Event recap: What you missed at the Digital Olfaction Panel at Monell’s Spring Colloquium

By Fanny Turlure

This month I had the pleasure of participating in a digital olfaction panel at Monell’s Spring Colloquium event. I was joined by fellow panelists from International Flavors & Fragrances Inc. (IFF) and the Monell Chemical Senses Center where we discussed the impact innovation has on the field of malodor detection and masking. If you missed the panel, here were some of the key takeaways:


Malodor masking isn’t as easy as it may seem

As malodor masking techniques continue to evolve, some challenges have come to the forefront around consistency and masking with certain fragrances. The malodor experience can vary widely from human to human and culture to culture, making it difficult to create standards across populations and geographies. Malodors also evolve over time, creating challenges around establishing a consistent, time-based odor analysis.

When it comes to masking a malodor itself, many brands and users jump to masking with what they consider a “more pleasant” fragrance. However, masking with fragrance can result in an even higher intensity odor although the malodor itself is usually decreased. This creates complications around untangling bad odors from fragrance and some combinations might ultimately give rise to other worse malodors. We’re seeing several technologies, such as digital olfaction, emerge that can help dissect and address these challenges.


Using human panels alone to screen malodors has its downfalls – but technology can help 

As brands roll out products, many rely on consumer testing through focus groups and panels to screen odors. Odors are complicated and difficult to standardize, so a human’s assessment is extremely valuable. But while human testing has its benefits such as faster results for gas odor samples and direct links to actual human perception, the approach falls short in a number of ways.

Panel design can be time consuming and expensive to organize, and accounting for diversity has become a significant issue. When testing via a human consumer panel, brands are often limited to the demographics of the area which can skew the results. Further, the sheer act of repeatedly assessing unpleasant odors is an unwelcome task for many, making recruiting testers a tricky task. Humans also risk experiencing olfactory fatigue (diminished sensitivity to all odors) and adaptation (diminished sensitivity to one specific odor to which one has been exposed for a prolonged time) which impacts their ability to consistently evaluate odors over time.

This is why many brands have turned to incorporating analytical equipment and technology for more efficient and effective odor testing. It’s safe to say that equipment doesn’t tire and can run 24/7. It does not experience olfactory fatigue or adaptation and can test more formulations than humans in any given time period. Many labs use a host of analytical techniques such as gas chromatography–mass spectrometry (GC-MS) to help augment the testing process. However, GC-MS can take a long time for results with limited throughput, resulting in a limited capacity for screening samples. Digital olfaction also quickly assesses materials and ensures product consistency through odor analysis, streamlining results by enabling labs to send only the best performing products to human panels for final evaluation.


Innovation is on the rise!

There were a few malodor innovations discussed at the event that I was particularly excited about. The first being the increased application of machine learning and artificial intelligence to augment human panels to empower brands to better account for regional and cultural preferences. Even though it is clear that technology helps expedite malodor testing, some level of human involvement in the evaluation process will need to remain (at least in the near future), so addressing this diversity challenge is critical.

Along the same lines, the industry is working towards a solution to make digital tools more relevant and representative of the human smelling experience. How can data be translated into hedonic characteristics, and even into like/dislike or judgment? The jury is still out on this one, but we’re seeing more organizations experiment with building models around how data and specific patterns could be translated into hedonic characteristics. In an ideal world, input and data from human panels and technology, like digital olfaction tools, would cross-feed each other for the most accurate and streamlined malodor analysis.

To learn more about how Aryballe’s digital olfaction technology can help enhance malodor detection and masking, click here.