Chemotaxonomy as a tool for interpreting the cryptic diversity of Poaceae pollen

The uniform morphology of different species of Poaceae (grass) pollen means that identification to below family level using light microscopy is extremely challenging. Poor taxonomic resolution reduces recoverable information from the grass pollen record, for example, species diversity and environmental preferences cannot be extracted. Recent research suggests Fourier Transform Infra-red Spectroscopy (FTIR) can be used to identify pollen grains based on their chemical composition. Here, we present a study of twelve species from eight subfamilies of Poaceae, selected from across the phylogeny but from a relatively constrained geographical area (tropical West Africa) to assess the feasibility of using this chemical method for identification within the Poaceae family. We assess several spectral processing methods and use K-nearest neighbour (k-nn) analyses, with a leave one-out cross-validation, to generate identification success rates at different taxonomic levels. We demonstrate we can identify grass pollen grains to subfamily level with an 80% success rate. Our success in identifying Poaceae to subfamily level using FUR provides an opportunity to generate high taxonomic resolution datasets in research areas such as palaeoecology, forensics, and melissopalynology quickly and at a relatively low cost. (C) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license.