Automated physiological recovery of avocado plants for plant-based adaptive machines. (April 2014)

• Record Type: Journal Article
• Authors: Damian, Dana D; Miyashita, Shuhei; Aoyama, Atsushi; Cadosch, Dominique; Huang, Po-Ting; Ammann, Michael; Pfeifer, Rolf
• Is Part Of: Adaptive behavior. Volume 22:Number 2(2014)
• Page Start: 109
• Page End: 122
• Publication Date: 2014-04
• Subjects: Automated physiological recovery -- plant–machine interface -- avocado plant; Animal behavior -- Periodicals; Animals -- Adaptation -- Periodicals; Adaptability (Psychology) -- Periodicals; Adaptation, Psychological -- Periodicals; Artificial intelligence -- Periodicals; 591.5
• DOI: 10.1177/1059712313511919
• Languages: English
• ISSNs: 1741-2633

Abstract

Interfacing robots with real biological systems is a potential approach to realizing truly adaptive machines, which is a long-standing engineering challenge. Although plants are widely spread and versatile, little attention has been given to creating cybernetic systems incorporating plants. Producing such systems requires two main steps: the acquisition and interpretation of biological signals, and issuing the appropriate stimulation signals for controlling the physiological response of the biological part. We investigate an automated physiological recovery of young avocado plants by realizing a closed interaction loop between the avocado plant and a water-control device. The study considers the two aforementioned steps by reading out postural cues (leaf inclination) and electrophysiological (biopotential) signals from the plant, and controlling the water resource adaptive to the drought condition of an avocado plant. Analysis of the two signals reveals time-frequency patterns of increased power and global synchronization in the narrow bands when water is available, and local synchronization in the broad bands for water shortage. The results indicate the feasibility of interface technologies between plants and machines, and provide preliminary support for achieving adaptive plant-based 'machines' based on plants' large and robust physiological spectrum and machines' control scheme diversity. We further discuss fundamental impediments hindering the use of living organisms like plants for artificial systems.