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Updated: Jan 9, 2026

Author Spotlight: Advancing Stomatal Research with Automated Aperture Measurement

Author Spotlight: Advancing Stomatal Research with Automated Aperture Measurement

Published on: February 9, 2024

A user-friendly machine-learning program to quantify stomatal features from fluorescence images.

Gabriel J Angres¹, Alexander Gillert², Andrew Muroyama¹

¹Department of Cell and Developmental Biology, University of California San Diego, La Jolla, CA, 92093, USA.

Biorxiv : the Preprint Server for Biology

|December 3, 2025

Summary

Researchers developed QuickSpotter, a tool for semi-automated stomatal annotation, to speed up the analysis of plant leaf development. This innovation aids in understanding how stomatal morphology impacts photosynthesis and plant health.

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Area of Science:

Plant Biology
Computational Biology
Genetics

Background:

Stomata are crucial plant pores for photosynthesis and gas exchange.
Stomatal morphology influences photosynthetic efficiency but is difficult to analyze manually in large datasets.

Purpose of the Study:

To develop a semi-automated tool (QuickSpotter) for efficient stomatal annotation from fluorescence images.
To enable high-throughput analysis of stomatal development and morphology.

Main Methods:

Developed QuickSpotter for semi-automated stomatal annotation.
Introduced StomEdit for rapid proofreading of annotations.
Utilized PairCaller to identify stomatal clusters.

Main Results:

QuickSpotter accurately annotates mature stomata across developmental stages.
The tool quantified stomatal morphology evolution during cotyledon development.
Subtle differences in stomatal development under pharmacological treatments were identified.

Conclusions:

The QuickSpotter suite facilitates large-scale, quantitative analyses of stomatal development.
Enables high-throughput phenotyping of leaf traits under various conditions.
Advances understanding of genetic and environmental factors influencing stomatal morphology.