Analysis of food pairing in regional cuisines of India

TL;DR

This study analyzes the food pairing patterns in eight Indian regional cuisines, revealing a general tendency towards negative food pairing driven by ingredient usage frequency, with spices and dairy playing key roles.

Contribution

It provides a comprehensive data-driven analysis of regional Indian cuisines, identifying the influence of ingredient classes on food pairing patterns and suggesting applications in recipe generation and health research.

Findings

All cuisines exhibit negative food pairing patterns.

Frequency of ingredient usage influences food pairing characteristics.

Spices promote negative pairing, while dairy tends to positive pairing.

Abstract

Any national cuisine is a sum total of its variety of regional cuisines, which are the cultural and historical identifiers of their respective regions. India is home to a number of regional cuisines that showcase its culinary diversity. Here, we study recipes from eight different regional cuisines of India spanning various geographies and climates. We investigate the phenomenon of food pairing which examines compatibility of two ingredients in a recipe in terms of their shared flavor compounds. Food pairing was enumerated at the level of cuisine, recipes as well as ingredient pairs by quantifying flavor sharing between pairs of ingredients. Our results indicate that each regional cuisine follows negative food pairing pattern; more the extent of flavor sharing between two ingredients, lesser their co-occurrence in that cuisine. We find that frequency of ingredient usage is central in rendering the characteristic food pairing in each of these cuisines. Spice and dairy emerged as the most significant ingredient classes responsible for the biased pattern of food pairing. Interestingly while individual spices contribute to negative food pairing, dairy products on the other hand tend to deviate food pairing towards positive side. Our data analytical study highlighting statistical properties of the regional cuisines, brings out their culinary fingerprints that could be used to design algorithms for generating novel recipes and recipe recommender systems. It forms a basis for exploring possible causal connection between diet and health as well as prospection of therapeutic molecules from food ingredients. Our study also provides insights as to how big data can change the way we look at food.