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The polysaccharides extracted from Strychnos potatorum (SPS) have been applied as an effective pharmacological agent for their anti-diabetic activity, anti-inflammatory effect, and hepato-protective and antioxidant activity. Due to the market demand for peculiar characteristics of these polysaccharides, it has gained greater importance to extract a higher yield of polysaccharides. The present study is focused on the application of response surface methodology (RSM) and artificial neural network (ANN) for the optimization of recovery of polysaccharides from SPS through microwave-assisted extraction (MAE). For RSM, three parameters namely SPS concentration (40 g/L), potassium nitrate concentration (1.5 M), and extraction time (13 min) were considered to produce a maximum yield of polysaccharides (0.88 ± 0.02 g/g). The organoleptic, structural, and thermal properties of extracted polysaccharides through CE …