Authors :
Katikala Johannas Meela; Kasula Hari Chandana; Dr. R. K. Selvakumar
Volume/Issue :
Volume 8 - 2023, Issue 8 - August
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/3ukt69vw
DOI :
https://doi.org/10.5281/zenodo.8340864
Abstract :
Data Science has emerged as a potent tool in a
wide range of industries, including the culinary arts. This
paper examines the role of data science in the culinary
arts and how it is transforming how we approach food.
Data Science is revolutionizing the food industry by
empowering chefs, restaurants, and food enthusiasts to
make data-driven decisions, inspire creativity, increase
efficiency in operation, and design distinctive dining
experiences. These capabilities are made possible by
leveraging data analytics, machine learning, and pattern
recognition. The main uses of data science in the culinary
arts are outlined in this paper, including menu
optimization, ingredient analysis, recipe suggestion
systems, food safety monitoring, and consumer behavior
analysis. We address potential advantages, difficulties,
and directions of integrating data science into culinary
practices, stressing the chances for innovation and
development in this always changing industry. All of these
observations are made through the use of genetic
algorithm.
Keywords :
Culinary Arts, Recipes, Ingredients, Flavour, Optimization, Chefs, Machine Laerning ,Genetic Algorithm.
Data Science has emerged as a potent tool in a
wide range of industries, including the culinary arts. This
paper examines the role of data science in the culinary
arts and how it is transforming how we approach food.
Data Science is revolutionizing the food industry by
empowering chefs, restaurants, and food enthusiasts to
make data-driven decisions, inspire creativity, increase
efficiency in operation, and design distinctive dining
experiences. These capabilities are made possible by
leveraging data analytics, machine learning, and pattern
recognition. The main uses of data science in the culinary
arts are outlined in this paper, including menu
optimization, ingredient analysis, recipe suggestion
systems, food safety monitoring, and consumer behavior
analysis. We address potential advantages, difficulties,
and directions of integrating data science into culinary
practices, stressing the chances for innovation and
development in this always changing industry. All of these
observations are made through the use of genetic
algorithm.
Keywords :
Culinary Arts, Recipes, Ingredients, Flavour, Optimization, Chefs, Machine Laerning ,Genetic Algorithm.