ArticlePlant physiology2017
PaCeQuant: A Tool for High-Throughput Quantification of Pavement Cell Shape Characteristics.
Article in Plant physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed, 76 citations in OpenAlex.
- A drought stress-induced MYB transcription factor regulates pavement cell shape in leaves of European aspen (Populus tremula).The New phytologist · 2026Article
- Stomatalia: a deep learning-based platform for quantitative stomata and pavement cell analysis.Plant methods · 2026Article
- Technological advances in imaging and modelling of leaf structural traits: a review of heat stress in wheat.Journal of experimental botany · 2026Review
- A user-friendly machine-learning program to quantify stomatal features from fluorescence images.bioRxiv : the preprint server for biology · 2025Article
- Integrating Artificial Intelligence and Biotechnology to Enhance Cold Stress Resilience in Legumes.Plants (Basel, Switzerland) · 2025Review
- PIN2-mediated self-organizing transient auxin flow contributes to auxin maxima at the tip of Arabidopsis cotyledons.Nature communications · 2025Article
- Quantification of bacterial shape using moment invariants enables distinguishing populations during cellular plasmolysis.MethodsX · 2024Article
- MYB52 negatively regulates ADF9-meditated actin filament bundling in Arabidopsis pavement cell morphogenesis.Journal of integrative plant biology · 2024Article
- PIN2-mediated self-organizing transient auxin flow contributes to auxin maxima at the tip of Arabidopsis cotyledons.bioRxiv : the preprint server for biology · 2024Article
- Hierarchical global and local auxin signals coordinate cellular interdigitation inbioRxiv : the preprint server for biology · 2024Article
- Plant microphenotype: from innovative imaging to computational analysis.Plant biotechnology journal · 2024Review
- Analysis of stomatal characteristics of maize hybrids and their parental inbred lines during critical reproductive periods.Frontiers in plant science · 2024Article
- Article
- Microtubule-associated protein SlMAP70 interacts with IQ67-domain protein SlIQD21a to regulate fruit shape in tomato.The Plant cell · 2023Article
- Machine learning and feature analysis of the cortical microtubule organization of Arabidopsis cotyledon pavement cells.Protoplasma · 2023Article
- Anisotropic cell growth at the leaf base promotes age-related changes in leaf shape in Arabidopsis thaliana.The Plant cell · 2023Article
- RSV-induced expanded ciliated cells contribute to bronchial wall thickening.Virus research · 2023Article
- Segmentation, tracking, and sub-cellular feature extraction in 3D time-lapse images.Scientific reports · 2023Article
- No cell is an island: characterising the leaf epidermis using epidermalmorph, a new R package.The New phytologist · 2023Article
- Mechano-chemical regulation of complex cell shape formation: Epidermal pavement cells-A case study.Quantitative plant biology · 2023Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pavement cells (PCs) are the most frequently occurring cell type in the leaf epidermis and play important roles in leaf growth and function. In many plant species, PCs form highly complex jigsaw-puzzle-shaped cells with interlocking lobes. Understanding of their development is of high interest for plant science research because of their importance for leaf growth and hence for plant fitness and crop yield. Studies of PC development, however, are limited, because robust methods are lacking that enable automatic segmentation and quantification of PC shape parameters suitable to reflect their cellular complexity. Here, we present our new ImageJ-based tool, PaCeQuant, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based, and PC-specific object descriptors. In addition, we included a method for classification and analysis of lobes at two-cell junctions and three-cell junctions, respectively. We provide an R script for graphical visualization and statistical analysis. We validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes. PaCeQuant thus provides a platform for robust, efficient, and reproducible quantitative analysis of PC shape characteristics that can easily be applied to study PC development in large data sets.
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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 OpenQuestion graph.