Stomata morphology measurement with interactive machine learning: accuracy, speed, and biological relevance?

Stomata morphology measurement with interactive machine learning: accuracy, speed, and biological relevance?

Abstract Stomatal morphology plays a critical role in regulating plant gas exchange influencing water use efficiency and ecological adaptability. While traditional methods for analyzing stomatal traits rely on labor-intensive manual measurements, machine learning (ML) tools offer a promising alterna...

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Bibliographic Details
Main Authors: Tomke S. Wacker, Abraham G. Smith, Signe M. Jensen, Theresa Pflüger, Viktor G. Hertz, Eva Rosenqvist, Fulai Liu, Dorte B. Dresbøll
Format: Article
Language:English
Published: BMC 2025-07-01
Series:Plant Methods
Subjects:
Stomatal size
Stomatal density
RootPainter
Model training
Model validation
Statistical power
Online Access:https://doi.org/10.1186/s13007-025-01416-2
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https://doi.org/10.1186/s13007-025-01416-2

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