Discrimination of unprocessed cotton on the basis of geographic origin using multi-element stable isotope signatures

Cotton is the most commonly used natural plant product for the manufacture of yarns and textiles. Consumer perception regarding differences in textile quality in relation to geographic provenance of cotton as well as stringent product labelling requirements demand for the supply chain to furnish proof of geographic provenance beyond merely paper-based audit trails.

We have applied isotope ratio mass spectrometry to generate multivariate data sets of raw cotton. A two-point equilibration process with water at ambient temperature was used to account for hydrogen exchange between free hydroxyl groups in the cellulose lattice at ambient humidity, prior to hydrogen isotope analysis.

The molar fraction of exchangeable hydrogen in cotton at ambient temperature was found to be 0.046, which is in good agreement with the expected exchange fraction of 0.05. Hierarchical cluster analysis of multivariate stable isotope abundance data from 17 US cotton and 15 non-US cotton samples was able to cluster 15 of the 17 US cotton samples in one group.

Hierarchical cluster analysis of multivariate stable isotope signatures of raw cotton showed great promise as an analytical tool to differentiate between US and non-US cotton and possibly even to be able to group unprocessed cotton according to geographic origin.