OPTIMIZATION OF ONION COOKIE BAKING PROCESS USING RESPONSE SURFACE METHODOLOGY

Abstract

ABSTRACT Response surface methodology (RSM) was used for the optimization of the baking process of cookies made by substituting onion powders (onion cookie). The experiments were carried out according to a central composite design, selecting onion powder content and baking time as independent variables, and pH, titratable acidity, moisture content, density, spread factor, Commission Internationale de I'Eclairage (CIE) color parameters (L*, a*and b*values), hardness and maximum deflection as response variables. Most polynomial models developed by RSM were highly effective to describe the relationships between the studied factors and the responses. Overall optimization, conducted by overlaying the contour plots under investigation, was able to point out an optimal range of the independent variables within which the eight responses were simultaneously optimized. The point chosen as representative of this optimal area corresponded to onion powder content = 2.5% and baking time = 13.61 min, conditions under which the model predicted pH = 7.10, titratable acidity = 117.08 g acid/100 g, moisture content = 3.21%, spread factor = 6.87, L*value = 71.40, a*value = 0.21, b*value = 31.69 and maximum deflection = 2.62 mm.PRACTICAL APPLICATIONSResponse surface methodology (RSM) was successfully applied to optimize the cookie baking process. Most polynomial models developed by RSM were highly effective to describe the relationships between the studied factors and the responses. This method provided a simple and straightforward optimization analysis for cookie baking, and the results would help to develop a new value‐added functional food containing onion powder, which is readily available and an inexpensive source of antioxidant properties. Onion powder is known to be a better ingredient than onion extract in the formulation of value‐ or function‐added products. The results can be easily implemented to estimate the physicochemical properties when the process parameters are known.