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Precision Agriculture

, Volume 20, Issue 4, pp 840–856 | Cite as

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

  • Adão Felipe dos SantosEmail author
  • Rouverson Pereira da Silva
  • Cristiano Zerbato
  • Patricia Candida de Menezes
  • Elizabeth Haruna Kazama
  • Carla Segato Strini Paixão
  • Murilo Aparecido Voltarelli
Article

Abstract

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 100 m 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 (< 38 mm, 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.

Keywords

Global navigation satellite system (GNSS) Precision point positioning Mechanized harvest Peanut digging 

Notes

Acknowledgements

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

Supplementary material

11119_2018_9616_MOESM1_ESM.pdf (84 kb)
Electronic supplementary material 1 (PDF 84 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Adão Felipe dos Santos
    • 1
    Email author
  • Rouverson Pereira da Silva
    • 1
  • Cristiano Zerbato
    • 1
  • Patricia Candida de Menezes
    • 1
  • Elizabeth Haruna Kazama
    • 1
  • Carla Segato Strini Paixão
    • 1
  • Murilo Aparecido Voltarelli
    • 2
  1. 1.Department of Agricultural EngineeringSão Paulo State UniversityJaboticabalBrazil
  2. 2.Federal University of São Carlos, Lagoa do Sino CampusBuriBrazil

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