased the amplitudes of the burning-induced depolarization signals (variation potential) and the magnitudes of photosynthetic inactivation (decreasing photosynthetic CO₂ assimilation and linear electron flow and increasing non-photochemical quenching of the chlorophyll fluorescence and cyclic electron flow around photosystem I) caused by these signals. Moreover, burning-induced hyperpolarization signals (maybe, system potentials) and increased photosynthetic CO₂ assimilation could be observed under strong water shortage. It was shown that the electrical signal-induced increase of the leaf stomatal conductance was a potential mechanism for the burning-induced activation of photosynthetic CO₂ assimilation under strong water shortage; this mechanism was not crucial for photosynthetic response under control conditions or weak water shortage. Thus, our results show that soil water shortage can strongly modify damage-induced electrical signals and fast physiological responses induced by these signals.

Sowing the seeds of intentionality: Motor intentions in plants

Motor intention/intentionality has been investigated from a wide variety of perspectives: some researchers have, for example, been focusing on the purely physical and mechanical aspects underlying the control of action, while others have been concentrating on subjective intentionality. Basically, all approaches ranging from the neuroscientific to phenomenological-inspired ones have been used to investigate motor intentions. The current study set out to examine motor intentions in connection to plant behavior utilizing the final goal of plant action as the definition of its motor intention. Taking a wide-angle approach, the first part of the review is dedicated to examining philosophical and psychological studies on motor intentions. Recent data demonstrating that plant behavior does indeed seem goal-directed will then be reviewed as we ponder the possibility of purposeful or intentional plant responses to stimuli and stress conditions in their environment. The article will draw to a close as we examine current theories attempting to explain plants' overt behavior and corresponding covert representations.

Machine Learning for Automatic Classification of Tomato Ripening Stages Using Electrophysiological Recordings

The physiological processes underlying fruit ripening can lead to different electrical signatures at each ripening stage, making it possible to classify tomato fruit through the analysis of electrical signals. Here, the electrical activity of tomato fruit (Solanum lycopersicum var. cerasiforme) during ripening was investigated as tissue voltage variations, and Machine Learning (ML) techniques were used for the classification of different ripening stages. Tomato fruit was harvested at the mature green stage and placed in a Faraday's cage under laboratory-controlled conditions. Two electrodes per fruit were inserted 1 cm apart from each other. The measures were carried out continuously until the entire fruits reached the light red stage. The time series were analyzed by the following techniques: Fast Fourier Transform (FFT), Wavelet Transform, Power Spectral Density (PSD), and Approximate Entropy. Descriptive analysis from FFT, PSD, and Wavelet Transform were used for PCA (Principal Component Analysis). Finally, ApEn, PCA1, PCA2, and PCA3 were obtained. These features were used in ML analyses for looking for classifiable patterns of the three different ripening stages: mature green, breaker, and light red. The results showed that it is possible to classify the ripening stages using the fruit's electrical activity. It was also observed, using precision, sensitivity, and F1-score techniques, that the breaker stage was the most classifiable among all stages. It was found a more accurate distinction between mature green × breaker than between breaker × light red. The ML techniques used seem to be a novel tool for classifying ripening stages. The features obtained from electrophysiological time series have the potential to be used for supervised training, being able to help in more accurate classification of fruit ripening stages.

Consciousness and cognition in plants

Unlike animal behavior, behavior in plants is traditionally assumed to be completely determined either genetically or environmentally. Under this assumption, plants are usually considered to be noncognitive organisms. This view nonetheless clashes with a growing body of empirical research that shows that many sophisticated cognitive capabilities traditionally assumed to be exclusive to animals are exhibited by plants too. Yet, if plants can be considered cognitive, even in a minimal sense, can they also be considered conscious? Some authors defend that the quest for plant consciousness is worth pursuing, under the premise that sentience can play a role in facilitating plant's sophisticated behavior. The goal of this article is not to provide a positive argument for plant cognition and consciousness, but to invite a constructive, empirically informed debate about it. After reviewing the empirical literature concerning plant cognition, we introduce the reader to the emerging field of plant neurobiology. Research on plant electrical and chemical signaling can help shed light into the biological bases for plant sentience. To conclude, we shall present a series of approaches to scientifically investigate plant consciousness. In sum, we invite the reader to consider the idea that if consciousness boils down to some form of biological adaptation, we should not exclude a priori the possibility that plants have evolved their own phenomenal experience of the world. This article is categorized under: Cognitive Biology > Evolutionary Roots of Cognition Philosophy > Consciousness Neuroscience > Cognition.

