For the parametric strict-feedback nonlinear systems in the literature, as the number/dimension of the system parameters increases, a large number of adaptive laws must be designed, which sharply consumes the available computational resource. Hence, reducing the number of parameters to be estimated is one of the effective ways for handling such problem. In this paper, a single-parameter-estimation based robust adaptive control scheme is proposed for a class of parametric strict-feedback nonlinear systems. By giving the concept of the maximum value of the norm of the system parameters and estimating such scalar constant (rather than the system parameters themselves), the developed control ensures that only one parameter needs to be updated online, making the control implementation inexpensive in computation. A simulation example is presented to demonstrate the effectiveness of the proposed scheme.