Metabolomics and Peptidomics in Cocoa: Scientometric Analysis and Systematic Review of Flavor-Related Chemical Compounds in Postharvest Transformation

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Authors: Martha Eugenia Londoño Zuluaga, Margareth Santander, Sebastian Escobar, Fabrice Vaillant
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Abstract

This paper provides a systematic review of research on metabolomics and peptidomics in cocoa, focusing particularly on compounds that influence flavor formation during postharvest processing. Special emphasis is placed on peptides and carbohydrates, which play a critical role in flavor quality. The systematic review involved searching the Scopus and Web of Science databases using equations, followed by merging the results into a unified dataset. A scientometrics analysis was conducted to evaluate scientific productivity across various parameters. Theoretical insights were illustrated using the Tree of Science framework to clarify core contributions. Key findings highlight that omics methodologies are pivotal for understanding the cocoa metabolome and peptidome, contributing to the establishment of robust databases of flavor precursors. Nevertheless, further research is necessary to identify specific metabolites that directly influence sensory attributes and to determine essential metabolites and optimal conditions for the development of high-quality products. Moreover, evaluating how postharvest and agro-industrial processing conditions affect quality biomarker modulation in order to maintain consistent sensory quality. This review uniquely contributes by introducing the innovative application of the Tree of Science methodology to cocoa research, offering a structured scientometric perspective on the evolution and emerging trends in cocoa metabolomics and peptidomics. Furthermore, the analysis of key flavor-related metabolites presented here serves as a valuable resource for optimizing cocoa flavor quality through targeted postharvest interventions.

Fields of Study & Subjects

Food Chemistry and Fat Analysis Coconut Research and Applications Botanical Research and Applications

Publication details

Journal / source
Journal of Scientometric Research
Volume
14
Issue
3
Pages
716–731
Publication date
3 January 2026
Language
EN