The Development of a Stereo Vision System to Study the Nutation Movement of Climbing Plants.

Climbing plants, such as common beans (Phaseolus vulgaris L.), exhibit complex motion patterns that have long captivated researchers. In this study, we introduce a stereo vision machine system for the in-depth analysis of the movement of climbing plants, using image processing and computer vision. Our approach involves two synchronized cameras, one lateral to the plant and the other overhead, enabling the simultaneous 2D position tracking of the plant tip. These data are then leveraged to reconstruct the 3D position of the tip. Furthermore, we investigate the impact of external factors, particularly the presence of support structures, on plant movement dynamics. The proposed method is able to extract the position of the tip in 86-98% of cases, achieving an average reprojection error below 4 px, which means an approximate error in the 3D localization of about 0.5 cm. Our method makes it possible to analyze how the plant nutation responds to its environment, offering insights into the interplay between climbing plants and their surroundings.

A case study of learning in plants: Lessons learned from pea plants.

To facilitate the study of learning in plants, we share our experiences of trying to replicate the pea plant experiment of Gagliano et al. In the course of our efforts, we identified 11 issues that must be addressed when attempting to replicate these experiments. The issues range from germination and transplantation of seedlings to experimental design and apparatus issues. We propose a number of solutions to overcome these hurdles.

Decision Making in Plants: A Rooted Perspective.

This article discusses the possibility of plant decision making. We contend that recent work on bacteria provides a pertinent perspective for thinking about whether plants make choices. Specifically, the analogy between certain patterns of plant behaviour and apparent decision making in bacteria provides principled grounds for attributing decision making to the former. Though decision making is our focus, the discussion has implications for the wider issue of whether and why plants (and non-neural organisms more generally) are appropriate targets for cognitive abilities. Moreover, decision making is especially relevant to the issue of plant intelligence as it is commonly taken to be characteristic of cognition.

Identification of intelligence-related proteins through a robust two-layer predictor.

In this study, we advance a robust methodology for identifying specific intelligence-related proteins across phyla. Our approach exploits a support vector machine-based classifier capable of predicting intelligence-related proteins based on a pool of meaningful protein features. For the sake of illustration of our proposed general method, we develop a novel computational two-layer predictor, Intell_Pred, to predict query sequences (proteins or transcripts) as intelligence-related or non-intelligence-related proteins or transcripts, subsequently classifying the former sequences into learning and memory-related classes. Based on a five-fold cross-validation and independent blind test, Intell_Pred obtained an average accuracy of 87.48 and 88.89, respectively. Our findings revealed that a score >0.75 (during prediction by Intell_Pred) is a well-grounded choice for predicting intelligence-related candidate proteins in most organisms across biological kingdoms. In particular, we assessed seismonastic movements and associate learning in plants and evaluated the proteins involved using Intell_Pred. Proteins related to seismonastic movement and associate learning showed high percentages of similarities with intelligence-related proteins. Our findings lead us to believe that Intell_Pred can help identify the intelligence-related proteins and their classes using a given protein/transcript sequence.

Understanding interdisciplinary perspectives of plant intelligence: Is it a matter of science, language, or subjectivity?

BACKGROUND: Evidence suggests that plants can behave intelligently by exhibiting the ability to learn, make associations between environmental cues, engage in complex decisions about resource acquisition, memorize, and adapt in flexible ways. However, plant intelligence is a disputed concept in the scientific community. Reasons for lack of consensus can be traced back to the history of Western philosophy, interpretation of terminology, and due to plants lacking neurons and a central nervous system. Plant intelligence thus constitutes a novel paradigm in the plant sciences. Therefore, the perspectives of scientists in plant-related disciplines need to be investigated in order to gain insight into the current state and future development of this concept. METHODS: This study analyzed opinions of plant intelligence held by scientists from different plant-related disciplines, including ethnobiology and other biological sciences, through an online questionnaire. RESULTS: Our findings show that respondents' personal belief systems and the frequency of taking into account other types of knowledge, such as traditional knowledge, in their own field(s) of study, were associated with their opinions of plant intelligence. Meanwhile, respondents' professional expertise, background (discipline), or familiarity with evidence provided on plant intelligence did not affect their opinions. CONCLUSIONS: This study emphasizes the influential role of scientists' own subjective beliefs. In response, two approaches could facilitate transdisciplinary understanding among scientists: (1) effective communication designed to foster change in agreement based on presented information; and (2) holding space for an interdisciplinary dialogue where scientists can express their own subjectivities and open new opportunities for collaboration.

