Optimization of the boiling process for hydrocyanic acid reduction (HCN) in cassava (Manihot esculenta Crantz) - Mejarito, Ivy Guitan
This study was conducted to optimize the boiling process to reduce the hydrocyanic acid content (HCN)in cassava (Lakan variety) to acceptable levels. Cassava samples were boiled using 13 combinations of boiling time and water-to-cassava ratio with a rotatable, central composite design. Raw and processed cassava samples were analyzed for HCN content using the acid titration method. Different boiling time and water-to-cassava ratio combination of 20-55 min and 1.38-5 mL H2O/g cassava led to HCN values of 33.63-114.54 mgkg wet basis. A linear model (p=0.0036) with the following equation was generated. HCN 162.1085 - (1.8194*)time (7.8851* water-to-cassava ratio) Boiling time (p=0.0023) and water-to-cassava ratio (p=0.0613) were the strong and marginal significant factors affecting the response, respectively. An optimum region with a target HCN content of ≤40 mg kg was bounded by the following boiling time and water-to-cassava ratios 45.44 minutes and 5.62 mL/g, 45.44 minutes and 5 mL/g, 55 minutes and 3.5 mL/g, and 55 minutes and 5.62 mL/g. Actual HCN concentrations of 38.18 and 73.13 mg/kg were found for samples boiled under optimal and non-optimal conditions, respectively. Both values were within the confidence and prediction intervals thereby validating the predicted model. HCN content of samples under optimal conditions conformed to the 40 mg/kg limit but failed to meet the 10 mg/kg and 25 mg/kg limit set for maximum HCN concentration by regulatory bodies. Cassava samples boiled using optimal and non-optimal boiling parameters were rated slightly acceptable in terms of color, aroma, texture, and overall acceptability where no significant difference was xiv found for all sensory attributes between the two treatments. Both boiled samples were described to have a yellow exterior, white interior and a starchy smell. Samples processed from optimal conditions were softer compared to the samples from the non-optimal run.