Abstract: Based on experimental error theory, the objective of regression design is to improve fitness of equation through enlarging the determination of error type information matrix A and thus reduce model error on basis of classification of error types and degree of freedom, which is independent of random error. Whether the significant difference of regression equation in fitness can be tested is dependent on residual degree of freedom. Saturated D-optimal design has the maximum determinant of information matrix A. Under the given regression model and number of replication, there was a minimum number of treatments in the experiment of Saturated D-optimal design which is characterized of optimization. Agricultural application of modern regression design was discussed in combination with properties of fertilizer field experiment.