ArticlePlant reproduction2020
Quantitative methods in microscopy to assess pollen viability in different plant taxa.
Article in Plant reproduction, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 30 citations in OpenAlex.
- Combined effects of inflorescence developmental age and environmental conditions during microgametogenesis on pollen viability, germination and size in Musa acuminata ssp.Annals of botany · 2026Article
- Study on evaluation of effects of electromagnetic radiation on pollen viability in some commonly occurring plant species following different staining methods.Protoplasma · 2026Article
- Article
- An improved fluorescein diacetate-propidium iodide staining system for assessing microspore and pollen viability at different developmental stages.Plant biotechnology journal · 2025Article
- Screening methods for thermotolerance in pollen.Annals of botany · 2025Review
- Optimizing Visualization of Pollen Tubes in Wheat Pistils.Plants (Basel, Switzerland) · 2024Article
- Pollen viability, longevity, and function in angiosperms: key drivers and prospects for improvement.Plant reproduction · 2024Review
- A simple method for measuring pollen germination rate using machine learning.Plant reproduction · 2023Article
- Deep learning-based high-throughput detection of in vitro germination to assess pollen viability from microscopic images.Journal of experimental botany · 2023Article
- Effects of Drought Stress on the Morphological Structure and Flower Organ Physiological Characteristics ofPlants (Basel, Switzerland) · 2023Article
- Evaluation of methods to assess the quality of cryopreserved Solanaceae pollen.Scientific reports · 2023Article
- Deep Learning Methods for Improving Pollen Monitoring.Sensors (Basel, Switzerland) · 2021Article
- Hazelnut Pollen Phenotyping Using Label-Free Impedance Flow Cytometry.Frontiers in plant science · 2020Article
- Methodologies and Considerations in Evaluating Heat Stress Response and Thermotolerance of Pollen Grains.Physiologia plantarumReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-quality pollen is a prerequisite for plant reproductive success. Pollen viability and sterility can be routinely assessed using common stains and manual microscope examination, but with low overall statistical power. Current automated methods are primarily directed towards the analysis of pollen sterility, and high throughput solutions for both pollen viability and sterility evaluation are needed that will be consistent with emerging biotechnological strategies for crop improvement. Our goal is to refine established labelling procedures for pollen, based on the combination of fluorescein (FDA) and propidium iodide (PI), and to develop automated solutions for accurately assessing pollen grain images and classifying them for quality. We used open-source software programs (CellProfiler, CellProfiler Analyst, Fiji and R) for analysis of images collected from 10 pollen taxa labelled using FDA/PI. After correcting for image background noise, pollen grain images were examined for quality employing thresholding and segmentation. Supervised and unsupervised classification of per-object features was employed for the identification of viable, dead and sterile pollen. The combination of FDA and PI dyes was able to differentiate between viable, dead and sterile pollen in all the analysed taxa. Automated image analysis and classification significantly increased the statistical power of the pollen viability assay, identifying more than 75,000 pollen grains with high accuracy (R
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Registered trials
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.