In continuation of the study of [10] and [5], designs for quadratic regression are considered when the possible values of the controlable variable aremixturesx= (x1,x2, …,xq+ 1) of nonnegative componentsxiwith Σq+ 11xi= I. The “all-boas” design of Box and Draper [1] for guarding against cubic bias, and the design that is optimum with respect to theD-optimality criterion ignoring the posaibility of such bias, are compared in terms of the average and the maximum of the variance and bias functions of the fitted repression. TheD-optimum design performs well in terms of the Box-Draper criterion unless the sample size is fairly large, and is superior in terms of maximum variance and bias.