Stable isotope profiling and machine learning for determining cocoa origin, ingredient composition, and cocoa content in Brazilian chocolates.
Journal:
Food chemistry
Published Date:
Nov 27, 2025
Abstract
Chocolate is a versatile product with flavours ranging from sweet to bitter. Cocoa, from a C3-photosynthetic plant, is its main raw material, while sugar from sugarcane (C4-metabolism) is commonly used. We analyzed the δ13C and δ15N composition of Brazilian chocolates, including Conventional, Bean-to-bar, and Imported brands across White, Milk, Semisweet, Dark <70 %, and Dark ≥70 % versions. Conventional White, Milk, and Semisweet chocolates showed no significant isotopic differences, with average δ13C values around -22 ‰, indicating high C4-derived ingredient content. Bean-to-bar chocolates presented δ13C values 2-3 ‰ lower, and those made with Amazon cocoa were ∼1.5 ‰ lighter than those from Atlantic Forest, enabling accurate prediction of cocoa origin. Imported chocolates showed even lighter δ13C values, suggesting greater use of C3-based ingredients. δ13C and δ15N values also enabled reliable estimation of cocoa content. These findings demonstrate that stable isotope analysis is a rapid, secure, and effective tool for determining composition, origin, and authenticity in chocolate.
