Quality of mechanical peanut sowing and digging using autopilot

Cristiano Zerbato,Carlos E A Furlani,Mailson F De Oliveira,Murilo A Voltarelli,Franciele M Carneiro,Tiago De O Tavares

doi:10.1590/1807-1929/agriambi.v23n8p630-637

Abstract

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.

Highlights

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; quality was adversely affected under manual operation
In studies performed in the United States using autopilot for peanut crop, Ortiz et al (2013) and Vellidis et al (2013) found that mechanical peanut digging is performed with high precision, minimizing deviations from the line and providing lower digging losses and higher financial return
Differences in parallelism between the passes of the tractor-sower set were observed among treatments (Table 1) in the sowing operation; when using guidance via autopilot, the spacing between passes was closer to the adjusted, which was 0.90 m

Summary

Introduction

Different methods of Global Navigation Satellite System (GNSS) positioning include real-time kinematic relative positioning (RTK), which enables the quality of positions to be determined in the order of centimeters (Baio & Moratelli 2011).The use of this technology in peanut crop is important due the possibility of reducing parallelism errors at sowing and reducing losses in mechanized harvesting due to the correct alignment of cutting knives and crop lines during the digging process; such losses represent a major problem in peanut crop.In studies performed in the United States using autopilot for peanut crop, Ortiz et al (2013) and Vellidis et al (2013) found that mechanical peanut digging is performed with high precision, minimizing deviations from the line and providing lower digging losses and higher financial return.Studies have demonstrated the economic returns of peanut crop using an automatic targeting system based on RTK correction under different working conditions, such as that performed by Vellidis et al (2014), who evaluated these returns at different curvatures and in different soil preparation systems (Ortiz et al, 2013).technology is less used in Brazilian crops compared with the USA, and there is a lack of knowledge among farmers about the benefits of automatic guidance on sowing and digging operations, which generates high losses.the aim of this study was to evaluate self-steering technology compared with manual steering in mechanized operations for peanut crop, in terms of the quality of these operations through statistical process control. Different methods of Global Navigation Satellite System (GNSS) positioning include real-time kinematic relative positioning (RTK), which enables the quality of positions to be determined in the order of centimeters (Baio & Moratelli 2011). The use of this technology in peanut crop is important due the possibility of reducing parallelism errors at sowing and reducing losses in mechanized harvesting due to the correct alignment of cutting knives and crop lines during the digging process; such losses represent a major problem in peanut crop.

Objectives

Methods

Results