Unveiling the carbohydrates profile of anti-diabetic medicinal plants by a developed and validated high-performance liquid chromatography coupled with refractive index detector (HPLC-RID)

Naturally occurring carbohydrates play a crucial role in the food nutritional and medicinal properties of plants. However, measuring these sugars in common herbal products is still not well established, especially for those intended for diabetic patients. The sugar content in these products directly impacts their safety, effectiveness, and authenticity. This study presents a straightforward isocratic high -performance liquid chromatography (HPLC) method with a refractive index (RI) detector. It allows for the simultaneous identification and measurement of seven sugars: d -(−)-Ribose, d -(+)-Xylose, d -(−)-Fructose, d -(+)-Glucose, Sucrose, d -(+)-Maltose, and α-Lactose. This method was applied for the determination of sugar content in aqueous extracts from Stevia rebaudiana (ST) (leaves) , Glycyrrhiza glabra (GG) (roots) , Withania somnifera (WS) (roots) , Gymnema sylvestre (GS) (leaves), Adhatoda Vasica Nees. (AV) (leaves), Emblica officinalis (EO) (fruit), Azadirachta indica A. (AI) (leaves), Alstonia scholaris (L.) (AS) (bark), Aegle marmelos (L.) (AM) (bark), Aloe barbadensis Mill. (ALV) (leaves pulp). We developed a method based on an ACE Excel 5 NH 2 column using an acetonitrile–water (85:15, v/v) mobile phase at a flow rate of 1.0 mL/min and a detection temperature of 35 °C. The method requires no derivatization and allows for direct analysis in aqueous samples. We followed ICH Q2 (R1) guidelines during the validation process. This confirmed excellent linearity, sensitivity (LOD/LOQ), accuracy, precision, specificity, and robustness. We extracted plant materials from several batches (n = 5 per species) using extraction with water at 80 °C hot aqueous extraction for 2 h followed by room temperature maceration for 24 h and then lyophilization, ensuring consistent results across different harvests. Our approach provided reliable sugar profiling among different medicinal plant species, showing variations between batches, and creating a solid dataset for quality control and authentication. This work is unique because it combines a universal, non-destructive RI-based detection system with an isocratic flow for which most of published work is unable to establish at HPLC-RI platform. It enables multi-sugar profiling in medicinal plants without needing derivatization or complex sample preparation. The method’s simplicity and reliability make it a practical tool for routine quality checks of herbal products, especially those aimed at managing blood sugar levels. Undetected adulteration of sugar could affect therapeutic goals.