Selecting optimum crop rotation

Graduation date: 1985The crop rotation decision is important to farmers because of its\ud impact on profitability, financing and risk exposure. This thesis\ud addresses the problem of farm level crop rotation selection under perfect\ud and imperfect knowledge of prices, yields and costs. The problem\ud is addressed by first estimating production functions for irrigated\ud wheat, corn, potatoes, and alfalfa in terms of annual weather; crop\ud variety; planting and harvesting date; and specific rotation. Subsequently,\ud these equations are used to construct estimates of the gross\ud margins for crop rotation activities. The study then proceeds to select\ud optimum crop rotations and proportions of land resources allocated\ud to each. The major criteria influencing the selection of optimum farm\ud crop rotation are profit maximization and risk avoidance. On the basis\ud of the two criteria, two empirical equilibrium one year linear programming\ud models are built. The first model includes cropping activities in\ud which the return depends on the preceding crops and on acreage constraints;\ud risk factors are disregarded. The second model adds risk\ud feature to the first model. Given various degrees of risk aversion,\ud the model provides a series of efficient farm crop rotation plans and\ud calculates their expected gross margins (profits) and standard deviations.\ud The empirical results obtained from this study indicate the importance\ud of risk consideration in improving the model predictive performance.\ud The model performs successfully in selecting crop rotations\ud comparable to the rotations practiced on the case farm when adequate\ud agronomic and risk considerations are introduced in the analysis. In\ud addition, the results show that less profitable crops such as corn and\ud alfalfa will be included in rotations if their presence exhibits a\ud positive influence on subsequent crops.\ud Two important areas among others need more attention in order to\ud obtain more applicable results. First, incorporation of the unexplained\ud variation In the risk estimation procedures to improve the predictive\ud performance of the model, Second, extension of the model to include\ud input risk, Inflation, cash flow, more resource constraints such\ud labor and capital within the developed framework may have noticeable\ud Impact on optimal crop rotation selection