Data-driven Methods for the Study of Food Perception, Preparation, Consumption, and Culture

Abstract

The study of food consumption, in the broadest sense, intersects with a wide range of academic disciplines. The perception of food involves molecular biology, chemistry, soft-matter physics, neuroscience, psychology, physiology, and even machine learning. Our choices and preparation of food are of interest to anthropologists, social scientists, historians, philosophers, and linguists. The advent of information technology has enabled the accumulation and analysis of large amounts of food-related data, from the interactions of biomolecules and the chemical properties of aroma compounds to online recipes and food-related social media postings. In this perspective article, we outline several areas in which the availability and analysis of data can inform us about general principles that may underlie the perception of food and the diversity of culinary practice. One of these areas is the study of umami taste through a combination of chemical analysis and quantitative sensory evaluation for a wide range of fermented products. Another is the mapping of global culinary diversity by mining online recipes and the analysis of culinary habits recorded by individuals on social media. A third area is the study of the properties of flavour compounds, and the application of these insights in the context of high-end gastronomy. These examples illustrate that large-scale data analysis is already transforming our understanding of food perception and consumption, and that it is likely to fundamentally influence our food choices and habits in the future.