Epsilon Archive for Student Projects

Abstract

Evaluation of machinery costs is necessary for selecting appropriate farm machinery. Timeliness cost due to untimely operations is an important component of machinery costs. Timeliness costs can be high for crop sprayers, since pesticide application must be carried out within a short time interval.

This Master thesis investigated the timeliness cost and the probability of a suitable workday for spraying. Timeliness factors were estimated for four different crops (oats, spring wheat, winter wheat and barley) using historical weed trial data. Workday probability was estimated using weather data, including temperature, rain, air humidity and wind speed, from four different meteorological stations in Sweden. Ownership and operating costs were also calculated. The optimum sprayer capacity for a specific situation was then calculated for each crop. In addition, the effects of variations in grain price, crop yield and workday probability on optimum sprayer capacity and total costs were studied.

The timeliness factor was estimated to be 0.0150 relative yield loss days-1 for oats, 0.0059 relative yield loss days-1 for barley, 0.0049 relative yield loss days-1 for winter wheat and 0.0035 relative yield loss days-1 for spring wheat. The workday probability for spraying was lower than the estimated probabilities for other operations such as tillage, sowing or harvesting. The average workday probability for spraying was estimated to be 0.36 for winter crops and 0.39 for spring crops.

The calculations showed that timeliness costs are an important component of total costs, of similar magnitude to machinery costs. Total costs decreased with increasing sprayer capacity up to a certain limit (optimum capacity) at which total costs were at a minimum. Above this point, total costs for higher capacities began to increase.

Analyses of variations in parameters such as grain price, crop yield and workday probability showed that optimum capacity and total costs varied to a higher degree with varying weather conditions.