Starch data should be presented in a table showing sample number and provenience details, sample weight (for quantitative standardisation), raw starch counts per morphotype/taxon and condition, and any relevant calculations of sample ubiquity, percentage frequency, etc. (see example below). These data can then be examined visually or interrogated using statistical methods to detect qualitative and/or quantitative trends in the distribution and frequency of different starch types.

It is relatively straightforward to determine:

  • whether a tool was multi-purpose (i.e. used to process many different types of starch-rich plants) or specialised (e.g. Berman and Pearsall 2008);
  • the number of tools used to prepare specific plants (species ubiquity);
  • whether a sample contains starches that are damaged, possibly from food processing activities.

From these data, it is also possible to assess whether starches recovered from artefacts are most likely use-related or derived from the surrounding sediment, by examining whether there are there quantitative and/or qualitative differences between assemblages from the artefact’s used and non-used surfaces and control sediment samples. Qualitative differences can be established simply by examining whether different types of starch (including morphotypes and damaged types) occur in these different samples. Because plant processing activities such as grinding or cooking are also likely to deposit the same types of starch in the surrounding sediment, it is also important also to check for quantitative differences between these assemblages, as it is expected that starch concentrations would be much higher on the artefact (owing to repeated contact with the plant) than in the sediment.