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'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake

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Published on: September 18, 2018

Computational gastronomy: capturing culinary creativity by making food computable.

Ganesh Bagler^1,2,3, Mansi Goel^4,5,6

¹Department of Computational Biology, Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), Okhla Phase III, New Delhi, 110020, India. bagler@iiitd.ac.in.

NPJ Systems Biology and Applications

|July 8, 2024

Summary

This summary is machine-generated.

Computational Gastronomy uses data-driven methods to analyze recipes for taste, nutrition, health, and sustainability. This approach explores if artificial intelligence can replicate chef creativity to generate novel recipes.

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Area of Science:

Food Science
Computational Science
Artificial Intelligence

Background:

Cooking is a fundamental creative activity with broad impacts on health, culture, and sustainability.
Traditional culinary arts lack systematic analysis, limiting innovation and understanding.
Data-driven approaches are emerging to study complex systems like food.

Purpose of the Study:

To introduce Computational Gastronomy as a novel data-driven paradigm for investigating food and cooking.
To systematically analyze recipes for key attributes including taste, nutrition, health, and environmental impact.
To explore the potential of artificial intelligence in replicating chef creativity and generating innovative recipes.

Main Methods:

Developing a data-driven, systematic, and rule-based approach to understand culinary arts.
Scrutinizing recipes computationally to assess taste, nutritional value, health implications, and carbon footprint.
Investigating the application of artificial intelligence algorithms to capture chef expertise and creativity.

Main Results:

Computational Gastronomy provides a framework for objective analysis of culinary practices.
The study opens possibilities for understanding and enhancing culinary creativity through computation.
AI algorithms show potential for generating novel recipes with optimized profiles.

Conclusions:

Computational Gastronomy offers a new frontier for culinary research and innovation.
Analyzing recipes through computation can lead to improved nutrition, health, and sustainability.
AI has the potential to augment human creativity in the kitchen, leading to unprecedented culinary creations.