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Journal of Zhejiang University SCIENCE B 2008 Vol.9 No.5 P.378-384


Quantifying biochemical variables of corn by hyperspectral reflectance at leaf scale

Author(s):  Qiu-xiang YI, Jing-feng HUANG, Fu-min WANG, Xiu-zhen WANG

Affiliation(s):  Institute of Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310029, China; more

Corresponding email(s):   hjf@zju.edu.cn

Key Words:  Biochemical variables, Corn, The first derivative spectral reflectance, Spectral reflectance

Qiu-xiang YI, Jing-feng HUANG, Fu-min WANG, Xiu-zhen WANG. Quantifying biochemical variables of corn by hyperspectral reflectance at leaf scale[J]. Journal of Zhejiang University Science B, 2008, 9(5): 378-384.

@article{title="Quantifying biochemical variables of corn by hyperspectral reflectance at leaf scale",
author="Qiu-xiang YI, Jing-feng HUANG, Fu-min WANG, Xiu-zhen WANG",
journal="Journal of Zhejiang University Science B",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Quantifying biochemical variables of corn by hyperspectral reflectance at leaf scale
%A Qiu-xiang YI
%A Jing-feng HUANG
%A Fu-min WANG
%A Xiu-zhen WANG
%J Journal of Zhejiang University SCIENCE B
%V 9
%N 5
%P 378-384
%@ 1673-1581
%D 2008
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B0730019

T1 - Quantifying biochemical variables of corn by hyperspectral reflectance at leaf scale
A1 - Qiu-xiang YI
A1 - Jing-feng HUANG
A1 - Fu-min WANG
A1 - Xiu-zhen WANG
J0 - Journal of Zhejiang University Science B
VL - 9
IS - 5
SP - 378
EP - 384
%@ 1673-1581
Y1 - 2008
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B0730019

To further develop the methods to remotely sense the biochemical content of plant canopies, we report the results of an experiment to estimate the concentrations of three biochemical variables of corn, i.e., nitrogen (N), crude fat (EE) and crude fiber (CF) concentrations, by spectral reflectance and the first derivative reflectance at fresh leaf scale. The correlations between spectral reflectance and the first derivative transformation and three biochemical variables were analyzed, and a set of estimation models were established using curve-fitting analyses. Coefficient of determination (R2), root mean square error (RMSE) and relative error of prediction (REP) of estimation models were calculated for the model quality evaluations, and the possible optimum estimation models of three biochemical variables were proposed, with R2 being 0.891, 0.698 and 0.480 for the estimation models of N, EE and CF concentrations, respectively. The results also indicate that using the first derivative reflectance was better than using raw spectral reflectance for all three biochemical variables estimation, and that the first derivative reflectances at 759 nm, 1954 nm and 2370 nm were most suitable to develop the estimation models of N, EE and CF concentrations, respectively. In addition, the high correlation coefficients of the theoretical and the measured biochemical parameters were obtained, especially for nitrogen (r=0.948).

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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