Response Surface Methodology for Optimizing and Simulating the Extraction of Anti- Diabetic Compounds from Cucumis Sativus

Abstract

The growing prevalence of diabetes mellitus has intensified the search for effective,
plant-based therapeutic agents with minimal side effects. Cucumis Sativus
(commonly known as cucumber) has been recognized for its potential anti-diabetic
properties, attributed to its rich phytochemical profile. This study aims to optimize
and simulate the extraction process of anti-diabetic compounds from Cucumis
Sativus using Response Surface Methodology (RSM), a statistical and
mathematical tool effective for modeling and analyzing problems where multiple
variables influence the desired outcome. In the literature, experimental data were
fitted to a second-order polynomial regression model, and the model's adequacy
was confirmed through with a high R² value indicating a strong predictive
reliability. A Central Composite Design (CCD) was employed to systematically
evaluate the influence of four independent variables; extraction temperature (°C),
extraction incubation-time (minutes), agitation speed (rpm), and volume of solvent
(mL) on the yield of bioactive compounds exhibiting