Quantitative methods in microscopy to assess pollen viability in different plant taxa.
Quantitative methods in microscopy to assess pollen viability in different plant taxa.
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DOI：
10.1007/s00497-020-00398-6
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发表时间：
2020-12
影响因子：
3.4
通讯作者：
Siniscalco C
中科院分区：
文献类型：
--
作者：
Ascari L;Novara C;Dusio V;Oddi L;Siniscalco C
高质量的花粉是植物繁殖成功的先决条件。花粉生活力和不育性可以常规评估使用普通染色和手动显微镜检查，但总体统计功率低。目前的自动化方法主要针对花粉不育性的分析，并且需要用于花粉生活力和不育性评估的高通量解决方案，这将与用于作物改良的新兴生物技术策略一致。我们的目标是完善基于荧光素（FDA）和碘化丙啶（PI）组合的花粉标记程序，并开发自动化解决方案，以准确评估花粉粒图像并对其进行质量分类。我们使用开源软件程序（CellProfiler，CellProfiler Analyst，Fiji和R）分析从10个使用FDA/PI标记的花粉分类群收集的图像。校正图像背景噪声后，花粉图像的质量进行了检查，采用阈值和分割。每个对象的功能的监督和非监督分类，用于识别可行的，死亡的和不育的花粉。FDA和PI染料的组合能够在所有分析的分类群中区分活的、死的和不育的花粉。自动化图像分析和分类显着增加了花粉活力测定的统计能力，与经典的手动计数相比，识别了超过75，000个花粉粒，具有高准确度（R2 = 0.99）。总的来说，我们提供了一套全面的方法作为基线的花粉活力，使用荧光显微镜，它可以与手动和机械化成像系统在植物生物学的基础和应用研究相结合的自动化评估。我们还向科学界提供完整的花粉图像（FDA/PI花粉数据集），供未来研究使用。本文的在线版本（10.1007/s 00497 -020-00398-6）包含补充材料，可供授权用户使用。
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 (R2 = 0.99) when compared to classical manual counting. Overall, we provide a comprehensive set of methodologies as baseline for the automated assessment of pollen viability using fluorescence microscopy, which can be combined with manual and mechanized imaging systems in fundamental and applied research on plant biology. We also supply the complete set of pollen images (the FDA/PI pollen dataset) to the scientific community for future research. The online version of this article (10.1007/s00497-020-00398-6) contains supplementary material, which is available to authorized users.
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影响因子：
1.6
作者：
Aronne, G;Cavuoto, D;Eduardo, P
通讯作者：
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Dupl'akova, Nikoleta;Dobrev, Petre I.;Honys, David
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