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.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price includes VAT (USA)
Tax calculation will be finalised during checkout.
Almeida, M. S., & Dal Poz, W. R. (2016). Precise point positioning and relative positioning with GNSS: What most accurate currently? Bulletin of Geodetic Science Curitiba, 22(1), 175–195.
Baio, F. R. R., & Moratelli, R. F. (2011). Auto guidance accuracy evaluation and contrast of the operational field capacity on the mechanized plantation system of sugar cane. Journal of the Brazilian Association of Agricultural Engineering, 31(2), 367–375.
Bragachini, M. E., & Peiretti, J. M. (2008). En la eficiencia de cosecha de maní (On the efficiency of the peanut harvest). Gacetilla de Prensa: 09/2008 março 2008. Retrieved September 3, 2018, from http://www.cosechaypostcosecha.org/data/gacetillas/2008/20080319_mani.asp (in Spanish).
Cappellli, N. L., Umezu, C. K., Silveira, A. C., & Garcia, A. P. (2006). Comparative performance among GPS receivers. Journal of the Brazilian Society of Agroinformatics, 8(1), 63–77.
Cavichioli, F. A., Zerbato, C., Bertonha, R. S., Silva, R. P., & Silva, V. F. A. (2014). Pods losses during the mechanical harvesting of peanuts. Journal of Agrarian Science, 42(3), 211–215.
CONAB. (2017). Monitoring of the Brazilian grain harvest, v.4 Harvest 2016/17-12° data collection, Brasília, pp. 1–158 September 2017. Retrieved September 3, 2018, from http://www.conab.gov.br/OlalaCMS/uploads/arquivos/17_09_12_10_14_36_boletim_graos_setembro_2017.pdf (in Portuguese).
Easterly, D. R., Adamchuk, V. I., Kocher, M. F., & Hoy, R. M. (2010). Using a vision sensor system for performance testing of satellite-based tractor auto-guidance. Computers and Electronics in Agriculture, 72(2), 107–118.
EMBRAPA - Brazilian Agricultural Research Corporation. (2013). Brazilian system of soil classification (3rd ed., p. 353). Brasília: Embrapa.
Holpp, M., Kroulik, M., Kviz, Z., Anken, T., Sauter, M., & Hensel, O. (2013). Large-scale field evaluation of driving performance and ergonomic effects of satellite-based guidance systems. Biosystems Engineering, 116(2), 190–197. https://doi.org/10.1016/j.biosystemseng.2013.07.018.
Ince, A. & Guzel, E. (2003). Effects of gynophore breaking resistance on losses in mechanized peanut harvesting. In G. Quick (Ed.) International conference on crop harvesting and processing, ASAE Publication Number 701P1103e. St Joseph, MI, USA: ASAE.
Keller, J. (2005). Auto-Guidance-System-Effiziente Flächenbearbeitung, Diesel verbrauchsoptimierung, Steigerung der Wirtschaftlichkeit (Efficient surface treatment, diesel consumption optimization, increase in economic efficiency). In: Max-Eyth-Gesellschaft Fur Agrartechnik (Ed.) VDI-Berichte 1868-Landtechnik für Profis (pp. 75–80). Düsseldorf, Germany: VDI Verlag GmbH.
Koppen, W. (1948). Climatologia: Con um estudo de los climas de la Tierra. (Climatology: With a study of the climates of the Earth) México: Fondo de Cultura Economico.
Kroulík, M., Kvíz, Z., Kumhála, F., Hula, J., & Loch, T. (2011). Procedures of soil farming allowing reduction of compaction. Precision Agriculture, 12(3), 317–333.
Leidner, J. (2012). Precision farming payoff in peanuts. Southeastern Peanut Farmer, 50(5), 10–12.
Lipinski, A. J., Markowski, P., Lipinski, S., & Pyra, Paweł. (2016). Precision of tractor operations with soil cultivation implements using manual and automatic steering modes. Biosystems Engineering, 14, 22–28.
Montgomery, D. C. (2009). Design and analysis of experiments (6th ed., pp. 179–268). Hoboken, NJ, USA: Wiley.
Oksanen, T. (2015). Accuracy and performance experiences of four wheel steered autonomous agricultural tractor in sowing operation. In L. Mejias, P. Corke, & J. Roberts (Eds.), Field and service robotics. Springer tracts in advanced robotics (Vol. 105). Switzerland: Springer. https://doi.org/10.1007/978-3-319-07488-7.
Oliveira, T. C., & Molin, J. P. (2011). Use of autopilots on citrus orchards establishment. Journal of the Brazilian Association of Agricultural Engineering, 31(2), 334–342.
Ortiz, B. V., Balkcom, K. B., Duzy, L., Van Santen, E., & Hartzog, D. L. (2013). Evaluation of agronomic and economic benefits of using RTK-GPS-based auto-steer guidance systems for peanut digging operations. Precision Agriculture, 14, 357–375.
Paixão, C. S. S., Santos, A. F., Voltarelli, M. A., Silva, R. P., & Carneiro, F. M. (2017). Times of efficiency and quality of soybean crop mechanical operation in geometry functions of plots. Journal of the Brazilian Association of Agricultural Engineering, 37(1), 106–115. https://doi.org/10.1590/1809-4430-eng.agric.v37n1p106-115/2017.
Perez-Ruiz, M., & Upadhyaya, S. K. (2012). GNSS in precision agricultural operations. In F. B. Elbahhar & A. Rivenq (Eds.), New approach of indoor and outdoor localization systems (pp. 1–24). InTech: London, United Kingdom.
Rizos, C., Janssen, V., Robert, C., & Grinter, T. (2012). PPP versus DGNSS. Geomatic. World, 20, 18–20.
