This PhD thesis aims to advance the understanding of root cognition through the development of an innovative system for the three-dimensional (3D) kinematic analysis of root movements, and through the observation of these movements in the context of plant social growing. One of the main scopes of the project was to implement a technological platform for root imaging that could enable to nest the study of root movement in the framework of plant cognition. The system has been tested on maize plants (first experiment) and it demonstrated a consistent technical performance, with no instances of data loss or integration failure. It resulted to be reliable across operators and accurate when comparing the computed parameters with manual measurements. The system developed has then been used in experiments investigating root responses to social growing. In the second experiment, it has been investigated whether root kinematics and its modulation along time is influenced by the presence of a neighbouring plant sharing the same substrate. The analysis was carried on using a machine-learning based approach to evaluate whether the features of root movement extracted could be used to distinguish between individual and social growing on a multivariate basis. Collected kinematic features showed to be modulated depending on the presence of a neighbour. The features importance analysis shows that the trajectory of the primary root movement of a plant growing with a neighbour exhibits more and faster nutations (oscillations), a more complex curvature and a faster relative growth rate. These results can be interpreted as a behavioural response that aims at increasing survival chances in a competing environment where another plant has access to the same resources. In the third experiment I investigated whether there is evidence of conspecific and heterospecific recognition in the primary root movements of maize and pea plants during the first days of growth. Primary root movements have been classified among 3 possible behaviours (aggregative, avoidant and neutral) using a geometrical approach. When growing with conspecifics, primary root movements reported a higher incidence of aggregative behaviour (as growth toward the root of the neighbour). The last experiment investigates the pre-motor intentionality of root movements addressing the concept of “intentionality” associated with actions as an expression of cognitive abilities. The movements of the root apex of the study plants reported geometrical precision in the detection of the neighbour and seem to put in place a goal-oriented behaviour. This work still leaves many open questions related to the physiological mechanisms underlying the studied phenomena. However, this research not only contributes with new experimental data to the emerging field of plant cognition but also brings up a methodological advancement that can support future studies.

EXPLORING KINEMATIC FEATURES OF ROOTS MOVEMENT: A PERSPECTIVE FOR THE STUDY OF PLANT COGNITION

SIMONETTI, VALENTINA
2025

Abstract

This PhD thesis aims to advance the understanding of root cognition through the development of an innovative system for the three-dimensional (3D) kinematic analysis of root movements, and through the observation of these movements in the context of plant social growing. One of the main scopes of the project was to implement a technological platform for root imaging that could enable to nest the study of root movement in the framework of plant cognition. The system has been tested on maize plants (first experiment) and it demonstrated a consistent technical performance, with no instances of data loss or integration failure. It resulted to be reliable across operators and accurate when comparing the computed parameters with manual measurements. The system developed has then been used in experiments investigating root responses to social growing. In the second experiment, it has been investigated whether root kinematics and its modulation along time is influenced by the presence of a neighbouring plant sharing the same substrate. The analysis was carried on using a machine-learning based approach to evaluate whether the features of root movement extracted could be used to distinguish between individual and social growing on a multivariate basis. Collected kinematic features showed to be modulated depending on the presence of a neighbour. The features importance analysis shows that the trajectory of the primary root movement of a plant growing with a neighbour exhibits more and faster nutations (oscillations), a more complex curvature and a faster relative growth rate. These results can be interpreted as a behavioural response that aims at increasing survival chances in a competing environment where another plant has access to the same resources. In the third experiment I investigated whether there is evidence of conspecific and heterospecific recognition in the primary root movements of maize and pea plants during the first days of growth. Primary root movements have been classified among 3 possible behaviours (aggregative, avoidant and neutral) using a geometrical approach. When growing with conspecifics, primary root movements reported a higher incidence of aggregative behaviour (as growth toward the root of the neighbour). The last experiment investigates the pre-motor intentionality of root movements addressing the concept of “intentionality” associated with actions as an expression of cognitive abilities. The movements of the root apex of the study plants reported geometrical precision in the detection of the neighbour and seem to put in place a goal-oriented behaviour. This work still leaves many open questions related to the physiological mechanisms underlying the studied phenomena. However, this research not only contributes with new experimental data to the emerging field of plant cognition but also brings up a methodological advancement that can support future studies.
6-mar-2025
Inglese
CASTIELLO, UMBERTO
Università degli studi di Padova
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/212881
Il codice NBN di questa tesi è URN:NBN:IT:UNIPD-212881