Abstract

An artificial intelligence model receives a FTIR spectrum of a given ingredient to predict its protein secondary structure. The model includes three artificial modules, which generate three predicted values corresponding to structural categories (e.g., α-helix, β-sheet, and other) of the predicted secondary structure. Proteins may be compared for similarity based on predicted values corresponding to the structural categories of the predicted secondary structure.