Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/48973 |
Resumo: | Mechanized operations on terrain slopes can still lead to considerable errors in the alignment and distribution of plants. Knowing slope interference in semi-mechanized planting quality can contribute to precision improvement in decision making, mainly in regions with high slope. This study evaluates the quality of semi-mechanized coffee planting in different land slopes using a remotely piloted aircraft (RPA) and statistical process control (SPC). In a commercial coffee plantation, aerial images were collected by a remotely piloted aircraft (RPA) and subsequently transformed into a digital elevation model (DEM) and a slope map. Slope data were subjected to variance analysis and statistical process control (SPC). Dependent variables analyzed were variations in distance between planting lines and between plants in line. The distribution of plants on all the slopes evaluated was below expected; the most impacted was the slope between 20–25%, implementing 7.8% fewer plants than projected. Inferences about the spacing between plants in the planting row showed that in slopes between 30–40%, the spacing was 0.53 m and between 0 and 15% was 0.55 m. This denotes the compensation of the speed of the operation on different slopes. The spacing between the planting lines had unusual variations on steep slopes. The SCP quality graphics are of lower quality in operations between 30–40%, as they have an average spacing of 3.65 m and discrepant points in the graphics. Spacing variations were observed in all slopes as shown in the SCP charts, and possible causes and implications for future management were discussed, contributing to improvements in the culture installation stage. |
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Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraftRemote sensingPlanting qualityUAVPhotogrammetryUASUnmanned aerial vehicle (UAV)Mechanized operations on terrain slopes can still lead to considerable errors in the alignment and distribution of plants. Knowing slope interference in semi-mechanized planting quality can contribute to precision improvement in decision making, mainly in regions with high slope. This study evaluates the quality of semi-mechanized coffee planting in different land slopes using a remotely piloted aircraft (RPA) and statistical process control (SPC). In a commercial coffee plantation, aerial images were collected by a remotely piloted aircraft (RPA) and subsequently transformed into a digital elevation model (DEM) and a slope map. Slope data were subjected to variance analysis and statistical process control (SPC). Dependent variables analyzed were variations in distance between planting lines and between plants in line. The distribution of plants on all the slopes evaluated was below expected; the most impacted was the slope between 20–25%, implementing 7.8% fewer plants than projected. Inferences about the spacing between plants in the planting row showed that in slopes between 30–40%, the spacing was 0.53 m and between 0 and 15% was 0.55 m. This denotes the compensation of the speed of the operation on different slopes. The spacing between the planting lines had unusual variations on steep slopes. The SCP quality graphics are of lower quality in operations between 30–40%, as they have an average spacing of 3.65 m and discrepant points in the graphics. Spacing variations were observed in all slopes as shown in the SCP charts, and possible causes and implications for future management were discussed, contributing to improvements in the culture installation stage.Multidisciplinary Digital Publishing Institute (MDPI)2022-01-22T02:11:48Z2022-01-22T02:11:48Z2021-06-16info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfSANTANA, L. S. et al. Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft. Agronomy, [S.l.], v. 11, n. 6, p. 1-18, June 2021. DOI: 10.3390/agronomy11061224.http://repositorio.ufla.br/jspui/handle/1/48973Agronomyreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessSantana, Lucas SantosFerraz, Gabriel Araújo e SilvaCunha, João Paulo BarretoSantana, Mozarte SantosFaria, Rafael de OliveiraMarin, Diego BedinRossi, GiuseppeConti, LeonardoVieri, MarcoSarri, Danieleeng2022-01-22T02:11:48Zoai:localhost:1/48973Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2022-01-22T02:11:48Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft |
title |
Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft |
spellingShingle |
Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft Santana, Lucas Santos Remote sensing Planting quality UAV Photogrammetry UAS Unmanned aerial vehicle (UAV) |
title_short |
Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft |
title_full |
Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft |
title_fullStr |
Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft |
title_full_unstemmed |
Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft |
title_sort |
Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft |
author |
Santana, Lucas Santos |
author_facet |
Santana, Lucas Santos Ferraz, Gabriel Araújo e Silva Cunha, João Paulo Barreto Santana, Mozarte Santos Faria, Rafael de Oliveira Marin, Diego Bedin Rossi, Giuseppe Conti, Leonardo Vieri, Marco Sarri, Daniele |
author_role |
author |
author2 |
Ferraz, Gabriel Araújo e Silva Cunha, João Paulo Barreto Santana, Mozarte Santos Faria, Rafael de Oliveira Marin, Diego Bedin Rossi, Giuseppe Conti, Leonardo Vieri, Marco Sarri, Daniele |
author2_role |
author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Santana, Lucas Santos Ferraz, Gabriel Araújo e Silva Cunha, João Paulo Barreto Santana, Mozarte Santos Faria, Rafael de Oliveira Marin, Diego Bedin Rossi, Giuseppe Conti, Leonardo Vieri, Marco Sarri, Daniele |
dc.subject.por.fl_str_mv |
Remote sensing Planting quality UAV Photogrammetry UAS Unmanned aerial vehicle (UAV) |
topic |
Remote sensing Planting quality UAV Photogrammetry UAS Unmanned aerial vehicle (UAV) |
description |
Mechanized operations on terrain slopes can still lead to considerable errors in the alignment and distribution of plants. Knowing slope interference in semi-mechanized planting quality can contribute to precision improvement in decision making, mainly in regions with high slope. This study evaluates the quality of semi-mechanized coffee planting in different land slopes using a remotely piloted aircraft (RPA) and statistical process control (SPC). In a commercial coffee plantation, aerial images were collected by a remotely piloted aircraft (RPA) and subsequently transformed into a digital elevation model (DEM) and a slope map. Slope data were subjected to variance analysis and statistical process control (SPC). Dependent variables analyzed were variations in distance between planting lines and between plants in line. The distribution of plants on all the slopes evaluated was below expected; the most impacted was the slope between 20–25%, implementing 7.8% fewer plants than projected. Inferences about the spacing between plants in the planting row showed that in slopes between 30–40%, the spacing was 0.53 m and between 0 and 15% was 0.55 m. This denotes the compensation of the speed of the operation on different slopes. The spacing between the planting lines had unusual variations on steep slopes. The SCP quality graphics are of lower quality in operations between 30–40%, as they have an average spacing of 3.65 m and discrepant points in the graphics. Spacing variations were observed in all slopes as shown in the SCP charts, and possible causes and implications for future management were discussed, contributing to improvements in the culture installation stage. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-16 2022-01-22T02:11:48Z 2022-01-22T02:11:48Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
SANTANA, L. S. et al. Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft. Agronomy, [S.l.], v. 11, n. 6, p. 1-18, June 2021. DOI: 10.3390/agronomy11061224. http://repositorio.ufla.br/jspui/handle/1/48973 |
identifier_str_mv |
SANTANA, L. S. et al. Monitoring errors of semi-mechanized coffee planting by remotely piloted aircraft. Agronomy, [S.l.], v. 11, n. 6, p. 1-18, June 2021. DOI: 10.3390/agronomy11061224. |
url |
http://repositorio.ufla.br/jspui/handle/1/48973 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Multidisciplinary Digital Publishing Institute (MDPI) |
publisher.none.fl_str_mv |
Multidisciplinary Digital Publishing Institute (MDPI) |
dc.source.none.fl_str_mv |
Agronomy reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1815438993446141952 |