The grass family (Poaceae) is one of the most economically important plant groups in the world today. In particular many major food crops, including rice, wheat, maize, rye, barley, oats and millet, are grasses that were domesticated from wild progenitors during the Holocene. Archaeological evidence has provided key information on domestication pathways of different grass lineages through time and space. However, the most abundant empirical archive of floral change - the pollen record - has been underused for reconstructing grass domestication patterns because of the challenges of classifying grass pollen grains based on their morphology alone. Here, we test the potential of a novel approach for pollen classification based on the chemical signature of the pollen grains measured using Fourier transform infrared (FTIR) microspectroscopy. We use a dataset of eight domesticated and wild grass species, classified using k-nearest neighbour classification coupled with leave-one-out cross validation. We demonstrate a 95 % classification success rate on training data and an 82 % classification success rate on validation data. This result shows that FTIR spectroscopy can provide enhanced taxonomic resolution enabling species level assignment from pollen. This will enable the full testing of the timing and drivers of domestication and agriculture through the Holocene.