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Multispectral images for discrimination of sources and doses of fertilizer in coffee plants

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dc.contributor.author Rezende, Camila Isabel Pereira
dc.contributor.author Assis, Gleice Aparecida de
dc.contributor.author Martins, George Deroco
dc.contributor.author Carvalho, Fábio Janoni
dc.contributor.author Franco, Miguel Henrique Rosa
dc.contributor.author Araújo, Nathalia Oliveira de
dc.date.accessioned 2023-12-06T22:25:41Z
dc.date.available 2023-12-06T22:25:41Z
dc.date.issued 2023-06-16
dc.identifier.citation REZENDE, Camila Isabel Pereira; ASSIS, Gleice Aparecida de; MARTINS, George Deroco; CARVALHO, George Deroco; FRANCO, Miguel Henrique Rosa; ARAÚJO, Nathalia Oliveira de. Multispectral images for discrimination of sources and doses of fertilizer in coffee plants. Revista Ceres, Viçosa, v. 70, n. 3, p. 54-63, 16 june 2023. Available from: https://www.scielo.br/j/rceres/a/cy5Fj3WdTZ3BmHVP3DbrdjG/?lang=en#. Accessed: 30 nov. 2023. pt_BR
dc.identifier.issn 2177-3491
dc.identifier.uri https://doi.org/10.1590/0034-737X202370030006 pt_BR
dc.identifier.uri http://www.sbicafe.ufv.br/handle/123456789/14002
dc.description.abstract Remote monitoring of the management of coffee crops is necessary as the demand in decision-making, where the aim is to rise production based on sustainable management is in a constant growth. In this work, it was evaluated the potential of images obtained by low-cost sensors in the discrimination of sources and doses of mineral and organomineral fertilizers in coffee. The experimental design was in randomized blocks, with five blocks and six treatments, as follows: (T1) - 100% of the organomineral treatment; (T2) - 70% of the organomineral treatment; (T3) - 50% of the organomineral treatment; (T4) - 100% of mineral fertilization; (T5) - standard treatment of the farm and (T6) - 70% of mineral fertilization. After management, we used the Mapir 3 Survey3W camera coupled to an ARP drone – Phantom4 to take images of the experiment over a 12-month vegetative period. Combined with image taking, it was collected agronomic parameters of coffee growth and productivity for two crops and concluded that different fertilization doses did not significantly affect the analyzed parameters. Based on the supervised classification of multispectral images, it was possible to discriminate treatments with a higher degree of accuracy (86.66% accuracy) than when analyzing coffee growth parameters. pt_BR
dc.format pdf pt_BR
dc.language.iso en pt_BR
dc.publisher Universidade Federal de Viçosa pt_BR
dc.relation.ispartofseries Revista Ceres;v. 70, n. 3, p. 54-63, 2023;
dc.rights Open Access pt_BR
dc.subject Coffea arabica L. pt_BR
dc.subject fertilization management pt_BR
dc.subject low-cost remote monitoring pt_BR
dc.subject treatment discrimination pt_BR
dc.subject.classification Cafeicultura::Sistemas agroecológicos e orgânicos pt_BR
dc.title Multispectral images for discrimination of sources and doses of fertilizer in coffee plants pt_BR
dc.type Artigo pt_BR

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