Like all scientific breakthroughs, there needs to be some sort of experiment or evidence gathering to prove a hypothesis. Sometimes these breakthroughs are unrelated to the original hypothesis and are made by accident - as long as there’s some form of information to analyse, there’s scope for discovery. With so much of an ordinary person’s life now open to analysis by the data they leave behind, we are beginning to make breakthroughs that explain everyday life experiences.
Recently a piece in The Hindu reported a study that used data analytics techniques to establish an unusual feature of Indian cuisine. It found that, whereas most other global cuisines rely on positive food pairing – the pairing of similarly flavoured ingredients - Indian cuisine instead relies on negative food pairings using dissimilarly flavoured ingredients. They also discovered, by shuffling around ingredients in a recipe to observe its effect on negative food pairing, that it was the spice that drove the negative pairing. Of the top 10 ingredients whose presence biased the flavour-sharing pattern of Indian cuisine towards negative pairing, nine were spices.
Indian cuisine is much more complex as 20 ingredients may be used for a dish compared to, say, five for a typical Western dish. When you consider this, and the variation in Indian cuisine across regions and groups, there are multiple possible combinations of ingredients which may all get a different reaction depending on who is tasting them. It demonstrates how Indian recipes could be personalised according to what spice combinations a person prefers. Read More