Heres How AI Can Determine The Taste Of Coffee Beans – Forbes

Coffee cups are pictured in the tasting area of the Vanibel cocoa and vanilla production facility, a ... [+] former 18th Century sugar refinery in Vieux-Habitants, Guadeloupe, on April 9, 2018. / (Photo credit HELENE VALENZUELA/AFP via Getty Images)

Artificial intelligence (AI) ispredictedto reach $126 billion by 2025. It is showing up in every industry, from healthcare and agriculture to education, finance and shipping. And now, AI has made a move to the food industry to discover and develop new flavors in food and drink.

In 2018, Danish brewer,CarlsburgusedAIto map and predict flavors from yeast and other ingredients in beer. IBM developed an AI for McCormick to create better spices. AndNotCo, which produces vegan NotMilks, uses AI to analyze molecular structures and find new combinations of plant-based ingredients.

A Colombian startup,Demetria, has raised$3 millionto date and is betting on its sensory digital fingerprint using AI to match a coffee bean's profile to the industry's standardcoffee flavor wheelcreated in 1995.

The new company says that this new sensory digital fingerprint for coffee beans will let roasters and producers assess quality and taste at any stage of the coffee production process.

Felipe Ayerbe, CEO of Demetria, says the wine-a-fication of coffee is here to stay.

"Coffee drinkers today have been exposed and are more aware of the taste and general experience they are looking for and are willing to pay more for that experience," said Ayerbe. "That is why you see an ever-growing array of possibilities and choices for something that is supposedly a commodity - different prices, origins, roasts, blends, flavor characteristics, preparations just like wine."

Ayerbe notes that coffee is still considered a tradable commodity, but the experience that consumers get is anything but a commodity. "In the last 20 years [..], coffee has undergone a voyage of premiumization where the most important variable is sensory quality - taste," adds Ayerbe.

Ayerbe says this revolution in specialty coffees was spurred in part by industry pioneers like Starbuck and Nespresso that upgraded the world's taste in coffee.

"With this sensory digital fingerprint, we are upgrading the industry from analog to digital by allowing the full value chain to [..] measure and manage the most important variable in the industry - taste," said Ayerbe. "We envision that farmers will for the first time not only be able to understand the quality of what they are selling but also manage their farming practices to optimize their quality, creating an unparalleled level of empowerment for them."

The sensor technology that Demetria uses has existed for 40 years.

"In the past several years, sensors have become miniaturized, more affordable and can connect to the cloud," said Ayerbe. "This allows for the collection, storage and analysis of huge amounts of data."

Ayerbe says the company uses handheld near-infra-red (NIR) sensors to read the spectral fingerprint of green coffee beans. This is because the different colors and wavelengths of the light spectrum react differently to each organic compound present in the coffee, representing the whole chemical composition of the beans.

"We then needed AI to translate the NIR data into the sensory language the industry understands," said Ayerbe. "And, until now, the taste or sensory quality of coffee beans has been determined by cupping, a manual, time-consuming process carried out by the industry's certified tasting experts, measured according to the industry's standard coffee tasting wheel," said Ayerbe.

With all the data gathered from the NIR readings and the cupping data, Demetria calibrated the AI to match a specific spectral fingerprint to an unmistakable taste profile.

Ayerbe says that the biggest hurdle the team had to overcome was determining subjective taste identifiers like body, balance and aftertaste that were in line with the standardized coffee taster's flavor wheel.

"These taste identifiers had to be determined holistically, rather than individually, to establish the true overall flavor profile of the coffee bean," said Ayerbe. "Also, coffee beans from the same sample are not homogenous, so for a single 300-500 gram sample of beans, multiple scans were required to gather enough data to represent an overall, unanimous flavor profile."

Demetria made thousands of scans that considered the slightest difference between each reading from a wide range of different coffee beans, and the result was a model with a sensorial digital fingerprint unique to Demetria.

Armed with the unique sensory digital fingerprint, Demetria built a matchmaking profile for a distinct flavor profile forCarcafeby training their AI and models to use spectral readings and correlating those with the cupping analyses from hundreds of samples coffee.

"The AI for the high-value profile required by Carcafe was gathered from multiple hundreds of samples of green coffee beans and measured against q-graders (cuppers) who sent over data on their cupping scores," said Ayerbe. "By compiling the big data cupping analysis, we were able to match the sensory fingerprint to this unique Colombian coffee."

Ayerbe said that after four months of processing the coffee samples, the company created a viable product for Carcafe where the AI was continuously retrained with new samples.

"The biggest technical challenge was training the AI to detect nuances in taste like a cupper can detect, rather than just clear profiles," said Ayerbe. "Clear profiles need to exist in the database, but the whole gamut of nuances need to be programmed too."

For the Carcafe profile that Demetria was matching, it needed to determine a particular sweetness; for example, chocolate is different from caramel which is different from brown sugar sweetness.

"So in the second iteration, we had to define the true taste and ensure that the AI could be specific enough to determine between these very similar but different types of sweetness," said Ayerbe. "To be able to pinpoint the producers that can match this profile exactly and give the farmers the tools to be able to grow that crop again consistently brings a new level of efficiency and transparency to Carcafe and their customers."

Ayerbe believes this process removes many variables and unknowns that currently exist in the coffee supply chain.

"If you can control more of the process, you will end up with less defective coffee, which will increase overall availability," adds Ayerbe. "It's also important to note that cuppers play a vital role in the training of the model, and this technology is in no way meant to replace their position in the industry."

Ayerbe says the problem with cupping is that it's a [..] scarce resource. "We are expanding the ability to assess sensory quality ubiquitously, along the whole value chain, and this especially is applicable at the producer level where cupping doesn't currently exist."

Ayerbe adds that their technology facilitates better use of the cuppers' time and allows traders and roasters to be more efficient in understanding who is producing the taste, type and quality of coffee they seek.

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Heres How AI Can Determine The Taste Of Coffee Beans - Forbes