Ganesh Bagler, professor at the Indraprastha Institute of Information Technology Delhi, found that the field of computational gastronomy, a mix of data science and food, could revolutionize the food industry and be used for better physical health and nutrition through culinary practices such as menu design, food-and-beverage pairing, creative recipe formation, dietary interventions and predicting flavour mixtures and savours.
In recent years, Bagler has amassed facts and data and uploaded it on his online, publicly-accessible platform, RecipeDB – a compilation of 1.2 lakh recipes from 74 countries and 26 regions, which can be processed and computed. He has also established an open-source database, FlavorDB, with 25,595 flavour molecules representing tastes and aromas, and have assembled a recreational platform called DietRx that examines diet-related elements to map the link between food and imperative molecular agents.
The crew is steadily updating their databases, as well as developing a way to analyse a food item by simply scanning it with a cellphone to work out the calorie content. Such a platform gives one the ability to solicit a list of ingredients and receive suitable recipes, or to look for French dishes that don’t include garlic but including onion and chilli.
Bagler’s use of computational techniques to identify unusual food pairings in Indian cuisine were eligible to be recognised as an up-and-coming technology by MIT Technology Review.
Popular wisdom says that foods tend to taste better when ingredients are in conformity with each other’s flavour. According to Bagler’s research, Indian cuisine is distinct as it heavily requires contrasting food pairings.
Data-driven technology can also be employed in the food industry to become more sustainable – a work that includes evaluating the number of calories for 600 to 700 ingredients, and the calorie-content for the entire recipe. Such facts have the probable to be wanted by bureaucratic organisations. In advanced countries, customers frequently demand more information on the carbon or water footprint of the recipe.
At the moment, Bagler works with 8-10 establishments in the food and beverage industry. Businesses are curious about being able to pair food items in order to better market their products, and some seek to create something that would be acceptable across the Indian subcontinent.
As AI and food-related facts are entwined, this development induces a new way of understanding food-related matters. The Chairman of US firm WISEcode, Paul Magelli, says that computational gastronomy gives people a greater perception of what lies in their food, how it affects their health, explains why a food tastes and smells as it does and looks into its sustainable production.
Experienced chefs scrutinise and employ advanced technology to attempt unlikely and occasionally unpleasant combinations, and still end up with exquisite dishes. Parvinder Singh Bali, of the Oberoi Centre for Learning and Development, remembers watching Heston Marc Blumenthal closely teaming up with analysts to confirm that blue cheese and chocolate actually is an agreeable duo when it comes to flavours.
Akshay Malhotra, a restaurateur and one of the partners at TagTaste – an online platform providing space for culinary specialists to join forces and work together – utilised FlavorDB database to recognize the link between foodstuffs, while also referring to Bagler’s research to know why, in some cases, strawberry fusion in pastries and drinks carries with it tart notes of pineapples and tropic fruits. According to Malhotra, certain food corporations skip the cost of utilising strawberry flavouring and instead have pineapple as a replacement.
Compagander is a New York-based organisation that uses data science, technology and artificial intelligence to develop a range of beauty, dietary and lifestyle products. By using AI, Compagander hopes to be able to help people optimise and personalise all aspects of the health, lifestyle and beauty.
