Panel performance monitoring by Poincaré plot: A case study on flavoured bottled waters

- Poincaré method should be used when missing or less data are inevitable.
- The method captures dissimilarity and serial correlation in sensory data.
- Case study on flavoured bottled water samples with free R code
- Ranking of product attributes/panelists and measurement of panel consistency
- The method is compared to other techniques and cross-validated.

The application of the Poincaré method is discussed on the field of sensory panel performance monitoring. The Poincaré plot evaluates and visualizes the difference from the consensus for each panelist even for one product and for one attribute. Sensory tests were carried out on 5 commercially available brands of pear-lemon and josta flavoured bottled waters. Several sensory parameters were assessed and a complex dissimilarity index was calculated. Based on this index the attributes and panelists can be ranked highlighting the attribute which was the hardest to evaluate and the most consistent panel member. Our method has been compared to the other methods using the sum of ranking difference method and cross-validated by leave-one-out technique. Regarding both the ranking of the panelists and the ranking of the attributes significant differences were found between the Poincaré method and the traditional techniques since the sum of ranking difference was greater than the critical value of 39 and 79 at 5%, respectively. Only the Poincaré method was able to indicate sweet flavour as the easiest attribute to evaluate. Free R code is available to carry out the calculations and apply this method.

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