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Estimating the Nutrient Content of Commercial Foods from their Label Using Numerical Optimization

  • Jieun KimEmail author
  • Mireille Boutin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9281)

Abstract

We propose a method for automatically estimating the amount of a given nutrient contained in a commercial food. The method applies when no part of any ingredient is removed in the preparation process. First, we automatically bound the amount of each ingredient used to prepare the food using the information provided on its label (Ingredient list and Nutrition Facts Label) along with the nutrition information for at least some of the ingredients. Using these bounds (minimum and maximum amount for each ingredient), we obtain an initial set of bounds (minimum and maximum amount) for the nutrient considered. We then utilize the Simplex algorithm to refine these bounds on the nutrient content. Our motivating application is the management of medical diets that require keeping track of certain nutrients such as phenylalanine (Phe) in the case of the inherited metabolic disease phenylketonuria (PKU). To test our method, we used it to estimate the Phe content of 25 commercial foods. In a majority of cases (17 / 25), the bounds obtained were within 10.4mg of each other and thus our method provided a very accurate estimate (\(\pm 5.2\)mg) for the Phe content of the foods.

Keywords

Nutrient Content Simplex Algorithm Food Label Commercial Food Initial Feasible Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Purdue UniversityWest LafayetteUSA

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