Backbone of the flavor network by Nathan Yau at FlowingData.
From the post:
Food flavors across cultures and geography vary a lot. Some cuisines use a lot of scallion and ginger, whereas another might use a lot of onion and butter. Then again, everyone seems to use garlic. Yong-Yeol Ahn, et al. took a closer look at what makes food taste different, breaking ingredients into flavor compounds and examining what the ingredients had in common. A flavor network was the result:
Each node denotes an ingredient, the node color indicates food category, and node size reflects the ingredient prevalence in recipes. Two ingredients are connected if they share a significant number of flavor compounds, link thickness representing the number of shared compounds between the two ingredients. Adjacent links are bundled to reduce the clutter.
Mushrooms and liver are on the edges, out on their lonesome.
You really need to see the graph/network with the post.
I am not ready to throw over my Julia Child’s cookbook in favor of using it to create recipes but it is an impressive piece of work.
Certainly could figure into being data that is merged into a recipe topic map to explain (possibly) substitutions or possible substitutions of ingredients.
Any foodies in the house?