Interlaboratory comparison of the intensity of drinking water odor and taste by two-way ordinal analysis of variation without replication. (26th May 2022) - Gadrich, Tamar; Kuselman, Ilya; Pennecchi, Francesca R.; Hibbert, D. Brynn; Semenova, Anastasia A.; Cheow, Pui Sze; Naidenko, Vladimir N.
Abstract: A case study of ordinal data from human organoleptic examination (sensory analysis) of drinking water obtained in an interlaboratory comparison of 49 ecological laboratories is described. The recently developed two-way ordinal analysis of variation (ORDANOVA) is applied for the first time for the treatment of responses on the intensity of chlorine and sulfurous odor of water at 20 and 60 ° C, which is classified into the six categories from 'imperceptible' to 'very strong'. The one-way ORDANOVA is used for the analysis of the 'salty taste' intensity of the water. A decomposition of the total variation of the ordinal data and simulation of the multinomial distribution of the data-relative frequencies in different categories allowed the determination of the statistical significance of the difference between laboratories in classifying chlorine or sulfurous odor intensity by categories, while the effect of temperature was not significant. No statistical difference was found between laboratories on salty taste intensity. The capabilities of experts to identify different categories of the intensity of the odor and taste are also evaluated. A comparison of the results obtained with ORDANOVA and ANOVA showed that ORDANOVA is a more useful and reliable tool for understanding categorical data such as the intensity of drinking water odor and taste. HIGHLIGHTS: An interlaboratory comparison of human responses to water odor and taste is reported. The two-way ORDANOVA is applied for the study of responses to water odor intensity. Interlaboratory data on water taste intensity are studied with the one-way ORDANOVA. The significance of some factors' influence on a laboratory result is evaluated. The applicability of ORDANOVA and ANOVA for ordinal data analysis is discussed. Graphical Abstract