Extraction Optimization for Vitex negundo and Cassia tora: A Quantitative Study

This dataset presents a comparative analysis of solvent extraction yields from two medicinally significant plants: Vitex negundo and Cassia tora. Both species are widely recognized in ethnomedicine for their anti-inflammatory, antimicrobial, and hepatoprotective properties. The study employed four solvents (methanol, chloroform, petroleum ether, and distilled water) to evaluate extraction efficiency from 10 g samples of dried plant material. For Vitex negundo, methanol yielded the highest extract (1.684 g; 16.84%), followed by distilled water (1.264 g; 12.64%), chloroform (0.663 g; 6.63%), and petroleum ether (0.409 g; 4.09%). In contrast, Cassia tora demonstrated a markedly higher yield with petroleum ether (1.802 g; 18.02%), followed by solvent (2.283 g; 22.83%), methanol (0.975 g; 9.75%), and chloroform (0.645 g; 6.45%). The dataset highlights solvent-dependent variability in phytochemical extraction, underscoring the importance of polarity and solubility in determining yield. Methanol, a polar protic solvent, proved most effective for Vitex negundo, suggesting the predominance of polar phytoconstituents such as flavonoids and glycosides. Conversely, Cassia tora exhibited higher extraction with petroleum ether, indicating the presence of non-polar compounds such as fatty acids, sterols, and terpenoids. Biostatistical analysis was performed using descriptive statistics, correlation matrices, regression analysis, ANOVA, and t-test to assess solvent efficiency and inter-species variability. The findings reveal significant differences (p < 0.05) between solvent yields, with methanol and petroleum ether showing the strongest extraction potential across species. This dataset provides reproducible evidence for solvent selection in phytochemical research, offering insights into optimizing extraction protocols for medicinal plant studies. It is intended to support pharmacognosy, phytochemistry, and natural product research communities by providing structured, quantitative data for comparative analysis.