Food, nutrition, culture, heritage. At the upshot, computational gastronomy brings all of these together to record recipes, track ingredients, and make insightful deductions of what we eat traditionally, and “why we eat what we eat,” as Prof Ganesh Bagler from IIIT-Delhi, puts it. The idea came about when he was teaching network science in IIT Jodhpur, and spoke to the students about the concept of a flavour network, that Yong-Yeol Ahn had studied, “of whether there are any general patterns that determine the ingredient combinations used in food today, or principles that transcend individual tastes and recipes,” as the paper says.
To the scientist then, computational gastronomy is the study of ingredients, and how and why they are used with one another, where each ingredient “becomes a bowl of flavour molecules”. It is looking at food as not just art, craft and skill, but also as a science. Which means the subject brings together data scientists and researchers, chefs, nutritionists, agriculturists, and people from the food industry, with the opportunity to bring about synergies. In terms of how far the science has developed, “We stand at 19th-century physics,” he says. Some things will still be in the realm of art.
Prof Bagler specifically wants to look at Indian cuisine at the present, and understand food pairing, or the way in which ingredients are put together. The chief insight so far has been that while Indian food has contrasting food pairing (combining flavours that aren’t similar to each other, in a dish), Western cuisine is based on complementary or uniform food pairing (flavours in a dish close to each other).
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Breaking it down
There are two initial legs to the process: recipe data compilation and ingredient (flavour) data compilation. It’s not easy to identify ‘set’ recipes in India because every family may cook, say
In terms of flavour molecules, data is compiled from the PubMed and Medline databases, which means research papers for 70-odd years are available. Information on ingredients has been extracted from these. There are about 1000 ingredients so far, with 192 unique ones, in the database. They will soon be compiling and publishing data on the health associations of ingredients.
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Cognizant of both covert biases (like conflict of interest) and overt biases (like ‘safe’ studies added to the scientific body that are unlikely to rock the boat), Prof Bagler is trying to come up with strategies to discount for the bias. He is also conscious of reductionism and over-simplification of food practices, and says as the science grows, the complexity and layers of the subject will also grow. Take turmeric: we know it’s good for health. But how much, in what quantity, in what way it was farmed, what ingredient bumps up its potential — all these are still to be studied. Going back to why we eat what we eat, Dr Bagler says that it could be a matter of taste, but it could also be because of the protective and sometimes medicinal value of our foods, but we need a deeper understanding of our food culture.
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