A FIELD MACHINERY SELECTION MODEL FOR WHEAT PRODUCERS IN THE ANDES PRE-CORDILLERA OF SOUTH CENTRAL CHILE

Chile's most important crop is wheat, which with other small grain cereals account for 80% of the area planted with annual crops. However, the area seeded yearly with wheat has been experiencing a steady decline. It has gone down from 780,000 hectares in 1966 to 546,000 hectares in 1980. Wheat output has fallen to less than 40% of domestic usage versus 75% a decade ago.; Wheat production costs in Chile are heavily influenced by the cost of owning and operating agricultural machinery. It has been estimated that the agricultural machinery cost component can vary between 30 to 36% of the total wheat production cost. Crop rotations and tillage intensity have important effects upon machinery system requirements and, consequently, production costs.; This research project focused on the development of a computer model to aid the selection of machinery systems for wheat producers in Chile, evaluating the effects of crop rotations and tillage systems upon machinery requirements and machinery related production costs. A systems analysis approach was used as the analytical and problem solving technique. Field work was carried out in Chile in order to collect agrometeorological, agronomic, economic and agricultural engineering data to develop the computer model. Model validation was conducted with data collected through field surveys carried out at the farm level.; The most important conclusions derived from the survey of wheat producers and the computer simulation analysis were as follows:; The large majority of farmers (85%) owned one (60%) or two (25%) two-wheel drive tractors. A very good correlation (r = 0.95) was found between the yearly seeded area and the total power available on the farm. The individual tractor power range was found to vary from 37.3 to 73.1 PTO-kW, with an average power per unit cultivated area of 0.55 kW/ha.; Computer predictions of days suitable for fieldwork at the 0.70 probability were matched very closely by the results from the farmer's survey. For 10 of the 12 biweekly periods the 0.70 design probability values were found to be within 10% of the farmers' estimates, with a correlation coefficient r = 0.91.; Ownership cost was consistently the largest of the system cost components, with values ranging from 41 to 36% (75 to 45% for the harvester) of the total system cost. . . . (Author's abstract exceeds stipulated maximum length. Discontinued here with permission of author.) UMI...