Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize

Background: Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement. Results: We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield. Conclusion: This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed.

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Main Authors: Zaman-Allah, M., Vergara Diaz, O., Araus, J.L., Amsal Tesfaye Tarekegne, Magorokosho, C., Zarco-Tejada, P.J., Hornero, A., Hernández-Alba, A., Das, B., Craufurd, P., Olsen, M., Prasanna, B.M., Cairns, J.E.
Format: Article biblioteca
Language:English
Published: BioMed Central 2015
Subjects:AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, Phenotyping Platforms, UAP, MAIZE, PHENOTYPES, REMOTE SENSING, UNMANNED AERIAL VEHICLES, NITROGEN FERTILIZERS,
Online Access:http://hdl.handle.net/10883/16941
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spelling dig-cimmyt-10883-169412024-03-13T19:38:57Z Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize Zaman-Allah, M. Vergara Diaz, O. Araus, J.L. Amsal Tesfaye Tarekegne Magorokosho, C. Zarco-Tejada, P.J. Hornero, A. Hernández-Alba, A. Das, B. Craufurd, P. Olsen, M. Prasanna, B.M. Cairns, J.E. AGRICULTURAL SCIENCES AND BIOTECHNOLOGY Phenotyping Platforms UAP MAIZE PHENOTYPES REMOTE SENSING UNMANNED AERIAL VEHICLES NITROGEN FERTILIZERS Background: Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement. Results: We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield. Conclusion: This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed. 2016-06-13T16:05:34Z 2016-06-13T16:05:34Z 2015 Article http://hdl.handle.net/10883/16941 10.1186/s13007-015-0078-2 English CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose. Open Access PDF ETHIOPIA London, United Kingdom BioMed Central 1 11 Plant Methods 35
institution CIMMYT
collection DSpace
country México
countrycode MX
component Bibliográfico
access En linea
databasecode dig-cimmyt
tag biblioteca
region America del Norte
libraryname CIMMYT Library
language English
topic AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Phenotyping Platforms
UAP
MAIZE
PHENOTYPES
REMOTE SENSING
UNMANNED AERIAL VEHICLES
NITROGEN FERTILIZERS
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Phenotyping Platforms
UAP
MAIZE
PHENOTYPES
REMOTE SENSING
UNMANNED AERIAL VEHICLES
NITROGEN FERTILIZERS
spellingShingle AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Phenotyping Platforms
UAP
MAIZE
PHENOTYPES
REMOTE SENSING
UNMANNED AERIAL VEHICLES
NITROGEN FERTILIZERS
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Phenotyping Platforms
UAP
MAIZE
PHENOTYPES
REMOTE SENSING
UNMANNED AERIAL VEHICLES
NITROGEN FERTILIZERS
Zaman-Allah, M.
Vergara Diaz, O.
Araus, J.L.
Amsal Tesfaye Tarekegne
Magorokosho, C.
Zarco-Tejada, P.J.
Hornero, A.
Hernández-Alba, A.
Das, B.
Craufurd, P.
Olsen, M.
Prasanna, B.M.
Cairns, J.E.
Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize
description Background: Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement. Results: We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield. Conclusion: This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed.
format Article
topic_facet AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Phenotyping Platforms
UAP
MAIZE
PHENOTYPES
REMOTE SENSING
UNMANNED AERIAL VEHICLES
NITROGEN FERTILIZERS
author Zaman-Allah, M.
Vergara Diaz, O.
Araus, J.L.
Amsal Tesfaye Tarekegne
Magorokosho, C.
Zarco-Tejada, P.J.
Hornero, A.
Hernández-Alba, A.
Das, B.
Craufurd, P.
Olsen, M.
Prasanna, B.M.
Cairns, J.E.
author_facet Zaman-Allah, M.
Vergara Diaz, O.
Araus, J.L.
Amsal Tesfaye Tarekegne
Magorokosho, C.
Zarco-Tejada, P.J.
Hornero, A.
Hernández-Alba, A.
Das, B.
Craufurd, P.
Olsen, M.
Prasanna, B.M.
Cairns, J.E.
author_sort Zaman-Allah, M.
title Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize
title_short Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize
title_full Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize
title_fullStr Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize
title_full_unstemmed Unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize
title_sort unmanned aerial platform‑based multi‑spectral imaging for field phenotyping of maize
publisher BioMed Central
publishDate 2015
url http://hdl.handle.net/10883/16941
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