Avaliação da eficiência de diferentes operações agrícolas utilizando técnicas de agricultura de precisão

Abstract

The aim of this study was to evaluate the operational capacity and efficiency of two agricultural operations utilizing GPS and software programs as evaluation tools. The operations analyzed were of soybean harvest, carried out with a Massey Ferguson MF34 combine harvester and of variable rate fertilizer application, carried out with a MF 5310 tractor and Amazone 1500 centrifuge distributor. The areas are located in the region of Não-Me-Toque, in the state of Rio Grande do Sul, South of Brazil. A GPS navigator, attached to the combine and tractor was utilized for data collection. The following data were collected and georeferenced: trajectory of the machines in operation, work speed, distance travelled, start and finish times, maneuver, unload and reload times, and altitude. The analysis, storage and processing of these data was supported by the following software: GPS TrackMaker® (trajectory, speed, distance and times), SGIS® (productivity maps), CR Campeiro 6.0 (speed and altitude maps) and Microsoft Office ExcelTM (data processing). The equations to determine operational efficiency was in accordance with Mialhe, except that the data were obtained by GPS. Besides determining capacity and operational efficiency, route efficiency was also determined and compared with trajectory efficiency, proposed in this study, in which the main information utilized is the distance travelled. Trajectory efficiency proved to be the most real information for areas with irregular shapes. Operational efficiency of the harvest was 54.13%, considered low when compared to international averages. Even with this low efficiency, the operational capacity of the harvest was of 2.47 ha.h-1. The operational efficiency in the variable rate application, varied between 52.7 and 65.6%, with 58.4% as mean value. This low value was due to the fact that the tractor utilized has a high operational capacity. The operational capacity varied from 12.5 ha.h-1 to 20.6 ha.h-1, with a mean of 17.6 ha.h-1. Altitude maps of the areas were created based on GPS data. Correlations between the different maps were carried out and values of 90% or greater were obtained, in some areas reaching 98.4%.