Evaluation of wine competition judge performance using principal componentsimilarity analysis

Principal component similarity (PCS) analysis was used to evaluate judge pe rformance from a wine competition. Data were analyzed for five internationa l judges and seven wine makers, for 42 white, 30 red and 25 specialty wines , using a 20-point quality scoring system. Principal similarity plots were used to group judges according rejudging 'style' and to identify outliers, for each wine category. Judge groupings were consistent when three differen t references were used; however, the most interpretable PCS plot was obtain ed when the overall mean-judge-score was used as the reference. Results fro m PCS were compared to principal component analysis (PCA). PCS analysis all owed the information from all significant principal components to be graphi cally represented in two dimensions and was more successful in classifying judges than plots based on the first three principal components. The techni que of PCS is an important complement to existing methodologies, and can pr ovide wine competition coordinators with an objective technique forjudge ev aluation and selection.