Electrical Signals, Plant Tolerance to Actions of Stressors, and Programmed Cell Death: Is Interaction Possible?

In environmental conditions, plants are affected by abiotic and biotic stressors which can be heterogenous. This means that the systemic plant adaptive responses on their actions require long-distance stress signals including electrical signals (ESs). ESs are based on transient changes in the activities of ion channels and H⁺-ATP-ase in the plasma membrane. They influence numerous physiological processes, including gene expression, phytohormone synthesis, photosynthesis, respiration, phloem mass flow, ATP content, and many others. It is considered that these changes increase plant tolerance to the action of stressors; the effect can be related to stimulation of damages of specific molecular structures. In this review, we hypothesize that programmed cell death (PCD) in plant cells can be interconnected with ESs. There are the following points supporting this hypothesis. (i) Propagation of ESs can be related to ROS waves; these waves are a probable mechanism of PCD initiation. (ii) ESs induce the inactivation of photosynthetic dark reactions and activation of respiration. Both responses can also produce ROS and, probably, induce PCD. (iii) ESs stimulate the synthesis of stress phytohormones (e.g., jasmonic acid, salicylic acid, and ethylene) which are known to contribute to the induction of PCD. (iv) Generation of ESs accompanies K⁺ efflux from the cytoplasm that is also a mechanism of induction of PCD. Our review argues for the possibility of PCD induction by electrical signals and shows some directions of future investigations in the field.

Stochastic Spatial Heterogeneity in Activities of H+-ATP-Ases in Electrically Connected Plant Cells Decreases Threshold for Cooling-Induced Electrical Responses

H⁺-ATP-ases, which support proton efflux through the plasma membrane, are key molecular transporters for electrogenesis in cells of higher plants. Initial activities of the transporters can influence the thresholds of generation of electrical responses induced by stressors and modify other parameters of these responses. Previously, it was theoretically shown that the stochastic heterogeneity of individual cell thresholds for electrical responses in a system of electrically connected neuronal cells can decrease the total threshold of the system (“diversity-induced resonance”, DIR). In the current work, we tested a hypothesis about decreasing the thresholds of generation of cooling-induced electrical responses in a system of electrically connected plant cells with increasing stochastic spatial heterogeny in the initial activities of H⁺-ATP-ases in these cells. A two-dimensional model of the system of electrically connected excitable cells (simple imitation of plant leaf), which was based on a model previously developed in our works, was used for the present investigation. Simulation showed that increasing dispersion in the distribution of initial activities of H⁺-ATP-ases between cells decreased the thresholds of generation of cooling-induced electrical responses. In addition, the increasing weakly influenced the amplitudes of electrical responses. Additional analysis showed two different mechanisms of the revealed effect. The increasing spatial heterogeneity in activities of H⁺-ATP-ases induced a weak positive shift of the membrane potential at rest. The shift decreased the threshold of electrical response generation. However, the decreased threshold induced by increasing the H⁺-ATP-ase activity heterogeneity was also observed after the elimination of the positive shift. The result showed that the “DIR-like” mechanism also participated in the revealed effect. Finally, we showed that the standard deviation of the membrane potentials before the induction of action potentials could be used for the estimation of thresholds of cooling-induced plant electrical responses. Thus, spatial heterogeneity in the initial activities of H⁺-ATP-ases can be a new regulatory mechanism influencing the generation of electrical responses in plants under actions of stressors.

