Quality of mechanical peanut sowing and digging using autopilot

Abstract

Over the past decade, automatic guidance of agricultural machinery via Global Navigation Satellite System (GNSS) signals has been increasingly adopted by the farming community. Peanut farmers are adopting such technology in order to improve the parallelism of operations to address difficulties that occur in mechanical digging, where losses are a big problem. This study aimed to evaluate mechanized operations of peanut sowing and digging controlled manually and by autopilot, along with their quality. The treatments consisted of two digging operations, with and without autopilot, and two displacement speeds (4.5 and 6.0 km h(-1)). The experiment was conducted in a medium-textured soil in a completely randomized design arranged in bands, using the analyzed variables as quality indicators. At sowing, parallelism between passes of the tractor-sower set, was evaluated at 120 points of each system (manual and automatic routing). The digging losses were evaluated in the two guidance systems, under two displacement speeds (4.5 to 6.0 km h(-1)) at 15 points per treatment. It was verified that the parallelism between the passes of the tractor-sower set was better when using the autopilot, which improved the operation quality. Displacement speed did not influence the digging loss. There were no differences in the visible digging loss, but higher quality was obtained when the operation was performed using autopilot. Minor invisible and total digging losses were obtained when the digging was performed with automatic routing, and superior quality was found at a speed of 4.5 km h(-1); however, quality was adversely affected under manual operation. Thus, the use of autopilot is effective for improving the accuracy and the quality of the operations.