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.

Our sisters the plants? notes from phylogenetics and botany on plant kinship blindness.

Before the upheaval brought about by phylogenetic classification, classical taxonomy separated living beings into two distinct kingdoms, animals and plants. Rooted in 'naturalist' cosmology, Western science has built its theoretical apparatus on this dichotomy mostly based on ancient Aristotelian ideas. Nowadays, despite the adoption of the Darwinian paradigm that unifies living organisms as a kinship, the concept of the "scale of beings" continues to structure our analysis and understanding of living species. Our aim is to combine developments in phylogeny, recent advances in biology, and renewed interest in plant agency to craft an interdisciplinary stance on the living realm. The lines at the origin of plant or animal have a common evolutionary history dating back to about 3.9 Ga, separating only 1.6 Ga ago. From a phylogenetic perspective of living species history, plants and animals belong to sister groups. With recent data related to the field of Plant Neurobiology, our aim is to discuss some socio-cultural obstacles, mainly in Western naturalist epistemology, that have prevented the integration of living organisms as relatives, while suggesting a few avenues inspired by practices principally from other ontologies that could help overcome these obstacles and build bridges between different ways of connecting to life.

Integrated information as a possible basis for plant consciousness.

It is commonly assumed that plants do not possess consciousness. Since the criterion for this assumption is usually human consciousness this assumption represents a top down attitude. It is obvious that plants are not animals and using animal criteria of consciousness will lead to its rejection in plants. However using a bottom up evolutionary approach and a leading theory of consciousness, Integrated Information Theory, we report that we find evidence that indicates that plant meristems act in a conscious fashion although probably at the level of minimal consciousness. Since many plants contain multiple meristems these observations highlight a very different evolutionary approach to consciousness in biological organisms.

Enacting Plant-Inspired Robotics.

Plants offer a source of bioinspiration for soft robotics. Nevertheless, a gap remains in designing robots based on the fundamental principles of plant intelligence, rooted in a non-centralized, modular architecture and a highly plastic phenotype. We contend that a holistic approach to plant bioinspiration-one that draws more fully on the features of plant intelligence and behavior-evidences the value of an enactivist perspective. This is because enactivism emphasizes not only features of embodiment such as material composition and morphology, but also autonomy as an important aspect of plant intelligence and behavior. The enactivist sense of autonomy concerns the dynamics of self-producing systems (such as plants) that create a distinction between themselves and a domain of interactions that bear on the conditions of viability of the system. This contrasts with the widespread, but diluted notion of autonomy that merely indicates the independent operability of a system for an arbitrary period. Different notions of autonomy are relevant for soft roboticists, for instance, when evaluating limitations on existing growing robots ("growbots") that take bioinspiration from plants, but depend on a fixed source of energy and material provided by an external agent. More generally, plant-inspired robots serve as a case study for an enactivist approach to intelligence, while, correspondingly, enactivism calls attention to the possibility of non-zoological forms of intelligence embodied in a self-organizing, autonomous system.

The dynamics of plant nutation.

In this article we advance a cutting-edge methodology for the study of the dynamics of plant movements of nutation. Our approach, unlike customary kinematic analyses of shape, period, or amplitude, is based on three typical signatures of adaptively controlled processes and motions, as reported in the biological and behavioral dynamics literature: harmonicity, predictability, and complexity. We illustrate the application of a dynamical methodology to the bending movements of shoots of common beans (Phaseolus vulgaris L.) in two conditions: with and without a support to climb onto. The results herewith reported support the hypothesis that patterns of nutation are influenced by the presence of a support to climb in their vicinity. The methodology is in principle applicable to a whole range of plant movements.