Fruit Herbivory Alters Plant Electrome: Evidence for Fruit-Shoot Long-Distance Electrical Signaling in Tomato Plants

The electrical activity of tomato plants subjected to fruit herbivory was investigated. The study aimed to test the hypothesis that tomato fruits transmit long-distance electrical signals to the shoot when subjected to herbivory. For such, time series classification by machine learning techniques and analyses related to the oxidative response were employed. Tomato plants (cv. “Micro-Tom”) were placed into a Faraday's cage and an electrode pair was inserted in the fruit's peduncle. Helicoverpa armigera caterpillars were placed on the fruit (either green and ripe) for 24 h. The time series were recorded before and after the fruit's exposure of the caterpillars. The plant material for chemical analyses was collected 24 and 48 h after the end of the acquisition of electrophysiological data. The time series were analyzed by the following techniques: Fast Fourier Transform (FFT), Wavelet Transform, Power Spectral Density (PSD), and Approximate Entropy. The following features from FFT, PSD, and Wavelet Transform were used for PCA (Principal Component Analysis): average, maximum and minimum value, variance, skewness, and kurtosis. Additionally, these features were used in Machine Learning (ML) analyses for looking for classifiable patterns between tomato plants before and after fruit herbivory. Also, we compared the electrome before and after herbivory in the green and ripe fruits. To evaluate an oxidative response in different organs, hydrogen peroxide, superoxide anion, catalase, ascorbate peroxidase, guaiacol peroxidase, and superoxide dismutase activity were evaluated in fruit and leaves. The results show with 90% of accuracy that the electrome registered in the fruit's peduncle before herbivory is different from the electrome during predation on the fruits. Interestingly, there was also a sharp difference in the electrome of the green and ripe fruits' peduncles before, but not during, the herbivory, which demonstrates that the signals generated by the herbivory stand over the others. Biochemical analysis showed that herbivory in the fruit triggered an oxidative response in other parts of the plant. Here, we demonstrate that the fruit perceives biotic stimuli and transmits electrical signals to the shoot of tomato plants. This study raises new possibilities for studies involving electrical signals in signaling and systemic response, as well as for the applicability of ML to classify electrophysiological data and its use in early diagnosis.

Influence of Local Burning on Difference Reflectance Indices Based on 400-700 nm Wavelengths in Leaves of Pea Seedlings

Local damage (e.g., burning) induces a variation potential (VP), which is an important electrical signal in higher plants. A VP propagates into undamaged parts of the plant and influences numerous physiological processes, including photosynthesis. Rapidly increasing plant tolerance to stressors is likely to be a result of the physiological changes. Thus, developing methods of revealing VP-induced physiological changes can be used for the remote sensing of plant systemic responses to local damage. Previously, we showed that burning-induced VP influenced a photochemical reflectance index in pea leaves, but the influence of the electrical signals on other reflectance indices was not investigated. In this study, we performed a complex analysis of the influence of VP induction by local burning on difference reflectance indices based on 400–700 nm wavelengths in leaves of pea seedlings. Heat maps of the significance of local burning-induced changes in the reflectance indices and their correlations with photosynthetic parameters were constructed. Large spectral regions with significant changes in these indices after VP induction were revealed. Most changes were strongly correlated to photosynthetic parameters. Some indices, which can be potentially effective for revealing local burning-induced photosynthetic changes, are separately shown. Our results show that difference reflectance indices based on 400–700 nm wavelengths can potentially be used for the remote sensing of plant systemic responses induced by local damages and subsequent propagation of VPs.

