Autosoft Journal

Online Manuscript Access

Hyperspectral Models for Estimating Chlorophyll Content of Young Apple Tree Leaves



A hyperspectral-based chlorophyll content estimating model for young apple tree leaves is proposed in this paper. It aims to have a contribution to modernized production and scientific management. The study takes the trees, which are two years old as the research objects. The young apple tree leaves are picked in autumn when they stop growing, and the spectral data and the chlorophyll content in the leaves of young apple trees are measured. First derivative (FD) is used to process the spectral data, and choose sensitive parameters. Hyperspectral models for estimating chlorophyll content in the leaves of young apple trees are established by a single variable (use one variable to establish models) and partial least square (PLS) methods. Four sensitive parameters are chosen to establish hyperspectral estimating models using partial least square. The model has the highest R2 (coefficient of determination), lower RMSE (root mean square error) and RE% (relative error). The partial least square model is more appropriate for estimating chlorophyll content in the leaves of young apple tree.



Total Pages: 11
Pages: 383-393


Manuscript ViewPdf Subscription required to access this document

Obtain access this manuscript in one of the following ways

Already subscribed?

Need information on obtaining a subscription? Personal and institutional subscriptions are available.

Already an author? Have access via email address?


Volume: 21
Issue: 3
Year: 2015

Cite this document


Blackburn, G. A. "Spectral Indices for Estimating Photosynthetic Pigment Concentrations: A Test Using Senescent Tree Leaves." International Journal of Remote Sensing 19.4 (1998): 657-675. Crossref. Web.

Blackburn, G. A. "Hyperspectral Remote Sensing of Plant Pigments." Journal of Experimental Botany 58.4 (2006): 855-867. Crossref. Web.

BLACKBURN, G, and J FERWERDA. "Retrieval of Chlorophyll Concentration from Leaf Reflectance Spectra Using Wavelet Analysis." Remote Sensing of Environment 112.4 (2008): 1614-1632. Crossref. Web.

Chen Y. Journal of Tropical and Subtropical Botany

Huang S. Transactions of the Chinese Society for Agricultural Machinery

Huang S. Transactions of the Chinese Society of Agricultural Engineering

Lang S. Spectroscopy and Spectral Analysis

Li M. Journal of Northwest Forestry University

Liu Z. Journal of Lake Sciences

Vane, Gregg, and Alexander F.H Goetz. "Terrestrial Imaging Spectrometry: Current Status, Future Trends." Remote Sensing of Environment 44.2-3 (1993): 117-126. Crossref. Web.

Wang J. Science China Press

Wang Z. Guangxi Agricultural Sciences

Wang Z. Chinese Agricultural Science Bulletin

WuW. (2003). Phytophysiology. Beijing: Science Press.

Yao F. Science of Surveying and Mapping

Yao F. Transactions of the CSAE

Yao F. Ludong University Journal

Yoder, Barbara J., and Rita E. Pettigrew-Crosby. "Predicting Nitrogen and Chlorophyll Content and Concentrations from Reflectance Spectra (400-2500 Nm) at Leaf and Canopy Scales." Remote Sensing of Environment 53.3 (1995): 199-211. Crossref. Web.

Zhang, Dongyan et al. "Research Vertical Distribution of Chlorophyll Content of Wheat Leaves Using Imaging Hyperspectra." Intelligent Automation & Soft Computing 18.8 (2012): 1111-1120. Crossref. Web.

Zhao J. Spectroscopy and Spectral Analysis

Zhou H. Remote Sensing Information

Zhu X. Chinese Journal of Applied Ecology

Zhu X. Spectroscopy and Spectral Analysis


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present


TSI Press
18015 Bullis Hill
San Antonio, TX 78258 USA
PH: 210 479 1022
FAX: 210 479 1048