Deep fat frying of yam slices: optimization of processing conditions using response surface methodology

Abstract

The deep-fat frying of yam slices was investigated with the aim of optimizing the processing conditions. During frying, frying temperature, initial dry matter and frying time have a significant effect on moisture loss and oil uptake. Response surface methodology central composite rotatable design was used to study the effects of the independent variables on quality attributes of yam chips. Breaking force, oil content, moisture content and color parameters were determined. Statistical analysis with response surface regression showed that breaking force, oil and moisture contents and color parameters (L* and a*) were significantly (P < 0.05) correlated with frying temperature, initial dry matter and frying time. The optimum conditions were a frying temperature of 175–180C, using tubers of initial dry matter of 0.179–0.214 kg/kg with a frying time of 4–5 min. It was suggested that the regression equation can be used to estimate the dependent variables for fried yam chips except b* (yellowness) parameter.