ArticlePlant physiology2021
Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping.
Article in Plant physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.
- Greater aperture counteracts effects of reduced stomatal density on water use efficiency: a case study on sugarcane and meta-analysis.Journal of experimental botany · 2024Pooled it
- UMF-stomata: An unsupervised multi-focus fusion framework for microscopic stomatal phenotyping.Plant phenomics (Washington, D.C.) · 2026Article
- Improving multi-trait genomic prediction using synthetic traits from hyperspectral data based on co-heritability.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Genetic markers of stomatal cluster development in Begoniaceae revealed through trait analysis assisted by interactive deep-learning.Plant physiology · 2026Article
- High-resolution microCT reveals relationships between stomata and interior leaf anatomy in sorghum.Plant physiology · 2026Article
- ZmSKIP enhances drought tolerance by reducing stomatal aperture in maize.PLoS genetics · 2026Article
- Brachypodium SPEECHLESS2 Promoter Drives Expression of a Synthetic EPF to Reduce Stomatal Density in Sugarcane Without Pleiotropic Effects.Plant biotechnology journal · 2026Article
- Stomata in-sight: Integrating live confocal microscopy with leaf gas exchange and environmental control.Plant physiology · 2025Article
- Article
- Understanding plant phenotypes in crop breeding through explainable AI.Plant biotechnology journal · 2025Review
- WSF: A Transformer-Based Framework for Microphenotyping and Genetic Analyzing of Wheat Stomatal Traits.Plants (Basel, Switzerland) · 2025Article
- StomaYOLO: A Lightweight Maize Phenotypic Stomatal Cell Detector Based on Multi-Task Training.Plants (Basel, Switzerland) · 2025Article
- Needs and opportunities to future-proof crops and the use of crop systems to mitigate atmospheric change.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- The combined effect of decreased stomatal density and aperture increases water use efficiency in maize.Scientific reports · 2025Article
- Spatial patterning of chloroplasts and stomata in developing cacao leaves.Communications biology · 2025Article
- Breaking the barrier of human-annotated training data for machine learning-aided plant research using aerial imagery.Plant physiology · 2025Article
- Genetic mapping for agronomic, nutritional, and leaf vein traits in the indigenous cropNPJ sustainable agriculture · 2025Article
- Reducing stomatal density by expression of a synthetic epidermal patterning factor increases leaf intrinsic water use efficiency and reduces plant water use in a C4 crop.Journal of experimental botany · 2024Article
- Application of deep learning for the analysis of stomata: a review of current methods and future directions.Journal of experimental botany · 2024Review
- Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning.Journal of experimental botany · 2024Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stomata are adjustable pores on leaf surfaces that regulate the tradeoff of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping epidermal cell traits have limited discoveries about the genetic basis of stomatal patterning. A high-throughput epidermal cell phenotyping pipeline is presented here and used for quantitative trait loci (QTL) mapping in field-grown maize (Zea mays). The locations and sizes of stomatal complexes and pavement cells on images acquired by an optical topometer from mature leaves were automatically determined. Computer estimated stomatal complex density (SCD; R2 = 0.97) and stomatal complex area (SCA; R2 = 0.71) were strongly correlated with human measurements. Leaf gas exchange traits were genetically correlated with the dimensions and proportions of stomatal complexes (rg = 0.39-0.71) but did not correlate with SCD. Heritability of epidermal traits was moderate to high (h2 = 0.42-0.82) across two field seasons. Thirty-six QTL were consistently identified for a given trait in both years. Twenty-four clusters of overlapping QTL for multiple traits were identified, with univariate versus multivariate single marker analysis providing evidence consistent with pleiotropy in multiple cases. Putative orthologs of genes known to regulate stomatal patterning in Arabidopsis (Arabidopsis thaliana) were located within some, but not all, of these regions. This study demonstrates how discovery of the genetic basis for stomatal patterning can be accelerated in maize, a C4 model species where these processes are poorly understood.
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