GC–MS-based metabolomics reveals biochemical differentiation of sugarloaf pineapples from Benin and Ghana

Abstract

The pineapple (Ananas comosus (L.) Merr.) sector plays a vital role in West Africa, yet the biochemical determinants of quality variation between production origins remain poorly characterised. This study compared the GC-MS-based metabolomic profiles of sugarloaf pineapples from Benin and Ghana to identify biochemical markers linked to typicity and commercial quality. Non-certified fruits from four major production areas were analysed, and data were processed through Principal Component Analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) using MetaboAnalyst 5.0 and mixOmics. Among 469 detected metabolites, 154 were retained after quality filtering, and 12 were identified as discriminant (Variable Importance in Projection VIP > 1, adjusted p-value p-adj < 0.05, and log₂ fold change (log₂FC)| > 1). Beninese pineapples showed higher levels of sucrose, fructose, sorbitol, myo-inositol, malic acid, and serotonin, reflecting a carbohydrate-rich metabolic profile associated with sweetness and a softer texture. By contrast, Ghanaian samples exhibited elevated galacturonic, citric, shikimic, ascorbic, and ferulic acids, indicating enhanced acidity, firmness, and antioxidant potential. These metabolic contrasts reflect agroecological and fertilisation differences (N/K/Ca) influencing biochemical pathways. Model validation (R²Y = 0.81; Q² = 0.57; CV-ANOVA p = 0.003) confirmed the reliability of group discrimination. This integrative metabolomic framework provides a foundation for objective quality assessment and traceability improvement in West African pineapples.