Systems and methods for scheduling alimentary combinations

A method of scheduling alimentary combinations, the method comprising:

• providing, by a computing device, an alimentary instruction set including a plurality of target nutrient quantities corresponding to a plurality of scheduled meals, wherein providing the alimentary instruction set further comprises:
• receiving a training data comprising a plurality of biological extractions each correlated to a respective target nutrient quantity;
• recording at least a biological extraction input from a user device;
• training a machine-learning model using the training data such that the trained machine-learning model is configured to receive the at least a biological extraction as an input and output at least a target nutrient quantity;
• inputting the biological extraction input to the trained machine-learning model;
• generating the at least a target nutrient quantity as a function of the biological extraction input and the trained machine-learning model;
• and
• generating the alimentary instruction output set as a function of the at least a target nutrient quantity;
• determining, by the computing device, a per-meal alimentary instruction set as a function of the plurality of target nutrient quantities;
• receiving, by the computing device, from each alimentary provider device of a plurality of alimentary provider devices, a plurality of provider ingredient combinations;
• generating, by the computing device, a ranked list of provider ingredient combinations as a function of the plurality of provider ingredient combinations, wherein generating further comprises:
• determining a nutrient listing corresponding to each provider ingredient combination of the plurality of provider ingredient combinations;
• creating a distance metric from each nutrient listing to the per-meal alimentary instruction set, and selecting at least a nutrient listing that minimizes the distance metric;
• generating the ranked list from the plurality of provider ingredient combinations;
• and
• ranking the plurality of provider ingredient combinations within the ranked list to minimize the distance metric;
• receiving, by the computing device from the user device, a user selection of a provider ingredient combination corresponding to a meal of the plurality of scheduled meals and at least a goal parameter;
• and
• generating, by the computing device, a modified ranked list of ingredient combinations as a function of the user selection and the alimentary instruction set.