Linking cocoa quality attributes to its origin using geographical indications

Abstract

Cocoa beans are at risk of food fraud and adulteration due to the many steps in the supply chain and the price difference between ‘fine’ and ‘bulk’ cocoa. Consequently, traceability methods for cocoa beans have been intently researched to minimize the impact of fraud and to provide transparency in the supply chain. Multiple methods to identify geographical origin using quality attributes have been assessed, including spectrometry, spectroscopy and sensory studies. This review presents recently published literature that uses specific quality attributes to classify cocoa or chocolate by their geographical origin. The information presented in this paper aims to help guide further development of traceability using geographical quality indications in the supply chain and encourage additional research to build on work using rapid and non-destructive methods. Integrating instrumental and sensory (descriptive and consumer) attributes will help to identify robust, relevant and comprehensive geographical quality indications. There is a need to transition to a more rapid, affordable and non-destructive analytical approach and use advanced data analysis methods to modernize traditional traceability methods. Harmonized methods and authentic samples at different scales (i.e. farms, regions, countries and continents) are needed to produce robust geographical indications to establish cocoa terroir effectively.