Cocoa (Theobroma cacao L.) bean colour is a central quality attribute affecting chocolate appearance, consumer acceptance, and market value, yet the mechanistic basis of colour variation across genotypes and processing conditions remains poorly understood. While previous studies have explored fermentation and genotype effects separately, the integrated influence of chemical composition, anthocyanin content, and mineral profiles on cocoa bean pigmentation has not been systematically investigated. This study aimed to elucidate the relationships between cocoa bean colour, biochemical composition, and fermentation across 38 diverse genotypes, including germplasm accessions and cultivated varieties. Colour attributes were quantified using CIELAB parameters (L*, a*, b*, chroma, hue angle), biochemical properties were measured for fat, total phenolics, and essential minerals (phosphorus, sodium, iron, magnesium, calcium), and anthocyanins (cyanidin, delphinidin, pelargonidin, malvidin) were profiled in fermented samples via LCMS. Hierarchical clustering and correlation analyses were employed to link genotype-specific biochemical traits to colour outcomes. Results revealed significant genotype-dependent variation, with EQX78, ARF 22, and MO 20 exhibiting superior colour characteristics, while some genotypes displayed inherently dark brown beans. Germplasm accessions showed optimal colour properties, whereas cultivated varieties had enhanced biochemical content. Fermentation reduced L* and hue angle while increasing a*, b*, and chroma, corresponding to intensified reddish-brown pigmentation, and cyanidin and delphinidin were identified as key anthocyanins driving colour changes. Correlations indicated that fat and mineral contents significantly modulate colour expression, providing mechanistic insights into pigmentation dynamics. These findings highlight the multifactorial nature of cocoa bean colour and establish a foundation for breeding and post-harvest strategies to optimize visual and nutritional quality. Future studies integrating genomics and controlled fermentation are warranted to develop predictive models for cocoa bean colour and to enhance the quality and market value of chocolate products.
S. et al. (Sun,) studied this question.