Computational Nutrition: A Method of Generating Food List to Meet Nutritional Requirements

Many models that are used to generate a meal plan only take proximates into account. The human body requires a mixture of proximates in addition to several macronutrients, micronutrients, and various vitamins and minerals. Furthermore, the models designed to generate these meal plans do not take into account the individual’s specific nutritional needs. These various requirements have some combination of lower bound amount (LBA), ideal amount (IA), and upper bound amount (UBA) necessary for the human body to thrive. The aim of this project was to generate a list of food items using a backtracking algorithm that will meet the specific nutritional requirements as defined by the input. Each nutrient receives a score based on the amount of nutrient contained in the food list in relation to the LBA, IA, and UBA. These scores are aggregated to give the meal plan an overall score