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Study of Food Pairing Phenomenon, Part I


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Posted by Don, Dueling Bubbas on March 04, 2015 at 15:37:47:

From link below, worth the read:

Data Mining Indian Recipes Reveals New Food Pairing Phenomenon

By studying the network of links between Indian recipes, computer scientists have discovered that the presence of certain spices makes a meal much less likely to contain ingredients with flavors in common.

The food pairing hypothesis is the idea that ingredients that share the same flavors ought to combine well in recipes. For example, the English chef Heston Blumenthal discovered that white chocolate and caviar share many flavors and turn out to be a good combination. Other unusual combinations that seem to confirm the hypothesis include strawberries and peas, asparagus and butter, and chocolate and blue cheese.

But in recent years researchers have begun to question how well this hypothesis holds in different cuisines. For example, food pairing seems to be common in North American and Western European cuisines but absent in cuisines from southern Europe and East Asia.

Today, Anupam Jain and pals at the Indian Institute of Technology Jodhpur say the opposite effect occurs in Indian cuisine. In this part of the world, foods with common flavors are less likely to appear together in the same recipe. And the presence of certain spices make the negative food pairing effect even stronger.

Jain and co began their work by downloading more than 2,500 recipes from an online cooking database called TarlaDalal.com. These recipes come from eight sub-cuisines, including Bengali, Gujarati, Punjabi, and South Indian, which together span vast geographies, climates, and cultures in the Indian subcontinent.

Together, these recipes contain 194 different ingredients. The average recipe contains seven ingredients but some can contain up to 40. In particular, the Mughlai sub-cuisine has many recipes with exceptionally large numbers of ingredients, probably because of its royal heritage.

Jain and co then created a flavor network in which ingredients are linked if they appear together in the same recipe. The network can then be studied for interesting phenomenon such as clustering effects.

The question that the team set out to answer was to what extent food pairing is positive or negative. In other words, do ingredients sharing flavor compounds occur in the same recipe more often than if the ingredients were chosen at random.




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