This article reports the findings and methodology of a study that discriminated the features of unprocessed cotton based on its geographic origin, using multi-element stable isotope signatures.
Since cotton is the most used natural plant product for the manufacture of yarns and textiles and there are differences in the textile quality of cotton based on where it is grown, product labeling requirements demand that proof of geographic origin of the cotton in a textile should require more than a paper-based audit trail. In applying isotope ratio mass spectrometry to generate multivariate data sets of raw cotton, the current study used a two-point equilibration process with water at ambient temperature 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 U.S. cotton and 15 non-U.S. cotton samples was able to cluster 15 of the 17 U.S. cotton samples in one group. The study concluded that hierarchical cluster analysis of multivariate stable isotope signatures of raw cotton showed great promise as an analytical tool to differentiate between U.S. and non-U.S. cotton and possibly even to be able to group unprocessed cotton according to geographic origin. (publisher abstract modified)