Stable isotope profiling and machine learning for determining cocoa origin, ingredient composition, and cocoa content
Karina Gonçalves da Silva1, Marcelo Zacharias Moreira1, Antonio Vargas de Oliveira Figueira2
1Laboratory of Isotope Ecology, Center for Nuclear Energy in Agriculture, University of São Paulo, Av. Centenário, 303, São Dimas, Piracicaba CEP 13416-000, SP, Brazil.
Stable isotope analysis of chocolate reveals ingredient origins and cocoa content. This method accurately distinguishes between C3 and C4 plant sources, identifying chocolate origin and authenticity.
Area of Science:
- Food Science
- Analytical Chemistry
- Agricultural Science
Background:
- Chocolate's flavor profile is influenced by its raw materials: cocoa (C3 plant) and sugar (C4 plant).
- Understanding ingredient sourcing is crucial for product authenticity and quality control in the food industry.
Purpose of the Study:
- To investigate the utility of stable isotope analysis (δ13C and δ15N) in characterizing Brazilian chocolates.
- To determine the origin of cocoa and estimate ingredient composition in various chocolate types.
Main Methods:
- Analysis of δ13C and δ15N stable isotope ratios in Brazilian chocolates (Conventional, Bean-to-bar, Imported).
- Comparison of isotopic signatures across different chocolate types (White, Milk, Semisweet, Dark <70%, Dark ≥70%).
Main Results:
- Conventional chocolates exhibited high C4-derived ingredient content (average δ13C ≈ -22‰).
- Bean-to-bar chocolates showed distinct isotopic signatures, differentiating cocoa origins (Amazon vs. Atlantic Forest).
- Stable isotope analysis reliably estimated cocoa content and determined product authenticity.
Conclusions:
- Stable isotope analysis is a powerful tool for verifying chocolate composition and geographical origin.
- The method provides a rapid, secure, and effective means to ensure chocolate authenticity.
- This technique supports quality control and traceability in the chocolate industry.
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