Use of real-time extend GNSS for planting and inverting peanuts

• Autor(a) principal: Santos, Adao Felipe dos [UNESP]
• Data de Publicação: 2019
• Outros Autores: Silva, Rouverson Pereira da [UNESP], Zerbato, Cristiano [UNESP], Menezes, Patricia Candida de [UNESP], Kazama, Elizabeth Haruna [UNESP], Strini Paixao, Carla Segato [UNESP], Voltarelli, Murilo Aparecido
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1007/s11119-018-9616-z; http://hdl.handle.net/11449/186796
• topic: Global navigation satellite system (GNSS); Precision point positioning; Mechanized harvest; Peanut digging

Among the main techniques employed in precision agriculture, yield mapping and automatic guidance of agricultural machines are the best-known to farmers. The objective of this study was to evaluate, using statistical process control tools, the quality of automatic guidance using satellite signals, to reduce positioning errors and losses in peanut digging. The treatments consisted of the use of manual (operator guidance) and automatic (autopilot) guidance with RTX satellite signals in sowing and digging operations. The quality of the operation was evaluated after collection of 30 points spaced at 100m for each quality indicator, which are the losses and the errors of alignment of the mechanised sets in sowing and digging operations. From the perspective of statistical control, manual guidance was shown to be compromised for the quality indicators of digging losses. Despite the instability in the sowing and digging operations, the use of automatic guidance proved to be accurate. The use of automatic guidance increases the precision and reduces overlaps (<38mm, as stipulated by the supplier) for sowing and digging. The manual sowing mean error between overlaps was stable; however, it did not remain constant over time.