Principles and methods for automated palynology

Katherine A Holt, Keith Bennett

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)


Pollen grains are microscopic so their identification and quantification has, for decades, depended upon human observers using light microscopes: a labour-intensive approach. Modern improvements in computing and imaging hardware and software now bring automation of pollen analyses within reach. In this paper, we provide the first review in over 15 yr of progress towards automation of the part of palynology concerned with counting and classifying pollen, bringing together literature published from a wide spectrum of sources. We
consider which attempts offer the most potential for an automated palynology system for universal application across all fields of research concerned with pollen classification and counting. We discuss what is required to make the datasets of these automated systems as acceptable as those produced by human palynologists, and present suggestions for how automation will generate novel approaches to counting and classifying pollen that have hitherto been unthinkable.
Original languageEnglish
Pages (from-to)735-742
Number of pages8
JournalNew Phytologist
Issue number3
Early online date27 May 2014
Publication statusPublished - Aug 2014


  • automation, palynology, pollen counting, pollen identification, protocols


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