- Agronomic: corn, soybeans
- Farm Business Management: whole farm planning, agricultural finance
- Natural Resources/Environment: biodiversity
The economic benefits of rotational cropping are normally perceived to result from positive yield interactions, reduced inputs, and reduced risk. The objective of this project is to estimate another benefit, that being reduced machine ownership and labor costs when growing crops in combination either in rotations or in simple diversification of continuously grown crops. These benefits have been difficult to quantify previous to recent advancements in securing mixed integer linear programming solutions.
In this project farm returns are maximized for four crop alternatives (corn, soybeans, oats, and alfalfa) or any mix of the four crops. The setting is eastern Nebraska under dryland conditions. In addition to the usual annual cost and returns items, the cost of machine ownership and labor is included in the decision process. While it is recognized that this cost (machine ownership and labor) will vary by cropping system, the quantification of these costs have been difficult to estimate. Here this is accomplished by also including the choice of field machines and labor in the optimizing process and providing a cost for each selected. Omitting machine ownership and labor from consideration in the economics of cropping systems as is commonly done may seriously bias results against diversified and rotational cropping by ignoring system benefits that arise from such crop mixes. The research model of this project includes several field time “windows” during which field operations for any crop must be completed. A large number of field machine alternatives were provided. The benefits of crop diversification arise because smaller machine-labor sets can be used for such multi crop systems compared to larger sets necessary under single crop situations. This occurs because multi crop systems reduce time pressure in the “windows” of field time.
The specific reduced cost results from diversifying crops depend upon farm size and the particular crop mix examined. For example, the highest multi crop benefit was found when soybeans replaced continuous corn on one-half the acreage of a 640 acre farm, with machine ownership, labor, and machine operating costs reduced by 57 dollars per acre (expressed per acre for 640 acres). Machine operating costs were included because these are inseparable from the particular machine set chosen. The reduced cost benefits are less for other crop combinations.
The above benefits were estimated allowing diversified herbicide-tillage methods in combination with diversified cropping. When only diversified cropping under a constant herbicide-tillage system was examined, benefits were reduced but still very significant.
The results were also generalized by crop across a range of rotation systems. This enables machine ownership, labor, and machine operating costs to be estimated for any crop mix from once-estimated relationships. Hence, a model of the detail described above is only needed once to estimate cost relationships and thereafter, cost of machine ownership, labor, and machine operation can be determined for any crop mix.
Cost of machinery ownership and labor for different cropping systems are often termed “fixed” and commonly omitted from budgeted costs for crop systems. However, if these costs are not considered, benefits of diversified farming may be seriously underestimated. The reason is that growing two or more crops together can reduce the necessary machinery and labor compared to growing one crop alone. This can occur because growing only one crop requires high levels of machinery and labor in one or more field time “windows” during which field operations must be completed.
The primary ownership costs under consideration for machinery include depreciation, interest on investment, and repairs. One reason why so little quantification of these costs by crop system has occurred is the difficulty of estimating the most efficient machinery-labor set for any crop or mixes of crops. In recent years, the increased availability of mixed integer linear programming routines allows analysis of such estimates. This model was used in this project.
1. Estimate Machinery Ownership Cost Advantages from Rotational Cropping Systems.
2. Develop Rotation Cost Budgets Utilizing Results from Objective 1.