Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1185906
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dc.contributor.authorTETILA, E. C.
dc.contributor.authorMORAES, P. M. de
dc.contributor.authorTETILA, J. Q. da S.
dc.contributor.authorOLIVEIRA, J. L. de
dc.contributor.authorBARBEDO, J. G. A.
dc.date.accessioned2026-03-30T17:55:14Z-
dc.date.available2026-03-30T17:55:14Z-
dc.date.created2026-03-30
dc.date.issued2025
dc.identifier.citationIn: WORKSHOP CIENTÍFICO DO CENTRO DE CIÊNCIA PARA O DESENVOLVIMENTO EM AGRICULTURA DIGITAL – SEMEAR DIGITAL, 2., 2025, Campinas. Anais [...]. Piracicaba: ESALQ/USP, 2025. p. 137-143.
dc.identifier.isbn978-85-86481-94-9
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1185906-
dc.descriptionAccording to data from the IBGE Agricultural Census, the state of Mato Grosso do Sul has 71,164 economically active properties, of which 43,223 are family farming establishments. The acquisition of agricultural machinery represents one of the main challenges faced by these small-scale producers. In this context, this work aims to evaluate the use of drones for the seeding of pastures, forest species, and cover crops in family farming systems. The study will be conducted in the community of Assentamento Itamarati 1, located in the municipality of Ponta Porã-MS. An 8-hectare agricultural area will be divided into four quadrants of two hectares each. Using the DJI Agras T30 drone, 100,000 seeds per hectare of each crop will be sown, totaling 10 seeds per square meter. The crops will be distributed as follows: 1st quadrant – Brachiaria grass; 2nd quadrant – forest species; 3rd quadrant – pearl millet; and 4th quadrant – sunn hemp. Thirty days after sowing, aerial monitoring will be carried out using a DJI Phantom 4 drone at an altitude of 10 meters, with the aim of generating productivity maps from the images captured during the flight. Using QGIS software, the average emergence rate of each crop (through plant counts) will be evaluated, and the results will be analyzed based on four metrics: Accuracy, Precision, Recall, and F-Measure. It is expected that new agricultural technologies and intelligent systems will become more efficient and sustainable than current food production methods, in addition to creating new opportunities for specialized employment in drone-based seeding, spraying, and map generation.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectSemeadura por drones
dc.subjectTaxa de emergência
dc.subjectAssentamento de Itamarati
dc.subjectProjeto Semear Digital
dc.subjectDrone Seeding
dc.subjectEmergence Rate
dc.subjectFamily Farming
dc.subjectItamarati Settlement
dc.titleEvaluation of drone seeding for pastures, forest species, and cover crops in family farming.
dc.typeArtigo em anais e proceedings
dc.subject.thesagroAgricultura Familiar
dc.description.notesOrganização: Silvia Maria Fonseca Silveira Massruhá, Durval Dourado Neto, Luciana Alvim Santos Romani, Jayme Garcia Arnal Barbedo, Édson Luis Bolfe, Ivan Bergier, Maria Angelica de Andrade Leite, Vitor Del Alamo Guarda, Catarina Barbosa Careta.
riaa.ainfo.id1185906
riaa.ainfo.lastupdate2026-03-30
dc.contributor.institutionEVERTON CASTELÃO TETILA, UNIVERSIDADE FEDERAL DA GRANDE DOURADOS; PAULA MARTIN DE MORAES; JULIANA QUEIROZ DA SILVA TETILA, FACULDADE ANHANGUERA DE DOURADOS; JOSEMAR LOURENÇO DE OLIVEIRA, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; JAYME GARCIA ARNAL BARBEDO, CNPTIA.
Aparece nas coleções:Artigo em anais de congresso (CNPTIA)

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