Farm accountancy data network normally serves two objectives: estimating the national agricultural income and providing detailed data at production branch level. This study proposes a new sampling design with two independent samples A and B each addressing one of these objectives. The design is based on stratified sampling along with a combination of optimal and power allocation. Violations of precision targets will be avoided by the collapsing of strata. We assess the accuracy of key structural and economic variables by means of a Monte Carlo simulation. Multiple linear regression has been shown to be a powerful tool for imputing financial data to individual census farms. The results illustrate that the proposed design meets prescribed precision and feasibility restrictions at both the single-strata and national levels. It is further demonstrated that unifying samples A and B helps to significantly reduce the survey costs.