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Updated: Mar 3, 2026

A Simple Protocol for Mapping the Plant Root System Architecture Traits

A Simple Protocol for Mapping the Plant Root System Architecture Traits

Published on: February 10, 2023

On plant roots logical gates.

Andrew Adamatzky¹, Georgios Ch Sirakoulis², Genaro J Martínez³

¹Unconventional Computing Laboratory, UWE, Bristol, UK.

|April 22, 2017

Summary

This summary is machine-generated.

This study introduces plant roots as novel asynchronous computing devices, implementing logical gates for Boolean functions. This research pioneers bio-computing by using root growth to perform calculations.

Keywords:

Logical gates Plant roots Unconventional computing

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Area of Science:

Biocomputing
Plant-based computation
Morphological computing

Background:

Boolean logic operations are fundamental to computation.
Existing computing paradigms rely on electronic components.
Novel computing substrates are sought for sustainable and integrated systems.

Purpose of the Study:

To propose theoretical constructs for implementing logical gates using plant roots.
To demonstrate the feasibility of plant roots as asynchronous computing devices.
To design a binary half-adder based on root-guided logical gates.

Main Methods:

Representing Boolean variables (True/False) by the presence/absence of plant roots.
Designing two-input, two-output logical gates based on root apex guidance (gravity and humidity).
Proposing a binary half-adder architecture utilizing these root-based gates.

Main Results:

Demonstrated theoretical models for AND/OR and NOT/AND gates using plant root morphology.
Proposed a functional design for a binary half-adder implemented with these bio-logical gates.
Established plant roots as viable components for asynchronous morphological computing.

Conclusions:

Plant roots can be theoretically engineered to perform logical operations, forming the basis of bio-computers.
Morphological computing with plant roots offers a novel, sustainable approach to asynchronous computation.
This work opens avenues for integrating biological systems with computational functions.