Document Type


Publication Date



Agricultural Economics Department

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farm labor, farm machinery


There has been a need for information on rates of performance of farm labor, power, and machinery for crop operations in east central South Dakota. Such information is of vital importance in computing cost for farm planning and budgeting. While there had been some studies on rates of performance in other states, the results were not applicable to South Dakota. Different methods had been used in making these surveys, with the interview method based on farm records and farmers' estimates being the most frequent. A study made in 1950 in the proposed Oahe irrigation area was considered inadequate for determining rates of performance because of many inconsistencies. The data presented here were based on a survey made in 1951. In making the survey, farmers were contacted and different field operations were timed for a period of 1 hour. Two hundred five schedules were taken in the proposed Oahe irrigation area of 1950. The data were tabulated and an equation developed by Burdick was used in calculating the rates of performance for different machines on different farming operations. These rates of performance were used in figuring labor, power, and fuel requirements for small grain and row crops on a per acre basis, with estimates made for irrigated as well as dryland conditions. When the size of tractor and machine was held constant, it was found that speed and size of field were the two most influential factors in determining rates of performance. As the length of the field decreased, rates of performance decreased. The rate of travel was the most important factor in influencing rates of performance. In comparing requirements for raising comparable crops on dryland and irrigated land, it was found that it takes about three times as many man-hours to produce the crop under irrigation as it does to produce it on dryland. South Dakota agriculture is changing rapidly and as a result there will be some need for adjustments in the data as here presented. But since the data are presented in physical terms, they can be used with any level of prices in computing costs.










South Dakota State State College of Agriculture and Mechanic Arts, Agricultural Experiment Station