Classification of Plant Electrophysiology Signals for Detection of Spider Mites Infestation in Tomatoes

Herbivorous arthropods, such as spider mites, are one of the major causes of annual crop losses. They are usually hard to spot before a severe infestation takes place. When feeding, these insects cause external perturbation that triggers changes in the underlying physiological process of a plant, which are expressed by a generation of distinct variations of electrical potential. Therefore, plant electrophysiology data portray information of the plant state. Analyses involving machine learning techniques applied to plant electrical response triggered by spider mite infestation have not been previously reported. This study investigates plant electrophysiological signals recorded from 12 commercial tomatoes plants contaminated with spider mites and proposes a workflow based on Gradient Boosted Tree algorithm for an automated differentiation of the plant’s normal state from the stressed state caused by infestation. The classification model built using the signal samples recorded during daylight and employing a reduced feature subset performs with an accuracy of 80% in identifying the plant’s stressed state. Furthermore, the Hjorth complexity encloses the most relevant information for discrimination of the plant status. The obtained findings open novel access towards automated detection of insect infestation in greenhouse crops and, consequently, more optimal prevention and treatment approaches.

Detection of Different Hosts From a Distance Alters the Behaviour and Bioelectrical Activity of Cuscuta racemosa

In our study, we investigated some physiological and ecological aspects of the life of Cuscuta racemosa Mart. (Convolvulaceae) plants with the hypothesis that they recognise different hosts at a distance from them, and they change their survival strategy depending on what they detect. We also hypothesised that, as an attempt of prolonging their survival through photosynthesis, the synthesis of chlorophylls (a phenomenon not completely explained in these parasitic plants) would be increased if the plants don't detect a host. We quantified the pigments related to photosynthesis in different treatments and employed techniques such as electrophysiological time series recording, analyses of the complexity of the obtained signals, and machine learning classification to test our hypotheses. The results demonstrate that the absence of a host increases the amounts of chlorophyll a, chlorophyll b, and β-carotene in these plants, and the content varied depending on the host presented. Besides, the electrical signalling of dodders changes according to the species of host perceived in patterns detectable by machine learning techniques, suggesting that they recognise from a distance different host species. Our results indicate that electrical signalling might underpin important processes such as foraging in plants. Finally, we found evidence for a likely process of attention in the dodders toward the host plants. This is probably to be the first empirical evidence for attention in plants and has important implications on plant cognition studies.

Exogenous Abscisic Acid Can Influence Photosynthetic Processes in Peas through a Decrease in Activity of H+-ATP-ase in the Plasma Membrane

Simple Summary

Numerous stressors (drought, low and high temperatures, mechanical damages, etc.) act on plants under environmental conditions, suppressing their physiological processes (in particular, photosynthesis). Abscisic acid (ABA) is an important hormone, which participates in increasing plant tolerance to the action of stressors; as a result, treatment by exogenous ABA is a perspective way of regulating the tolerance in agriculture. We investigated the influence of ABA spraying on photosynthetic processes, as well as on their heat tolerance and their regulation by electrical signals propagating after local burning and modifying photosynthesis. It was shown that ABA spraying decreased photosynthetic activity and increased photosynthetic heat tolerance; additionally, the ABA treatment weakened the influence of electrical signals on photosynthesis. We revealed that these responses could be caused by a decrease in activity of H⁺-ATP-ase, which is an important ion transporter in plant cell plasma membrane that supports efflux of H⁺ from cytoplasm. As a whole, our results show the potential influence of the ABA treatment on photosynthetic processes, which is related to a decrease in activity of H⁺-ATP-ase. The result can be potentially useful for development of new methods of management of plant tolerance in agriculture.

Abstract

Abscisic acid (ABA) is an important hormone in plants that participates in their acclimation to the action of stressors. Treatment by exogenous ABA and its synthetic analogs are a potential way of controlling the tolerance of agricultural plants; however, the mechanisms of influence of the ABA treatment on photosynthetic processes require further investigations. The aim of our work was to investigate the participation of inactivation of the plasma membrane H⁺-ATP-ase on the influence of ABA treatment on photosynthetic processes and their regulation by electrical signals in peas. The ABA treatment of seedlings was performed by spraying them with aqueous solutions (10⁻⁵ M). The combination of a Dual-PAM-100 PAM fluorometer and GFS-3000 infrared gas analyzer was used for photosynthetic measurements; the patch clamp system on the basis of a SliceScope Pro 2000 microscope was used for measurements of electrical activity. It was shown that the ABA treatment stimulated the cyclic electron flow around photosystem I and decreased the photosynthetic CO₂ assimilation, the amplitude of burning-induced electrical signals (variation potentials), and the magnitude of photosynthetic responses relating to these signals; in contrast, treatment with exogenous ABA increased the heat tolerance of photosynthesis. An investigation of the influence of ABA treatment on the metabolic component of the resting potential showed that this treatment decreased the activity of the H⁺-ATP-ase in the plasma membrane. Inhibitor analysis using sodium orthovanadate demonstrated that this decrease may be a mechanism of the ABA treatment-induced changes in photosynthetic processes, their heat tolerance, and regulation by electrical signals.