Roberson, G. T. (2009). Planting, harvesting, and curing peanuts. In: D. L. Jordan, R. L. Brandenburg, A. B. Brown, S. G. Bullen, G. T. Roberson, B. Shew & J. F. Spears (Eds.) Peanut information (pp. 131–148). North Carolina Coop. Ext. Series AG-331. Raleigh, NC, USA.
Roberson, G. T., & Jordan, D. L. (2014). RTK-GPS and automatic steering for peanut digging. Applied Engineering in Agriculture, 30(3), 405–409.
Rocha, R. S. M., Jerez, G. O., Brassarote, G. O. N., & Monico, J. F. G. (2017). Assessment of the ionospheric scintillation and different data time intervals effect on the precise point positioning in its on-line versions. Revista Brasileira de Geomática, 5(2), 251–276.
Samohyl, R. W. (2009) Statistical quality control (1st ed.). São Paulo, Brazil: Elsevier: Elsevier Campus. v. 1. ISBN 978-85-352-3220-2.
Santos, A. F., Kazama, E. H., Ormond, A. T. S., Tavares, T. O., & Silva, R. P. (2016a). Quality of mechanized peanut digging in function of the auto guidance. African Journal of Agricultural Research, 11(48), 4894–4901.
Santos, A. F., Silva, R. P., Corrêa, L. N., Borba, M. A. P., & Girio, L. A. S. (2016b) Accuracy and precision monitoring through statistical process control. In: Brazilian Congress of Precision Agriculture-ConBAP, 2016, Goiânia. Anais Goiânia: SBEA, CD-Rom.
Santos, E. P., Silva, R. P., Bertonha, R. S., Noronha, R. H. F., & Zerbato, C. (2013). Productivity and losses in the peanut on five different harvesting dates. Revista Ciência Agronômica, 44(4), 695–702.
Seeber, G. (2003). Satellite geodesy: Foundations, methods and applications (p. 586). Berlin, New York: Walter de Gruyter.
Silva, E. L., & Gervásio, E. S. (1999). The use of TDR for moisture determination in different layers of a dystrophic dusky red latossol. Revista Brasileira Engenharia Agrícola Ambiental, 3(3), 417–420.
Tavares, T. O., Damasceno, A. F., Voltarelli, M. A., Silva, R. P., & Furlani, C. E. A. (2017). Effective power and hourly fuel consumption demanded by set tractor-coffee harvester in function of adequacy tractor ballasting. Journal of the Brazilian Association of Agricultural Engineering, 37(4), 699–708. https://doi.org/10.1590/1809-4430-eng.agric.v37n4p699-708/2017.
Tey, Y. S., & Brindal, M. (2012). Factors influencing the adoption of precision agricultural technologies: A review for policy implications. Precision Agriculture, 13, 713–730. https://doi.org/10.1007/s11119-012-9273-6.
Tiwari, R., Skone, S., Tiwari, S., & Strangeways H. J. (2011). 3WBMod assisted PLL GPS software receiver for mitigating scintillation affect in high latitude region. IEEE. Retrieved September 26, 2018 from, http://www.ursi.org/proceedings/procGA11/ursi/FG-4.pdf.
TRIMBLE RTX. (2017). Retrieved September 03, 2018 from http://www.trimble.com/Positioning-Services/Trimble-RTX.aspx.
USDA. (2018). United States Department of Agriculture. Peanut Area, Yield, and Production. Retrieved June 10, 2018 from http://apps.fas.usda.gov/psdonline/psdreport.aspx?hidReportRetrievalName=BVS&hidReportRetrievalID=918&hidReportRetrievalTemplateID=1.
Vaccaro, G. L. R., Martins, J. C., & Menezes, T. M. (2011). Statistical analysis of the quality of tension levels in electrical energy distribution systems. Production, 21, 539–552. https://doi.org/10.1590/S0103-65132011005000047.
Vellidis, G., Ortiz, B., Beasley, J., Hill, R., Henry, H., & Brannen, H. (2014). Reducing digging losses by using automated steering to plant and invert peanuts. Agronomy, 4, 337–348. https://doi.org/10.3390/agronomy4030337.
Voltarelli, M. A., Silva, R. P., Cassia, M. T., Daloia, J. G. M., & Paixão, C. S. S. (2017). Quality of base cutting in sugarcane using knives of different angles and coatings. Revista Ciência Agronômica, 48(3), 438–447.
Williams, E. J., & Drexler, J. S. (1981). A non-destructive method for determining peanut pod maturity. Peanut Science, 8(2), 134–141.
Zerbato, C., Furlani, C. E. A., Ormond, A. T. S., Gírio, L. A. S., Carneiro, F. M., & Silva, R. P. (2017a). Statistical process control applied to mechanized peanut sowing as a function of soil texture. PLoS ONE, 12(7), e0180399. https://doi.org/10.1371/journal.pone.0180399.
Zerbato, C., Furlani, C. E. A., Silva, R. P., Voltarelli, M. A., & Santos, A. F. (2017b). Statistical control of processes applied for peanut mechanical digging in soil textural classes. Journal of the Brazilian Association of Agricultural Engineering, 37(2), 315–322.
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
Electronic supplementary material
Below is the link to the electronic supplementary material.
About this article
Cite this article
dos Santos, A.F., da Silva, R.P., Zerbato, C. et al. Use of real-time extend GNSS for planting and inverting peanuts. Precision Agric 20, 840–856 (2019). https://doi.org/10.1007/s11119-018-9616-z
- Global navigation satellite system (GNSS)
- Precision point positioning
- Mechanized harvest
- Peanut digging