Food-Bridging: A New Network Construction to Unveil the Principles of Cooking

In this manuscript we propose, analyse, and discuss a possible new principle behind traditional cuisine: the Food-bridging hypothesis and its comparison with the food-pairing hypothesis using the same dataset and graphical models employed in the food-pairing study by Ahn et al. [Scientific Reports,1:196,2011]. The Food-bridging hypothesis assumes that if two ingredients do not share a strong molecular or empirical affinity, they may become affine through a chain of pairwise affinities. That is, in a graphical model as employed by Ahn et al., a chain represents a path that joints the two ingredients, the shortest path represents the strongest pairwise chain of affinities between the two ingredients. Food-pairing and Food-bridging are different hypotheses that may describe possible mechanisms behind the recipes of traditional cuisines. Food-pairing intensifies flavour by mixing ingredients in a recipe with similar chemical compounds, and food-bridging smoothes contrast between ingredients. Both food-pairing and food-bridging are observed in traditional cuisines, as shown in this work. We observed four classes of cuisines according to food-pairing and food-bridging: (1) East Asian cuisines, at one extreme, tend to avoid food-pairing as well as food-bridging; and (4) Latin American cuisines, at the other extreme, follow both principles. For the two middle classes: (2) Southeastern Asian cuisines, avoid food-pairing and follow food-bridging; and (3) Western cuisines, follow food-pairing and avoid food-bridging.

[1]  References , 1971 .

[2]  Cinly Ooi,et al.  Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder , 2015, PloS one.

[3]  Kush R. Varshney,et al.  Flavor Pairing in Medieval European Cuisine: A Study in Cooking with Dirty Data , 2013, ArXiv.

[4]  Donald B. Johnson,et al.  Efficient Algorithms for Shortest Paths in Sparse Networks , 1977, J. ACM.

[5]  John Suckling,et al.  Commentary: Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder , 2016, Front. Neurosci..

[6]  Albert-László Barabási,et al.  Flavor network and the principles of food pairing , 2011, Scientific reports.

[7]  Vasiliki Kalavri,et al.  The shortest path is not always a straight line , 2016, Proc. VLDB Endow..

[8]  Albert Diaz-Guilera,et al.  An algebraic topological method for multimodal brain networks comparisons , 2015, Front. Psychol..

[9]  Yong-Yeol Ahn,et al.  The Flavor Network , 2013, Leonardo.

[10]  Shilpa Chakravartula,et al.  Complex Networks: Structure and Dynamics , 2014 .

[11]  Luis Mateus Rocha,et al.  Distance closures on complex networks , 2013, Network Science.

[12]  Seunghyeon Kim,et al.  Uncovering the Nutritional Landscape of Food , 2014, PloS one.

[13]  Ganesh Bagler,et al.  Analysis of Food Pairing in Regional Cuisines of India , 2015, PloS one.

[14]  Job Ubbink,et al.  The kitchen as laboratory : reflections on the science of food and cooking , 2012 .

[15]  Carey P. McCORD.  THE KITCHEN IS A LABORATORY , 1970 .

[16]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[17]  L Helen,et al.  This is an open access article distributed under the terms of the attached BioMed Central License. See license for details. , 2008 .

[18]  Luis Mateus Rocha,et al.  Semi-metric Networks for Recommender Systems , 2012, 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[19]  George A. Burdock.  Fenaroli's Handbook of flavor ingredients , 2019 .