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AOBPreview originally published online on July 29, 2009
Annals of Botany 2009 104(5):1005-1010; doi:10.1093/aob/mcp186
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© The Author 2009. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

TECHNICAL ARTICLE

Counting pollen grains using readily available, free image processing and analysis software

Clayton M. Costa and Suann Yang*

Department of Biology, 208 Mueller Laboratory, The Pennsylvania State University, University Park, PA 16802, USA

* For correspondence. E-mail suy14{at}psu.edu

Received: 6 March 2009    Returned for revision: 6 May 2009    Accepted: 15 June 2009    Published electronically: 29 July 2009

Background and Aims: Although many methods exist for quantifying the number of pollen grains in a sample, there are few standard methods that are user-friendly, inexpensive and reliable. The present contribution describes a new method of counting pollen using readily available, free image processing and analysis software.

Methods: Pollen was collected from anthers of two species, Carduus acanthoides and C. nutans (Asteraceae), then illuminated on slides and digitally photographed through a stereomicroscope. Using ImageJ (NIH), these digital images were processed to remove noise and sharpen individual pollen grains, then analysed to obtain a reliable total count of the number of grains present in the image. A macro was developed to analyse multiple images together. To assess the accuracy and consistency of pollen counting by ImageJ analysis, counts were compared with those made by the human eye.

Key Results and Conclusions: Image analysis produced pollen counts in 60 s or less per image, considerably faster than counting with the human eye (5–68 min). In addition, counts produced with the ImageJ procedure were similar to those obtained by eye. Because count parameters are adjustable, this image analysis protocol may be used for many other plant species. Thus, the method provides a quick, inexpensive and reliable solution to counting pollen from digital images, not only reducing the chance of error but also substantially lowering labour requirements.

Key words: Carduus acanthoides, Carduus nutans, ImageJ, image processing, pollen grain count


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