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

Página do item simplificado
dc.contributor.authorSantos, Adao Felipe dos [UNESP]
dc.contributor.authorSilva, Rouverson Pereira da [UNESP]
dc.contributor.authorZerbato, Cristiano [UNESP]
dc.contributor.authorMenezes, Patricia Candida de [UNESP]
dc.contributor.authorKazama, Elizabeth Haruna [UNESP]
dc.contributor.authorStrini Paixao, Carla Segato [UNESP]
dc.contributor.authorVoltarelli, Murilo Aparecido
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.date.accessioned2019-10-06T05:28:55Z
dc.date.available2019-10-06T05:28:55Z
dc.date.issued2019-08-01
dc.description.abstractAmong 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.en
dc.description.affiliationSao Paulo State Univ, Dept Agr Engn, Via Access Prof Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP, Brazil
dc.description.affiliationUniv Fed Sao Carlos, Lagoa Sino Campus,Highway SP-189, BR-18290000 Buri, SP, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Agr Engn, Via Access Prof Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP, Brazil
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipIdCAPES: 001
dc.format.extent840-856
dc.identifierhttp://dx.doi.org/10.1007/s11119-018-9616-z
dc.identifier.citationPrecision Agriculture. Dordrecht: Springer, v. 20, n. 4, p. 840-856, 2019.
dc.identifier.doi10.1007/s11119-018-9616-z
dc.identifier.issn1385-2256
dc.identifier.urihttp://hdl.handle.net/11449/186796
dc.identifier.wosWOS:000475571300011
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofPrecision Agriculture
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectGlobal navigation satellite system (GNSS)
dc.subjectPrecision point positioning
dc.subjectMechanized harvest
dc.subjectPeanut digging
dc.titleUse of real-time extend GNSS for planting and inverting peanutsen
dc.typeArtigo
dcterms.licensehttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dcterms.rightsHolderSpringer

Arquivos

Coleções

Artigos - Engenharia Rural - FCAV