Collaborating Authors

Plant-based burger company uses algorithms to generate flavors and address consumer preferences

Daily Mail - Science & tech

A Swiss fragrance company is counting on artificial intelligence to help it perfect the plant-based burger. Firmenich, one of the world's leading flavor manufacturers, says recreating the sensation of beef relies not only on flavor, texture and color, but also on how it responds to cooking and the way it feels in the mouth. 'Finding a protein that resembles meat from a vegetable protein is highly complex,' Emmanuel Butstraen, head of Firmenich's flavors unit, told AFP. One of the toughest challenges is avoiding an unpleasant aftertaste--pea proteins tend to release bitterness, which the taste buds are quick to pick up, Butstraen noted. Vegetable proteins can give off hints of green apples or pears, an aftertaste of beans, bitterness or sourness, or even a feeling of dryness, said Jerome Barra, the company's innovation director.

Firmenich creates the world's first flavor entirely with Artificial Intelligence


Geneva-based Firmenich, the world's largest privately owned perfume and taste company, is using Microsoft-powered Artificial Intelligence to serve consumers' Food & Nutrition needs with speed, creativity and innovation. The 125 year old Swiss company opened its d-lab, or digital lab, in Lausanne in 2018. Led by Firmenich's purpose to create positive emotions to enhance wellbeing naturally, the d-lab's mission is to drive what Chief Digital & Information Officer, Eric Saracchi, calls "tech for good" through end to end value chain digital transformation. For Firmenich, this includes everything from collecting consumer insights through digital surveys to digital tracking of raw materials to ensure the most accurate and transparent supply chain traceability and optimizing plant safety. In February, Firmenich's Flavors Division began one of these global insights studies with a series of surveys of 15k people across 22 countries.

Drinking coffee from a 'smooth' cup makes it tastes better, scientists claim

Daily Mail - Science & tech

It's a claim which is bound to cause a stir among coffee lovers. Experts say what you sip the drink from affects its flavour – with a rough cup leaving a bitter after-taste while the same coffee tastes sweeter from a smoother vessel. Scientists in Brazil – the world's biggest coffee producer – ran tests involving experts and regular drinkers. They found that the'haptic' – or touching – experience of what people were drinking from made a big difference. More than 230 people took part in the research, with half of them experts – including professional coffee graders.

Ripple Foods world's first pea-derived milk contains 50 per cent more calcium than dairy

Daily Mail - Science & tech

From almond to soy, a variety of alternatives to cows milk can now be found in most supermarkets. But now there is an even odder option for those looking for a sip of white stuff without any lactose inside - a milk made from peas. Now, Ripple Foods have created a legume-derived milk, which contains protein from yellow peas. Ripple Foods have created the world's first legume-derived milk, which contains protein from yellow peas (pictured) The company is hoping to compete with the dairy industry with milk derived from pea proteins. The milk is made from yellow peas - round legumes that are dried and then split in half by hand or by machine.

NotCo taps AI to develop new plant-based alternatives - Verdict


Chilean food-tech start-up NotCo uses artificial intelligence (AI) to identify the optimum combinations of plant proteins when creating vegan alternatives to animal-based food products. The company, set up in 2015, has attracted investment from Amazon founder Jeff Bezos and Future Positive, a US investment fund founded by Biz Stone, the co-founder of Twitter. NotCo's machine learning algorithm compares the molecular structure of dairy or meat products to plant sources, searching for proteins with similar molecular components. NotCo has a database containing over 400,000 different plants, including macronutrient breakdown and chemical composition. These factors are used to predict novel food combinations with the target flavour, texture, and functionality.