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Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data

Remote sensing techniques can be efficient for non-destructive, rapid detection of wheat nitrogen (N) nutrient status. In the paper, we examined the relationships of canopy multi-angular data with aerial N uptake of winter wheat (Triticum aestivum L.) across different growing seasons, locations, yea...

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Autores principales: Guo, Bin-Bin, Zhu, Yun-Ji, Feng, Wei, He, Li, Wu, Ya-Peng, Zhou, Yi, Ren, Xing-Xu, Ma, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982994/
https://www.ncbi.nlm.nih.gov/pubmed/29887871
http://dx.doi.org/10.3389/fpls.2018.00675
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author Guo, Bin-Bin
Zhu, Yun-Ji
Feng, Wei
He, Li
Wu, Ya-Peng
Zhou, Yi
Ren, Xing-Xu
Ma, Ying
author_facet Guo, Bin-Bin
Zhu, Yun-Ji
Feng, Wei
He, Li
Wu, Ya-Peng
Zhou, Yi
Ren, Xing-Xu
Ma, Ying
author_sort Guo, Bin-Bin
collection PubMed
description Remote sensing techniques can be efficient for non-destructive, rapid detection of wheat nitrogen (N) nutrient status. In the paper, we examined the relationships of canopy multi-angular data with aerial N uptake of winter wheat (Triticum aestivum L.) across different growing seasons, locations, years, wheat varieties, and N application rates. Seventeen vegetation indices (VIs) selected from the literature were measured for the stability in estimating aerial N uptake of wheat under 13 view zenith angles (VZAs) in the solar principal plane (SPP). In total, the back-scatter angles showed better VI behavior than the forward-scatter angles. The correlation coefficient of VIs with aerial N uptake increased with decreasing VZAs. The best linear relationship was integrated with the optimized common indices DIDA and DDn to examine dynamic changes in aerial N uptake; this led to coefficients of determination (R(2)) of 0.769 and 0.760 at the −10° viewing angle. Our novel area index, designed the modified right-side peak area index (mRPA), was developed in accordance with exploration of the spectral area calculation and red-edge feature using the equation: mRPA = (R(760)/R(600))(1/2) × (R(760)-R(718)). Investigating the predictive accuracy of mRPA for aerial N uptake across VZAs demonstrated that the best performance was at −10° [R(2) = 0.804, p < 0.001, root mean square error (RMSE) = 3.615] and that the effect was relatively similar between −20° to +10° (R(2) = 0.782, p < 0.001, RMSE = 3.805). This leads us to construct a simple model under wide-angle combinations so as to improve the field operation simplicity and applicability. Fitting independent datasets to the models resulted in relative error (RE, %) values of 12.6, 14.1, and 14.9% between estimated and measured aerial N uptake for mRPA, DIDA, and DDn across the range of −20° to +10°, respectively, further confirming the superior test performance of the mRPA index. These results illustrate that the novel index mRPA represents a more accurate assessment of plant N status, which is beneficial for guiding N management in winter wheat.
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spelling pubmed-59829942018-06-08 Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data Guo, Bin-Bin Zhu, Yun-Ji Feng, Wei He, Li Wu, Ya-Peng Zhou, Yi Ren, Xing-Xu Ma, Ying Front Plant Sci Plant Science Remote sensing techniques can be efficient for non-destructive, rapid detection of wheat nitrogen (N) nutrient status. In the paper, we examined the relationships of canopy multi-angular data with aerial N uptake of winter wheat (Triticum aestivum L.) across different growing seasons, locations, years, wheat varieties, and N application rates. Seventeen vegetation indices (VIs) selected from the literature were measured for the stability in estimating aerial N uptake of wheat under 13 view zenith angles (VZAs) in the solar principal plane (SPP). In total, the back-scatter angles showed better VI behavior than the forward-scatter angles. The correlation coefficient of VIs with aerial N uptake increased with decreasing VZAs. The best linear relationship was integrated with the optimized common indices DIDA and DDn to examine dynamic changes in aerial N uptake; this led to coefficients of determination (R(2)) of 0.769 and 0.760 at the −10° viewing angle. Our novel area index, designed the modified right-side peak area index (mRPA), was developed in accordance with exploration of the spectral area calculation and red-edge feature using the equation: mRPA = (R(760)/R(600))(1/2) × (R(760)-R(718)). Investigating the predictive accuracy of mRPA for aerial N uptake across VZAs demonstrated that the best performance was at −10° [R(2) = 0.804, p < 0.001, root mean square error (RMSE) = 3.615] and that the effect was relatively similar between −20° to +10° (R(2) = 0.782, p < 0.001, RMSE = 3.805). This leads us to construct a simple model under wide-angle combinations so as to improve the field operation simplicity and applicability. Fitting independent datasets to the models resulted in relative error (RE, %) values of 12.6, 14.1, and 14.9% between estimated and measured aerial N uptake for mRPA, DIDA, and DDn across the range of −20° to +10°, respectively, further confirming the superior test performance of the mRPA index. These results illustrate that the novel index mRPA represents a more accurate assessment of plant N status, which is beneficial for guiding N management in winter wheat. Frontiers Media S.A. 2018-05-25 /pmc/articles/PMC5982994/ /pubmed/29887871 http://dx.doi.org/10.3389/fpls.2018.00675 Text en Copyright © 2018 Guo, Zhu, Feng, He, Wu, Zhou, Ren and Ma. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Guo, Bin-Bin
Zhu, Yun-Ji
Feng, Wei
He, Li
Wu, Ya-Peng
Zhou, Yi
Ren, Xing-Xu
Ma, Ying
Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data
title Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data
title_full Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data
title_fullStr Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data
title_full_unstemmed Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data
title_short Remotely Estimating Aerial N Uptake in Winter Wheat Using Red-Edge Area Index From Multi-Angular Hyperspectral Data
title_sort remotely estimating aerial n uptake in winter wheat using red-edge area index from multi-angular hyperspectral data
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982994/
https://www.ncbi.nlm.nih.gov/pubmed/29887871
http://dx.doi.org/10.3389/fpls.2018.00675
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