ReviewiScience2026
Plant embodied intelligence: A paradigmatic perspective.
Review in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The concept of intelligence is expanding beyond neural systems to include plants. Following this trend, we turn our focus on a key but undeveloped branch-plant embodied intelligence (PEI), where adaptive problem-solving activities emerge from dynamic interactions between distributed plant structures and their environment. Specifically, this review first outlines PEI's theoretical foundations and then proposes research avenues, including adaptive morphogenesis and growth, distributed information processing and memory, ecological communication and swarm-like behavior, and decision-making under risk and competition. Next, a comprehensive analysis of global research highlights pioneering work, spanning plant neurobiology, systems biology, and bio-inspired materials, while identifying critical gaps. Accordingly, a convergent methodology of quantitative phenotyping, molecular systems biology, ecological modeling, and plant-inspired robotics/software. Finally, we articulate how the pursuit of PEI can reciprocally advance both plant sciences and intelligent systems sciences, ultimately positioning plants as active collaborators for sustainable innovation.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.