Pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image

Pineapple becomes number 4th highest fruit production in Indonesia in 2020 and is one of the mainstay export commodities. Estimates of pineapple production using high-resolution images from drones are extremely rare, whereas production estimates for popular commodities do not pay attention to plant...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Aditya Nugraha Putra, Wanda Kristiawati, Dewi Camila Mumtazydah, Tiaranita Anggarwati, Renata Annisa, Dinna Hadi Sholikah, Dwi Okiyanto, Sudarto
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Pineapple Forcing Remote sensing, UAV, near-infrared Ultra-high-resolution Index Agriculture (General) S1-972 Agricultural industries HD9000-9495
Acceso en línea:	https://doaj.org/article/88d84dcf432043b7ae5a594d2935e986
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:88d84dcf432043b7ae5a594d2935e986
record_format	dspace
spelling	oai:doaj.org-article:88d84dcf432043b7ae5a594d2935e9862021-11-24T04:35:34ZPineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image2772-375510.1016/j.atech.2021.100025https://doaj.org/article/88d84dcf432043b7ae5a594d2935e9862021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2772375521000253https://doaj.org/toc/2772-3755Pineapple becomes number 4th highest fruit production in Indonesia in 2020 and is one of the mainstay export commodities. Estimates of pineapple production using high-resolution images from drones are extremely rare, whereas production estimates for popular commodities do not pay attention to plant growth stages. This study aims to estimate pineapple biomass using UAVs at various pineapple growth stages to obtain the best formulation. Aerial photographs were taken using the Quest UAV, equipped with visible light and near infra-red camera. Ultra-high-resolution aerial photographs were taken using a UAV with a multispectral camera then transformed into a vegetation index (GDVI, NDVI, OSAVI, and TDVI). Images were taken on land plots with plant forcing ages (F) F-5, F-4, F-3, F-3, F-2, F-1, F0, F+1, and F+2. The results show that each pineapple growth stage has a different index to estimate. GDVI can be used to estimate the age of pineapples at F-5, F-4, F-3, and F+1 stage, while OSAVI can be used for F-2, F-1, and F + 2 TDVI for F0. The validation test result using a paired t-test showed that the biomass data on the field's measurement results are no different from the estimate data, so the best vegetation index can be used to estimate biomass.Aditya Nugraha PutraWanda KristiawatiDewi Camila MumtazydahTiaranita AnggarwatiRenata AnnisaDinna Hadi SholikahDwi Okiyanto SudartoElsevierarticlePineappleForcingRemote sensing, UAV, near-infraredUltra-high-resolutionIndexAgriculture (General)S1-972Agricultural industriesHD9000-9495ENSmart Agricultural Technology, Vol 1, Iss , Pp 100025- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Pineapple Forcing Remote sensing, UAV, near-infrared Ultra-high-resolution Index Agriculture (General) S1-972 Agricultural industries HD9000-9495
spellingShingle	Pineapple Forcing Remote sensing, UAV, near-infrared Ultra-high-resolution Index Agriculture (General) S1-972 Agricultural industries HD9000-9495 Aditya Nugraha Putra Wanda Kristiawati Dewi Camila Mumtazydah Tiaranita Anggarwati Renata Annisa Dinna Hadi Sholikah Dwi Okiyanto Sudarto Pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image
description	Pineapple becomes number 4th highest fruit production in Indonesia in 2020 and is one of the mainstay export commodities. Estimates of pineapple production using high-resolution images from drones are extremely rare, whereas production estimates for popular commodities do not pay attention to plant growth stages. This study aims to estimate pineapple biomass using UAVs at various pineapple growth stages to obtain the best formulation. Aerial photographs were taken using the Quest UAV, equipped with visible light and near infra-red camera. Ultra-high-resolution aerial photographs were taken using a UAV with a multispectral camera then transformed into a vegetation index (GDVI, NDVI, OSAVI, and TDVI). Images were taken on land plots with plant forcing ages (F) F-5, F-4, F-3, F-3, F-2, F-1, F0, F+1, and F+2. The results show that each pineapple growth stage has a different index to estimate. GDVI can be used to estimate the age of pineapples at F-5, F-4, F-3, and F+1 stage, while OSAVI can be used for F-2, F-1, and F + 2 TDVI for F0. The validation test result using a paired t-test showed that the biomass data on the field's measurement results are no different from the estimate data, so the best vegetation index can be used to estimate biomass.
format	article
author	Aditya Nugraha Putra Wanda Kristiawati Dewi Camila Mumtazydah Tiaranita Anggarwati Renata Annisa Dinna Hadi Sholikah Dwi Okiyanto Sudarto
author_facet	Aditya Nugraha Putra Wanda Kristiawati Dewi Camila Mumtazydah Tiaranita Anggarwati Renata Annisa Dinna Hadi Sholikah Dwi Okiyanto Sudarto
author_sort	Aditya Nugraha Putra
title	Pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image
title_short	Pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image
title_full	Pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image
title_fullStr	Pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image
title_full_unstemmed	Pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image
title_sort	pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: vegetation index approach from ultra-high-resolution image
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/88d84dcf432043b7ae5a594d2935e986
work_keys_str_mv	AT adityanugrahaputra pineapplebiomassestimationusingunmannedaerialvehicleinvariousforcingstagevegetationindexapproachfromultrahighresolutionimage AT wandakristiawati pineapplebiomassestimationusingunmannedaerialvehicleinvariousforcingstagevegetationindexapproachfromultrahighresolutionimage AT dewicamilamumtazydah pineapplebiomassestimationusingunmannedaerialvehicleinvariousforcingstagevegetationindexapproachfromultrahighresolutionimage AT tiaranitaanggarwati pineapplebiomassestimationusingunmannedaerialvehicleinvariousforcingstagevegetationindexapproachfromultrahighresolutionimage AT renataannisa pineapplebiomassestimationusingunmannedaerialvehicleinvariousforcingstagevegetationindexapproachfromultrahighresolutionimage AT dinnahadisholikah pineapplebiomassestimationusingunmannedaerialvehicleinvariousforcingstagevegetationindexapproachfromultrahighresolutionimage AT dwiokiyanto pineapplebiomassestimationusingunmannedaerialvehicleinvariousforcingstagevegetationindexapproachfromultrahighresolutionimage AT sudarto pineapplebiomassestimationusingunmannedaerialvehicleinvariousforcingstagevegetationindexapproachfromultrahighresolutionimage
_version_	1718415923866501120

Pineapple biomass estimation using unmanned aerial vehicle in various forcing stage: Vegetation index approach from ultra-high-resolution image

Ejemplares similares