Extracellular ionic fluxes suggest the basis for cellular life at the 1/f ridge of extended criticality

The criticality hypothesis states that a system may be poised in a critical state at the boundary between different types of dynamics. Previous studies have suggested that criticality has been evolutionarily selected, and examples have been found in cortical cell cultures and in the human nervous system. However, no one has yet reported a single- or multi-cell ensemble that was investigated ex vivo and found to be in the critical state. Here, the precise 1/f noise was found for pollen tube cells of optimum growth and for the physiological ("healthy") state of blood cells. We show that the multi-scale processes that arise from the so-called critical phenomena can be a fundamental property of a living cell. Our results reveal that cell life is conducted at the border between order and disorder, and that the dynamics themselves drive a system towards a critical state. Moreover, a temperature-driven re-entrant state transition, manifest in the form of a Lorentz resonance, was found in the fluctuation amplitude of the extracellular ionic fluxes for the ensemble of elongating pollen tubes of Nicotiana tabacum L. or Hyacintus orientalis L. Since this system is fine-tuned for rapid expansion to reach the ovule at a critical temperature which results in fertilisation, the core nature of criticality (long-range coherence) offers an explanation for its potential in cell growth. We suggest that the autonomous organisation of expansive growth is accomplished by self-organised criticality, which is an orchestrated instability that occurs in an evolving cell.

Burning-induced electrical signals influence broadband reflectance indices and water index in pea leaves

Electrical signals (ESs) can be induced by local action of stressors in plants; they influence numerous physiological processes (photosynthesis, transpiration, respiration, genes expression, synthesis of phytohormones, etc.) and, thereby, induce a systemic adaptation response. Development of optical methods of a remote sensing of this response can be important for agricultural and ecological monitoring. Preliminarily, we showed (Sukhova et al., Plant Sign Behav 2019; 14:e1610301) that burning-induced ESs induced changes in leaf reflectance at broad spectral bands (400-500, 500-600, 600-700, and 700-800 nm). The aims of the present work were (i) investigation of ESs influence on difference reflectance indices (RIs) calculated on the basis of these broad spectral bands and (ii) analysis of connection of the indices with water content in plants. Pea seedlings were investigated. ESs were induced by burning of the first mature leaf; ESs had high amplitudes in the second leaf and had low amplitudes in the fourth leaf. It was shown that ESs induced significant changes in RIs, which were calculated on basis of intensities of the reflected light at (i) 400-500 and 600-700 nm, (ii) 500-600 and 700-800 nm, and (iii) 600-700 and 700-800 nm. The effect was strong in the second leaf and weak in the fourth leaf; that is, the response was dependent on the magnitude of ESs. ESs-induced changes in RI were strongly connected with ESs-induced decrease of leaf water content which was estimated on basis of decrease of water index. Thus, broadband RIs can be used for revealing the ESs-induced systemic stress response in plants.

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.

