Correspondence analysis and adsorbate selection for chemical sensor arrays

Carey et al. utilized principal components analysis (PCA) to analyze frequency shift data obtained from piezoelectric sensors formed by coating quartz crystals with 27 different GC stationary phases and tested using 14 analytes. The objective of the analysis was to determine an optimal reduced set of coatings for detection of the analytes. The results were correlated with those obtained from cluster analysis. In this paper the data are re‐analyzed using correspondence analysis (CA). The advantage of using CA include a symmetric treatment of sensor coatings and analytes and better identification of the representation of the analytes in terms of the detection components. The results obtained by the conjunctive use of PCA, a varimax rotation and cluster analysis were obtained by CA.