Assessing the relationship between concentrations of malodor compounds and odor scores from judges.

Background: The purpose of this review was to assess the relationship between mean organoleptic scores (using a 0-to-5 scale) and concentrations of putative odorants representative of those thought to be important in oral malodor, as well as to propose a simple model that explains the dose-response curves obtained from a group of odor judges.

Methods: The model assumes that the scale is rooted at the detection threshold (0), the maximum score (5) is fully saturating and the brain and olfactory nervous system can act as a faithful transducer of the state of binding (occupancy) of the smell receptors in the nose. The authors predicted that the response would be exponential or sigmoidal in nature. They tested this using published empirical data based on seven odor judges and eight odor compounds.

Results: Analysis of the data by different plotting methods showed the odorants to be significantly different from each other (P < .01 by regression analysis) with regard to thresholds and slopes. The lower the threshold, the stronger the inherent odor of the compound. The greater the slope, the greater the odor power. Volatile sulfur compounds had low smell thresholds and high odor power and were highly volatile, while indole was less volatile but had a very low threshold. Both compounds may be significant in human oral malodor.

Conclusions: The authors found that the organoleptic scale was exponential in practice. These findings imply that when inhibitory agents are tested against odor-generating bacteria, a given percentage inhibition of the volatile compound production rate by a treatment (such as an antimicrobial mouthwash) will result in an equal incremental reduction on the scale, regardless of the starting position on the scale. Understanding the scale enables dental professionals to develop better ways of training, calibrating and standardizing odor judges, along with better ways of designing clinical trials and interpreting data regarding the efficacy of antiodor treatments.