Principal component similarity analysis for classification and its application to GC data of mango

Abstract As a method for classification, principal component similarity (PCS) analysis reported previously was modified. It was found by using model computation that PCS was easy to use to interpret the result of discrimination, especially when purposes of classification were not clearly defined in advance (unsupervised). A portable, low-cost headspace gas chromatograph (GC) was used for routine analysis of volatile compounds recovered from mango samples. PCS could classify the mango samples based on cultivars which were ripened in storage and on the tree. PCS was, as a result, found to be useful in processing the obtained GC data for crude classification, preliminary to detailed analysis, e.g. obtained GC data for crude classification, preliminary to detained analysis, e.g. stepwise discriminant analysis.