Clayton M Costa1, Suann Yang. 1. Department of Biology, 208 Mueller Laboratory, Pennsylvania State University, University Park, PA 16802, USA.
Abstract
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.
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.
Authors: Y M Staedler; T Kreisberger; S Manafzadeh; M Chartier; S Handschuh; S Pamperl; S Sontag; O Paun; J Schönenberger Journal: J Exp Bot Date: 2018-01-23 Impact factor: 6.992
Authors: Joseline Sofía Ocaña-Cabrera; Jonathan Liria; Karla Vizuete; Cristina Cholota-Iza; Fernando Espinoza-Zurita; Claude Saegerman; Sarah Martin-Solano; Alexis Debut; Jorge Ron-Román Journal: PLoS One Date: 2022-09-20 Impact factor: 3.752