Response surface methodology combines statistical and mathematical techniques for developing and optimizing processes, creating new products, and improving existing products. It is used particularly where several variables affect the process or the properties of the product, for example temperature, time, pH, and ingredient levels in a thermal process or a fermentation. By running designed experiments and fitting mathematical models to the results, food technologists can map how the variables interact, find the combination that gives the best outcome, and do so with far fewer experimental runs than trial and error.