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bioRxiv · 10.64898/2026.08.03.742415

AI-enabled simultaneous phenotyping of leaf vein and stomatal traits uncovers independent genetic control in maize

Sechi, M.·Porcedda, R.·Pallaoro, M.·Ferguson, J. N.·Dell'Acqua, M.·Vandin, A.·Caproni, L.
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Abstract

BackgroundLeaves maintain hydraulic homeostasis during photosynthesis through the coordinated action of stomata, which regulate gas exchange and transpiration, and veins, which supply water to the leaf lamina. While functional links between stomatal and vascular traits are known in dicots, their potential genetic coordination in C4 crops remains poorly understood. We investigated the genetic architecture of these traits in maize using a Multi-parent Advanced Generation Inter-Cross (MAGIC) population and a low-cost, high-throughput phenotyping platform integrating leaf clearing, digital microscopy, artificial intelligence, and image analysis ResultsWe phenotyped 285 recombinant inbred lines and the MAGIC founder lines, generating 8,072 images from 2,026 leaf samples taken from seedlings grown in controlled conditions. A YOLOv8-based model automatically detected stomata, while a custom and efficient image-processing pipeline quantified vein traits and stomatal spatial distribution patterns along cell bundles. This enabled simultaneous characterization of stomatal density, size, and distribution together with vein density, thickness, and bundle-associated spatial patterning. Substantial phenotypic variation was observed among genotypes, with strong correlations between abaxial and adaxial traits but no significant correlations between stomatal and vein traits. QTL mapping identified 37 genomic regions associated with stomatal and vein traits, including loci containing known developmental regulators such as stomatal density and distribution1 and stomagen1, as well as novel loci controlling stomatal spatial patterns, divergence between leaf surfaces and veins traits. ConclusionsThese results support independent genetic control of stomata and veins and decoupled contribution to water-use efficiency, providing a novel genetic framework to independently optimize leaf hydraulic capacity and gas exchange in target environments.

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Sechi, M., Porcedda, R., Pallaoro, M., Ferguson, J. N., Dell'Acqua, M., Vandin, A., Caproni, L.. 2026-08-04. AI-enabled simultaneous phenotyping of leaf vein and stomatal traits uncovers independent genetic control in maize. https://doi.org/10.64898/2026.08.03.742415

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