Estimation of corn chlorophyll content using different red edge position algorithms

This research was based on the combined planting model of corn-soybean strip intercropping and the corns under different nitrogen levels were used as the test materials. The reflectance spectrum and chlorophyll content of leaves and canopies of corns were measured at the jointing stage, tasseling st...

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Main Authors: ZHANG Jiawei, WANG Zhonglin, TAN Xianming, WANG Beibei, YANG Wenyu, YANG Feng
Format: Article
Language:English
Published: Zhejiang University Press 2021-08-01
Series:浙江大学学报. 农业与生命科学版
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Online Access:https://www.academax.com/doi/10.3785/j.issn.1008-9209.2020.10.201
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author ZHANG Jiawei
WANG Zhonglin
TAN Xianming
WANG Beibei
YANG Wenyu
YANG Feng
author_facet ZHANG Jiawei
WANG Zhonglin
TAN Xianming
WANG Beibei
YANG Wenyu
YANG Feng
author_sort ZHANG Jiawei
collection DOAJ
description This research was based on the combined planting model of corn-soybean strip intercropping and the corns under different nitrogen levels were used as the test materials. The reflectance spectrum and chlorophyll content of leaves and canopies of corns were measured at the jointing stage, tasseling stage and filling stage. Red edge position (REP) was extracted by continuous wavelet transform (CWT) and other algorithms [maximum first derivative method (FD), four-point interpolation method (FPI) and linear extrapolation method (LEM)]. The quantitative relationships between REP and chlorophyll contents were systematically analyzed to compare the accuracy and stability of the REP extracted by each red edge algorithm on the two scales of leaf and canopy. The results showed that, based on the REP-CWT, the estimation accuracy of chlorophyll content was higher on leaf and canopy scales, and the stability was the strongest, which indicated that REP-CWT was feasible in extracting the REP of corn reflectance spectrum. The quantitative estimation models of corn leaf chlorophyll content and canopy chlorophyll content base on REP-LEM and REP-FPI, respectively, were the best. This study provides a new method for extracting the REP of corn reflectance spectrum, and then constructs the best quantitative estimation model of corn chlorophyll content on different observation scales (leaf and canopy), and offers an effective way to monitor the nitrogen nutrition status of corn.
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issn 1008-9209
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publisher Zhejiang University Press
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series 浙江大学学报. 农业与生命科学版
spelling doaj-art-037ca8d122974902b776a0ca03fa28dd2025-08-20T02:47:27ZengZhejiang University Press浙江大学学报. 农业与生命科学版1008-92092097-51552021-08-014746447210.3785/j.issn.1008-9209.2020.10.20110089209Estimation of corn chlorophyll content using different red edge position algorithmsZHANG JiaweiWANG ZhonglinTAN XianmingWANG BeibeiYANG WenyuYANG FengThis research was based on the combined planting model of corn-soybean strip intercropping and the corns under different nitrogen levels were used as the test materials. The reflectance spectrum and chlorophyll content of leaves and canopies of corns were measured at the jointing stage, tasseling stage and filling stage. Red edge position (REP) was extracted by continuous wavelet transform (CWT) and other algorithms [maximum first derivative method (FD), four-point interpolation method (FPI) and linear extrapolation method (LEM)]. The quantitative relationships between REP and chlorophyll contents were systematically analyzed to compare the accuracy and stability of the REP extracted by each red edge algorithm on the two scales of leaf and canopy. The results showed that, based on the REP-CWT, the estimation accuracy of chlorophyll content was higher on leaf and canopy scales, and the stability was the strongest, which indicated that REP-CWT was feasible in extracting the REP of corn reflectance spectrum. The quantitative estimation models of corn leaf chlorophyll content and canopy chlorophyll content base on REP-LEM and REP-FPI, respectively, were the best. This study provides a new method for extracting the REP of corn reflectance spectrum, and then constructs the best quantitative estimation model of corn chlorophyll content on different observation scales (leaf and canopy), and offers an effective way to monitor the nitrogen nutrition status of corn.https://www.academax.com/doi/10.3785/j.issn.1008-9209.2020.10.201cornred edge positioncontinuous wavelet transformchlorophyllmonitoring
spellingShingle ZHANG Jiawei
WANG Zhonglin
TAN Xianming
WANG Beibei
YANG Wenyu
YANG Feng
Estimation of corn chlorophyll content using different red edge position algorithms
浙江大学学报. 农业与生命科学版
corn
red edge position
continuous wavelet transform
chlorophyll
monitoring
title Estimation of corn chlorophyll content using different red edge position algorithms
title_full Estimation of corn chlorophyll content using different red edge position algorithms
title_fullStr Estimation of corn chlorophyll content using different red edge position algorithms
title_full_unstemmed Estimation of corn chlorophyll content using different red edge position algorithms
title_short Estimation of corn chlorophyll content using different red edge position algorithms
title_sort estimation of corn chlorophyll content using different red edge position algorithms
topic corn
red edge position
continuous wavelet transform
chlorophyll
monitoring
url https://www.academax.com/doi/10.3785/j.issn.1008-9209.2020.10.201
work_keys_str_mv AT zhangjiawei estimationofcornchlorophyllcontentusingdifferentrededgepositionalgorithms
AT wangzhonglin estimationofcornchlorophyllcontentusingdifferentrededgepositionalgorithms
AT tanxianming estimationofcornchlorophyllcontentusingdifferentrededgepositionalgorithms
AT wangbeibei estimationofcornchlorophyllcontentusingdifferentrededgepositionalgorithms
AT yangwenyu estimationofcornchlorophyllcontentusingdifferentrededgepositionalgorithms
AT yangfeng estimationofcornchlorophyllcontentusingdifferentrededgepositionalgorithms