Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto”
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.5/25453 |
Resumo: | Mestrado em Engenharia de Viticultura e Enologia (Double degree) / Instituto Superior de Agronomia. Universidade de Lisboa / Faculdade de Ciências. Universidade do Porto |
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Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto”algorithmsimage analysisMATLAByield estimationVINBOTMestrado em Engenharia de Viticultura e Enologia (Double degree) / Instituto Superior de Agronomia. Universidade de Lisboa / Faculdade de Ciências. Universidade do PortoYield estimation in recent years is identified as one of more important topics in viticulture because it can lead to more efficiently managed vineyards producing wines of highly quality. Recently, to improve the efficiency of yield estimation, image analysis is becoming an important tool to collect detailed information from the vines regarding the yield. New technologies were developed for yield estimation using a new ground platform, such as VINBOT, using image analysis. This work was done in a vineyard of the “Instituto Superior de Agronomia”, with the aim to estimate the final yield, during the growing cycle 2019 of the variety “Arinto”, using images collected in three different modality: laboratory condition (1), field condition (2) and VINBOT robot. In the every condition, the images were captured with the RGB-D camera. For (1) and (2) the photos were acquired manually through the use of a digital camera placed on a tripod but in the (3) the RGB-D camera was fixed on the VINBOT robot. In this work, the correlation of yield components between field data and images data was evaluated. In addition, throught MATLAB, it was evaluate the number of visible berries in the images and the percentage of visible berries not occluded by leaves and by other berries. Througt the laboratory results was calculate a growth factor of bunches on the periods pea-size and veraison. On the VINBOT analysis the efficacy to estimate the total yield from the number of berries was higher at maturation with a 10% error ratio. The relationship between canopy porosity and exposed berries showed for all the stages high and significant R2 indicating that we can use it to estimate berries occlusion through image analysis. This accuracy makes the proposed methodology ideal for early yield prediction as a very helpful tool for the grape and wine industrys.n.Lopes, CarlosPisciotta, AntoninoRepositório da Universidade de LisboaGenuardi, Sergio2022-09-09T10:12:08Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.5/25453TID:203082010engGenuardi, S. - Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto”. Lisboa: ISA, 2021, 56 p.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-06T14:55:01Zoai:www.repository.utl.pt:10400.5/25453Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:09:19.387447Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto” |
title |
Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto” |
spellingShingle |
Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto” Genuardi, Sergio algorithms image analysis MATLAB yield estimation VINBOT |
title_short |
Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto” |
title_full |
Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto” |
title_fullStr |
Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto” |
title_full_unstemmed |
Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto” |
title_sort |
Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto” |
author |
Genuardi, Sergio |
author_facet |
Genuardi, Sergio |
author_role |
author |
dc.contributor.none.fl_str_mv |
Lopes, Carlos Pisciotta, Antonino Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Genuardi, Sergio |
dc.subject.por.fl_str_mv |
algorithms image analysis MATLAB yield estimation VINBOT |
topic |
algorithms image analysis MATLAB yield estimation VINBOT |
description |
Mestrado em Engenharia de Viticultura e Enologia (Double degree) / Instituto Superior de Agronomia. Universidade de Lisboa / Faculdade de Ciências. Universidade do Porto |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021 2021-01-01T00:00:00Z 2022-09-09T10:12:08Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.5/25453 TID:203082010 |
url |
http://hdl.handle.net/10400.5/25453 |
identifier_str_mv |
TID:203082010 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Genuardi, S. - Assessing berry number for grapevine yield estimation by image analysis: case study with the white variety “Arinto”. Lisboa: ISA, 2021, 56 p. |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
s.n. |
publisher.none.fl_str_mv |
s.n. |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799131187736739840 |