Fragrances result in a combination of certain ingredients, but the research team says that it is often trial-and-error when it comes to predicting how they will end up smelling.
This has led to the development and validation of the Perfumery Radar 2.0 model, updated from a previous version which helps predict resulting smells.
The tool classifies perfumes into families, such as floral, citrus or musk; and also identifies their nuances, such as spicy or sweet, fresh or warm.
On the radar
According to Miguel A. Teixeira and colleagues from LSRE laboratory in Portugal, when compared to how perfumers categorized the fragrances tested, their ‘radar’ closely matched how the experts described them, without subjective biases.
The researchers say that it will be a “valuable tool for the pre-formulation stages of fragrance design and classification, thus helping perfumers” create new scents.
They also say it offers a different mode of analysis from traditional methods of relying only on experts' sense of smell to blend fragrances.
Time and material saving
“The design of new fragrances for the perfume industry still relies on a trial-and-error process, which requires time and some raw materials that are in short supply,” says the research.
“And although expert perfumers have famously well-trained noses, they are still affected by biases, such as personal experience and social habits.”
Experts also disagree on the nuances of a given fragrance, which can be complex, depending on the number of ingredients and how they interact with each other.
Teixeira's team wanted to see if they could quantify what the nose knows and use science to bolster the art of the fragrance industry.
The study appears in the ACS journal Industrial & Engineering Chemistry Research.