Repository logo
 
Publication

Estimation of Productivity and Above-Ground Biomass for Corn (Zea mays) via Vegetation Indices in Madeira Island

2023Journal article Open access
Simple item page
dc.contributor.authorMacedo, Fabrício Lopes
dc.contributor.authorNóbrega, Humberto
dc.contributor.authorFreitas, José G. R. de
dc.contributor.authorRagonezi, Carla
dc.contributor.authorPinto, Lino
dc.contributor.authorRosa, Joana
dc.contributor.authorCarvalho, Miguel A. A. Pinheiro
dc.date.accessioned2024-01-08T12:25:32Z
dc.date.available2024-01-08T12:25:32Z
dc.date.issued2023
dc.description.abstractThe advancement of technology associated with the field, especially the use of unmanned aerial vehicles (UAV) coupled with multispectral cameras, allows us to monitor the condition of crops in real time and contribute to the field of machine learning. The objective of this study was to estimate both productivity and above-ground biomass (AGB) for the corn crop by applying different vegetation indices (VIs) via high-resolution aerial imagery. Among the indices tested, strong correlations were obtained between productivity and the normalized difference vegetation index (NDVI) with a significance level of p < 0.05 (0.719), as well as for the normalized difference red edge (NDRE), or green normalized difference vegetation index (GNDVI) with crop productivity (p < 0.01), respectively 0.809 and 0.859. The AGB results align with those obtained previously; GNDVI and NDRE showed high correlations, but now with a significance level of p < 0.05 (0.758 and 0.695). Both GNDVI and NDRE indices showed coefficients of determination for productivity and AGB estimation with 0.738 and 0.654, and 0.701 and 0.632, respectively. The use of the GNDVI and NDRE indices shows excellent results for estimating productivity as well as AGB for the corn crop, both at the spatial and numerical levels. The possibility of predicting crop productivity is an essential tool for producers, since it allows them to make timely decisions to correct any deficit present in their agricultural plots, and further contributes to AI integration for drone digital optimization.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMacedo, F.L.; Nóbrega, H.; de Freitas, J.G.R.; Ragonezi, C.; Pinto, L.; Rosa, J.; Pinheiro de Carvalho, M.A.A. Estimation of Productivity and Above-Ground Biomass for Corn (Zea mays) via Vegetation Indices in Madeira Island. Agriculture 2023, 13, 1115. https://doi.org/10.3390/ agriculture13061115pt_PT
dc.identifier.doi10.3390/agriculture13061115pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/5462
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationCentre for the Research and Technology of Agro-Environmental and Biological Sciences
dc.relationCentre for the Research and Technology of Agro-Environmental and Biological Sciences
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectPrecision agriculturept_PT
dc.subjectNDREpt_PT
dc.subjectNDVIpt_PT
dc.subjectGNDVIpt_PT
dc.subjectModeling trainingpt_PT
dc.subjectMachine learningpt_PT
dc.subjectMultispectral imagespt_PT
dc.subjectArtificial intelligencept_PT
dc.subject.pt_PT
dc.subjectEscola Superior de Tecnologias e Gestãopt_PT
dc.subjectFaculdade de Ciências da Vidapt_PT
dc.titleEstimation of Productivity and Above-Ground Biomass for Corn (Zea mays) via Vegetation Indices in Madeira Islandpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre for the Research and Technology of Agro-Environmental and Biological Sciences
oaire.awardTitleCentre for the Research and Technology of Agro-Environmental and Biological Sciences
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04033%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04033%2F2020/PT
oaire.citation.issue6pt_PT
oaire.citation.startPage1115pt_PT
oaire.citation.titleAgriculturept_PT
oaire.citation.volume13pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameMacedo
person.familyNameNóbrega
person.familyNameRagonezi
person.familyNameAlmeida Pinheiro de Carvalho
person.givenNameFabrício Lopes de
person.givenNameHumberto
person.givenNameCarla
person.givenNameMiguel Angelo
person.identifier2439118
person.identifier1218558
person.identifier.ciencia-idBD1F-4778-60D1
person.identifier.ciencia-idFC12-D3F0-EF3D
person.identifier.ciencia-id4610-6741-6816
person.identifier.orcid0000-0002-8025-6422
person.identifier.orcid0000-0001-8900-9340
person.identifier.orcid0000-0002-1822-5473
person.identifier.orcid0000-0002-5084-870X
person.identifier.ridAEE-0913-2022
person.identifier.scopus-author-id36460033800
person.identifier.scopus-author-id8758577600
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication0cae1387-e03a-4cd4-bd47-c48edc60ad27
relation.isAuthorOfPublicationafc849c2-6d0f-461a-9f8f-0501ed5183f8
relation.isAuthorOfPublicationa51cc988-63ce-40e5-9b71-a27b1eadc937
relation.isAuthorOfPublication2e433c48-88f8-40a2-b21f-de78b44aab1c
relation.isAuthorOfPublication.latestForDiscoverya51cc988-63ce-40e5-9b71-a27b1eadc937
relation.isProjectOfPublication0fbc36e7-b7eb-44ee-8858-fb77c563003b
relation.isProjectOfPublication53f600b8-a43f-4466-bfd6-d6565b137631
relation.isProjectOfPublication.latestForDiscovery53f600b8-a43f-4466-bfd6-d6565b137631

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Estimation of Productivity and Above-Ground Biomass for Corn (Zea mays) via Vegetation Indices in Madeira Island.pdf
Size:
3.14 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Artigos em revistas internacionais