Plant Bioinspired Ecological Robotics.

Plants are movers, but the nature of their movement differs dramatically from that of creatures that move their whole body from point A to point B. Plants grow to where they are going. Bio-inspired robotics sometimes emulates plants' growth-based movement; but growing is part of a broader system of movement guidance and control. We argue that ecological psychology's conception of "information" and "control" can simultaneously make sense of what it means for a plant to navigate its environment and provide a control scheme for the design of ecological plant-inspired robotics. In this effort, we will outline several control laws and give special consideration to the class of control laws identified by tau theory, such as time to contact.

Plants are intelligent, here's how.

HYPOTHESES: The drive to survive is a biological universal. Intelligent behaviour is usually recognized when individual organisms including plants, in the face of fiercely competitive or adverse, real-world circumstances, change their behaviour to improve their probability of survival. SCOPE: This article explains the potential relationship of intelligence to adaptability and emphasizes the need to recognize individual variation in intelligence showing it to be goal directed and thus being purposeful. Intelligent behaviour in single cells and microbes is frequently reported. Individual variation might be underpinned by a novel learning mechanism, described here in detail. The requirements for real-world circumstances are outlined, and the relationship to organic selection is indicated together with niche construction as a good example of intentional behaviour that should improve survival. Adaptability is important in crop development but the term may be complex incorporating numerous behavioural traits some of which are indicated. CONCLUSION: There is real biological benefit to regarding plants as intelligent both from the fundamental issue of understanding plant life but also from providing a direction for fundamental future research and in crop breeding.

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.

Are plants sentient?

Feelings in humans are mental states representing groups of physiological functions that usually have defined behavioural purposes. Feelings, being evolutionarily ancient, are thought to be coordinated in the brain stem of animals. One function of the brain is to prioritise between competing mental states and, thus, groups of physiological functions and in turn behaviour. Plants use groups of coordinated physiological activities to deal with defined environmental situations but currently have no known mental state to prioritise any order of response. Plants do have a nervous system based on action potentials transmitted along phloem conduits but which in addition, through anastomoses and other cross-links, forms a complex network. The emergent potential for this excitable network to form a mental state is unknown, but it might be used to distinguish between different and even contradictory signals to the individual plant and thus determine a priority of response. This plant nervous system stretches throughout the whole plant providing the potential for assessment in all parts and commensurate with its self-organising, phenotypically plastic behaviour. Plasticity may, in turn, depend heavily on the instructive capabilities of local bioelectric fields enabling both a degree of behavioural independence but influenced by the condition of the whole plant.

Predicting green: really radical (plant) predictive processing.

In this article we account for the way plants respond to salient features of their environment under the free-energy principle for biological systems. Biological self-organization amounts to the minimization of surprise over time. We posit that any self-organizing system must embody a generative model whose predictions ensure that (expected) free energy is minimized through action. Plants respond in a fast, and yet coordinated manner, to environmental contingencies. They pro-actively sample their local environment to elicit information with an adaptive value. Our main thesis is that plant behaviour takes place by way of a process (active inference) that predicts the environmental sources of sensory stimulation. This principle, we argue, endows plants with a form of perception that underwrites purposeful, anticipatory behaviour. The aim of the article is to assess the prospects of a radical predictive processing story that would follow naturally from the free-energy principle for biological systems; an approach that may ultimately bear upon our understanding of life and cognition more broadly.

"Feature Detection" vs. "Predictive Coding" Models of Plant Behavior.

In this article we consider the possibility that plants exhibit anticipatory behavior, a mark of intelligence. If plants are able to anticipate and respond accordingly to varying states of their surroundings, as opposed to merely responding online to environmental contingencies, then such capacity may be in principle testable, and subject to empirical scrutiny. Our main thesis is that adaptive behavior can only take place by way of a mechanism that predicts the environmental sources of sensory stimulation. We propose to test for anticipation in plants experimentally by contrasting two empirical hypotheses: "feature detection" and "predictive coding." We spell out what these contrasting hypotheses consist of by way of illustration from the animal literature, and consider how to transfer the rationale involved to the plant literature.