Environmental discrimination based on quartz grain surface textures: a statistical investigation

ABSTRACT The relative abundance of thirty-two surface features identified on the surfaces of quartz sand grains from eight coded samples was noted independently by five scanning electron microscopists. These data (reduced to binary form) were the subject of canonical variate analyses which discriminated clearly between all samples. Thirteen variables were important in distinguishing between the eight samples. This indicates that there are no single key surface features which, on their own, would allow rapid environmental discrimination. The contention that a multiplicity of surface features should be recorded for the purpose of environmental discrimination is, therefore, upheld. Operator variance, although considerable in the recognition of individual surface features, is negligible in discrimination of samples based on binary data. The SEM technique of analysis of quartz grain surface textures is a reliable and statistically valid means of discriminating between samples from different environments.