The economic viability of alternative and more sustainable agriculture farming systems depend on the value of farm profits. These values may be estimated through short or long-run of profit maximization, but there is a difference in these methods. In short-run profit maximization the instantaneous marginal benefits are equated to the marginal costs of production. Where as in the long-run maximization of profits the capital value of soil resources are quantify in addition to the direct revenues and costs of each system over time. A long-run approach is fundamental to capture the value of capital improvements in soil resources. In this study we use short-run experimental data from SAFS's rotations to calibrate the crop simulation model EPIC, and obtain a time series cross-sectional data set for developing the dynamic bioeconomic models. With data from EPIC we are able to expand the existing short-run analysis, to estimate the long-run profitability and ecological benefits of alternative sustainable farming systems in comparison to conventional systems. Profit maximizing farmers who may not adopt sustainable methods based on short-run returns may well adopt them when long-run capital values are included. Finally, when environmental constraints are imposed on agricultural technology, for example to reduce non-point source pollution, results from our bioeconomic models are expected to show that sustainable technologies are more valuable.