Spatio-temporal evaluation of plant height in corn via unmanned aerial systems

Detailed spatial and temporal data on plant growth are critical to guide crop management. Conventional methods to determine field plant traits are intensive, time-consuming, expensive, and limited to small areas. The objective of this study was to examine the integration of data collected via unman...

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Autores principales: Varela, Sebastián, Assefa, Yared, Vara Prasad, P. V., Peralta, Nahuel R., Griffin, Terry W., Sharda, Ajay, Ferguson, Allison, Ciampittia, Ignacio A.
Formato: Objeto de conferencia Resumen
Lenguaje:Inglés
Publicado: 2018
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/70988
http://47jaiio.sadio.org.ar/sites/default/files/CAI-8.pdf
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id I19-R120-10915-70988
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
data modeling
RGB color model
systems modeling
Sensors
biological research
spellingShingle Ciencias Informáticas
data modeling
RGB color model
systems modeling
Sensors
biological research
Varela, Sebastián
Assefa, Yared
Vara Prasad, P. V.
Peralta, Nahuel R.
Griffin, Terry W.
Sharda, Ajay
Ferguson, Allison
Ciampittia, Ignacio A.
Spatio-temporal evaluation of plant height in corn via unmanned aerial systems
topic_facet Ciencias Informáticas
data modeling
RGB color model
systems modeling
Sensors
biological research
description Detailed spatial and temporal data on plant growth are critical to guide crop management. Conventional methods to determine field plant traits are intensive, time-consuming, expensive, and limited to small areas. The objective of this study was to examine the integration of data collected via unmanned aerial systems (UAS) at critical corn (Zea mays L.) developmental stages for plant height and its relation to plant biomass. The main steps followed in this research were (1) workflow development for an ultrahigh resolution crop surface model (CSM) with the goal of determining plant height (CSM-estimated plant height) using data gathered from the UAS missions; (2) validation of CSM-estimated plant height with ground-truthing plant height (measured plant height); and (3) final estimation of plant biomass via integration of CSM-estimated plant height with ground-truthing stem diameter data. Results indicated a correlation between CSM-estimated plant height and ground-truthing plant height data at two weeks prior to flowering and at flowering stage, but high predictability at the later growth stage. Log–log analysis on the temporal data confirmed that these relationships are stable, presenting equal slopes for both crop stages evaluated. Concluding, data collected from low-altitude and with a low-cost sensor could be useful in estimating plant height.
format Objeto de conferencia
Resumen
author Varela, Sebastián
Assefa, Yared
Vara Prasad, P. V.
Peralta, Nahuel R.
Griffin, Terry W.
Sharda, Ajay
Ferguson, Allison
Ciampittia, Ignacio A.
author_facet Varela, Sebastián
Assefa, Yared
Vara Prasad, P. V.
Peralta, Nahuel R.
Griffin, Terry W.
Sharda, Ajay
Ferguson, Allison
Ciampittia, Ignacio A.
author_sort Varela, Sebastián
title Spatio-temporal evaluation of plant height in corn via unmanned aerial systems
title_short Spatio-temporal evaluation of plant height in corn via unmanned aerial systems
title_full Spatio-temporal evaluation of plant height in corn via unmanned aerial systems
title_fullStr Spatio-temporal evaluation of plant height in corn via unmanned aerial systems
title_full_unstemmed Spatio-temporal evaluation of plant height in corn via unmanned aerial systems
title_sort spatio-temporal evaluation of plant height in corn via unmanned aerial systems
publishDate 2018
url http://sedici.unlp.edu.ar/handle/10915/70988
http://47jaiio.sadio.org.ar/sites/default/files/CAI-8.pdf
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