A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.

Filed experiments were concluded to provide proof of concept. Accurate plot segmentation results enabled the extraction of several canopy features associated with biomass yield. The software for aerial biomass estimation is available for other users.

Detalles Bibliográficos
Autor principal: CGIAR Research Program on Rice
Formato: Informe técnico
Lenguaje:Inglés
Publicado: 2020
Materias:
Acceso en línea:https://hdl.handle.net/10568/122305
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author CGIAR Research Program on Rice
author_browse CGIAR Research Program on Rice
author_facet CGIAR Research Program on Rice
author_sort CGIAR Research Program on Rice
collection Repository of Agricultural Research Outputs (CGSpace)
description Filed experiments were concluded to provide proof of concept. Accurate plot segmentation results enabled the extraction of several canopy features associated with biomass yield. The software for aerial biomass estimation is available for other users.
format Informe técnico
id CGSpace122305
institution CGIAR Consortium
language Inglés
publishDate 2020
publishDateRange 2020
publishDateSort 2020
record_format dspace
spelling CGSpace1223052023-03-14T12:17:08Z A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops. CGIAR Research Program on Rice rice crops development rural development biomass estimation systems canopy agrifood systems experiments extraction software Filed experiments were concluded to provide proof of concept. Accurate plot segmentation results enabled the extraction of several canopy features associated with biomass yield. The software for aerial biomass estimation is available for other users. 2020-12-31 2022-10-06T13:56:03Z 2022-10-06T13:56:03Z Report https://hdl.handle.net/10568/122305 en Open Access application/pdf CGIAR Research Program on Rice. 2020. A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops. Reported in Rice Annual Report 2020. Innovations.
spellingShingle rice
crops
development
rural development
biomass
estimation
systems
canopy
agrifood systems
experiments
extraction
software
CGIAR Research Program on Rice
A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.
title A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.
title_full A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.
title_fullStr A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.
title_full_unstemmed A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.
title_short A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.
title_sort novel nir image segmentation method for the precise estimation of above ground biomass in rice crops
topic rice
crops
development
rural development
biomass
estimation
systems
canopy
agrifood systems
experiments
extraction
software
url https://hdl.handle.net/10568/122305
work_keys_str_mv AT cgiarresearchprogramonrice anovelnirimagesegmentationmethodforthepreciseestimationofabovegroundbiomassinricecrops
AT cgiarresearchprogramonrice novelnirimagesegmentationmethodforthepreciseestimationofabovegroundbiomassinricecrops