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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
22/01/2022 |
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Data da última atualização: |
22/01/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ANDRADE, R. G.; HOTT, M. C.; MAGALHAES JUNIOR, W. C. P. de; MACHADO, J. C.; BORGES, C. A. V. |
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Afiliação: |
RICARDO GUIMARAES ANDRADE, CNPGL; MARCOS CICARINI HOTT, CNPGL; WALTER COELHO P DE MAGALHAES JUNIOR, CNPGL; JUAREZ CAMPOLINA MACHADO, CNPGL; CRISTIANO AMANCIO VIEIRA BORGES, CNPGL. |
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Título: |
Unmanned aircraft for monitoring elephant grass genotypes in energy biomass production. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
International Journal of Advanced Engineering Research and Science, v. 9, n. 1, p. 70-76, 2022. |
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DOI: |
https://dx.doi.org/10.22161/ijaers.91.9 |
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Idioma: |
Inglês |
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Conteúdo: |
Elephant grass is a promising plant for economic and sustainable energy production. However, adapted cultivars and efficient strategies for selecting genotypes aimed at energy biomass production is essential. Remote sensing techniques provide spatiotemporal information from plants in an agile, non-destructive and non-invasive way. The present study aimed to use remote sensors onboard an unmanned aerial vehicle (UAV) to monitor elephant grass genotypes and assist in plant phenotyping for energy biomass production. The experimental plots were imaged in the visible and near infrared bands. Imaging was carried out in 66 experimental plots in the José Henrique Bruschi Experimental Field (CEJHB), located in Coronel Pacheco, MG, Brazil. The experiment was arranged in a randomized block design with three replications, and 22 elephant grass genotypes were evaluated. The aggregated index iMAPNDRE was strongly correlated with the dry matter production observed in the field, therefore a method with potential application for estimating the biomass of elephant grass genotypes. Thus, sensors aboard UAV platforms can assist breeders to select the best elephant grass genotypes for energy production. |
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Palavras-Chave: |
Drone; Índice de vegetação; Monitoramento; UAV. |
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Thesagro: |
Bioenergia; Capim Elefante; Sensoriamento Remoto. |
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Thesaurus Nal: |
Bioenergy; Grasses; Remote sensing; Vegetation index. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/230450/1/Unmanned-aircraft.pdf
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Marc: |
LEADER 02151naa a2200313 a 4500
001 2139252
005 2022-01-22
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://dx.doi.org/10.22161/ijaers.91.9$2DOI
100 1 $aANDRADE, R. G.
245 $aUnmanned aircraft for monitoring elephant grass genotypes in energy biomass production.$h[electronic resource]
260 $c2022
520 $aElephant grass is a promising plant for economic and sustainable energy production. However, adapted cultivars and efficient strategies for selecting genotypes aimed at energy biomass production is essential. Remote sensing techniques provide spatiotemporal information from plants in an agile, non-destructive and non-invasive way. The present study aimed to use remote sensors onboard an unmanned aerial vehicle (UAV) to monitor elephant grass genotypes and assist in plant phenotyping for energy biomass production. The experimental plots were imaged in the visible and near infrared bands. Imaging was carried out in 66 experimental plots in the José Henrique Bruschi Experimental Field (CEJHB), located in Coronel Pacheco, MG, Brazil. The experiment was arranged in a randomized block design with three replications, and 22 elephant grass genotypes were evaluated. The aggregated index iMAPNDRE was strongly correlated with the dry matter production observed in the field, therefore a method with potential application for estimating the biomass of elephant grass genotypes. Thus, sensors aboard UAV platforms can assist breeders to select the best elephant grass genotypes for energy production.
650 $aBioenergy
650 $aGrasses
650 $aRemote sensing
650 $aVegetation index
650 $aBioenergia
650 $aCapim Elefante
650 $aSensoriamento Remoto
653 $aDrone
653 $aÍndice de vegetação
653 $aMonitoramento
653 $aUAV
700 1 $aHOTT, M. C.
700 1 $aMAGALHAES JUNIOR, W. C. P. de
700 1 $aMACHADO, J. C.
700 1 $aBORGES, C. A. V.
773 $tInternational Journal of Advanced Engineering Research and Science$gv. 9, n. 1, p. 70-76, 2022.
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Embrapa Gado de Leite (CNPGL) |
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