| Michigan's Saginaw Valley farmers face problems of non-increasing navy bean yields and soil erosion. Many solutions have been proposed to these problems. A need exists for analysis of management strategies in production agriculture. A thorough analysis will hasten the adoption of socially and individually attractive production practices.; A major component of the farm is the machinery complement requirement. A computer model was developed which selects field machinery capable of satisfying the requirement. The model considers seven crops: alfalfa, corn, navy beans, oats, soybeans, sugar beets, and wheat. Labor supply can vary between 1 and 2 full time operators. Machinery technology includes self-propelled combines and four-wheel drive tillage tractors.; Model input includes: farm size, crop rotation, field operation date constraints, labor supply, and available workday data. The number and size of machines to complete all field work within prescribed date constraints is determined. The average annual cost of individual machines and total complement is determined.; The deterministic model uses standard engineering techniques to match machine productivity to available time. Available time is a function of available workday data, workday length, and labor supply. Machine productivity depends upon: assumed available machine sizes, allowable operating speeds, implement draft, and machine efficiencies.; The model is unique in its measure of the risk associated with selected machinery complements. Using actual yearly available workday data, the model selects a machinery set for each year of data. The selected machinery sets are ranked on a cost per hectare basis. Risk issues can be addressed by analyzing the relative rankings of the selected machinery complements.; The model can, if desired, consider one available workday data set. Results show the use of one available workday data set, a statistical grouping of several yearly data sets, to be inferior in its measure of risk when compared to generation of machinery sets for each year of actual data.; Model results show rotations containing alfalfa and/or sugar beets to exhibit the highest machinery costs. Whole farm and sensitivity tests are provided. |
