High-Resolution Melting Analysis of Chloroplast Markers for Species Authentication and Fraud Detection in Commercial Acai and Jucara Products
Magda Delorence LugoniD, Francine Alves Nogueira de AlmeidaiD, Pablo Viana OliveiraiD, Karolinni Bianchi BrittoiD, Pedro Henrique Dias dos SantosiD, Rafaela Campostrini ForzzaiD, Mário Augusto Gonçalves JardimiD, Greiciane Gaburro PanetoiD
Abstract
Authentication of acai products is increasingly important due to the risk of species substitution among morphologically similar Euterpe taxa, with implications for food quality, labeling accuracy, and consumer trust. Despite advances in molecular methods, rapid and cost-effective tools for discriminating closely related Euterpe species in processed commercial matrices remain limited. This study evaluated High-Resolution Melting (HRM) analysis targeting two complementary chloroplast markers -- psbK-I and ycf1b -- as a practical approach for species-level authentication of acai (Euterpe oleracea and E. precatoria) and jucara (E. edulis) products. In silico specificity analysis confirmed that the ycf1b primer pair shows amplification restricted to the Arecaceae family, supporting the analytical robustness of the method. The combined markers enabled reliable differentiation of all target species, including closely related taxa, with a detection limit of approximately 10% in admixed samples. When applied to 50 commercial products, HRM successfully authenticated 46 samples, substantially outperforming DNA sequencing, which was limited by amplification failure and mixed chromatograms. Mislabeling was detected in one acai sorbet and three frozen acai pulps marketed as acai but molecularly identified as E. edulis, constituting a violation of Brazilian food labeling regulations. These findings demonstrate that HRM analysis provides a robust, rapid, and scalable strategy for routine species authentication in processed plant-based matrices, with potential for integration into food quality control workflows and large-scale commercial monitoring programs.
02 /Specification & Classification
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