Abstract: The development of new experimental design and analysis methods that can provide satisfactory formula through conducting as few experiments as possible is extremely important for complex multi-factor and multi-level optimization problem, such as animal and plant nutrition, and fermentation engineering. Based on uniform design and support vector regression, a novel experimental design and analysis method named as UD-SVR for the prescription optimization was proposed. It was applied to optimize the complicated artificial diet including six factors for the cotton bollworm, Helicoverpa armigera （Hübner）. The optimization results showed that the mean pupal weight increased from 0.2436 g in the initial benchmark formulation to 0.3044 g in the optimal prescription after carrying out only 22 schemes. UD-SVR is more efficient than the reference models and has the potential to be widely used for experimental design and analysis of the prescription optimization.

Key words: Helicoverpa armigera, artificial diet, uniform design, support vector regression, prescription optimization