Plants as electromic plastic interfaces: A mesological approach

In this manuscript, we propose that plants are eco-plastic and electromic interfaces that can drive emergent intelligent behaviours from synchronized electrical networks. Behind the semantic and anthropocentric problems related by many authors to the extensive use of the terms cognition, intelligence or even 'consciousness' for plants, we suggest a more pragmatic perspective, considering the vegetal world to be a complex biosystemic entity that is able to co-build the world or a form of the world or of significant reality via a set of reciprocal, emerging and confluent interactions. Speaking of adaptive sensory modalities involving perceptual binding or a global state of receptivity nonlinearly leading to cognitive functions, learning capabilities and intelligent behaviours of plants seem to be the more realistic and operational model to describe how plants perceive and treat environmental data. In this study, we strongly suggest that the electrome, which mainly involves constant spontaneous emission of low voltage potentials, is an early marker and a unifying factor of whole plant reactivity in a constantly changing environment and is therefore the key to understanding the cognitive nature of plants. This dynamic coupling enables plants to be knowledge-accumulating systems that are used by evolution to progress and survive, while mesological plasticity is a unique means for plants to interact as subjects with their milieu (umwelt) or natural habitat and to co-signify a possible world.

Are plants cognitive? A reply to Adams

According to F. Adams [this journal, vol. 68, 2018] cognition cannot be realized in plants or bacteria. In his view, plants and bacteria respond to the here-and-now in a hardwired, inflexible manner, and are therefore incapable of cognitive activity. This article takes issue with the pursuit of plant cognition from the perspective of an empirically informed philosophy of plant neurobiology. As we argue, empirical evidence shows, contra Adams, that plant behavior is in many ways analogous to animal behavior. This renders plants suitable to be described as cognitive agents in a non-metaphorical way. Sections two to four review the arguments offered by Adams in light of scientific evidence on plant adaptive behavior, decision-making, anticipation, as well as learning and memory. Section five introduces the 'phyto-nervous' system of plants. To conclude, section six resituates the quest for plant cognition into a broader approach in cognitive science, as represented by enactive and ecological schools of thought. Overall, we aim to motivate the idea that plants may be considered genuine cognitive agents. Our hope is to help propel public awareness and discussion of plant intelligence once appropriately stripped of anthropocentric preconceptions of the sort that Adams' position appears to exemplify.

Long-distance electrical signals as a link between the local action of stressors and the systemic physiological responses in higher plants

Our review is devoted to the analysis of the role of long-distance electrical signals in the development of the fast systemic physiological responses in higher plants. The characteristics and mechanisms of basic electrical signals (variation potential, action potential and system potential) are analyzed, and a potential schema of the generation and propagation of the system potential is proposed. The review summarizes the physiological changes induced by the variation potential, action potential and system potential in higher plants, including changes in gene expressions, the production of phytohormones, photosynthesis, phloem mass-flow, respiration, ATP content, transpiration and plant growth. Potential mechanisms of the changes are analyzed. Finally, a hypothetical schema, which describes a hierarchy of the variation potential, action potential and system potential, in the development of the fast systemic non-specific adaptation of plants to stressors, is proposed.

Single measurement detection of individual cell ionic oscillations using an n-type semiconductor - electrolyte interface

Pollen tubes are used as models in studies on the type of tip-growth in plants. They are an example of polarised and rapid growth because pollen tubes are able to quickly invade the flower pistil in order to accomplish fertilisation. How different ionic fluxes are perceived, processed or generated in the pollen tube is still not satisfactorily understood. In order to measure the H⁺, K⁺, Ca²⁺ and Cl⁻ fluxes of a single pollen tube, we developed an Electrical Lab on a Photovoltaic-Chip (ELoPvC) on which the evolving cell was immersed in an electrolyte of a germination medium. Pollen from Hyacinthus orientalis L. was investigated ex vivo. We observed that the growing cell changed the (redox) potential in the medium in a periodic manner. This subtle measurement was feasible due to the effects that were taking place at the semiconductor-liquid interface. The experiment confirmed the existence of the ionic oscillations that accompany the periodic extension of pollen tubes, thereby providing – in a single run – the complete discrete frequency spectrum and phase relationships of the ion gradients and fluxes, while all of the metabolic and enzymatic functions of the cell life cycle were preserved. Furthermore, the global 1/f^α characteristic of the power spectral density, which corresponds to the membrane channel noise, was found.