Next Article in Journal
KLUM: An Urban VNIR and SWIR Spectral Library Consisting of Building Materials
Next Article in Special Issue
Eco-Friendly Estimation of Heavy Metal Contents in Grapevine Foliage Using In-Field Hyperspectral Data and Multivariate Analysis
Previous Article in Journal
Hyperspectral Endmember Extraction Using Spatially Weighted Simplex Strategy
Previous Article in Special Issue
Study of a High Spectral Resolution Hyperspectral LiDAR in Vegetation Red Edge Parameters Extraction
 
 
Article

Estimating Peanut Leaf Chlorophyll Content with Dorsiventral Leaf Adjusted Indices: Minimizing the Impact of Spectral Differences between Adaxial and Abaxial Leaf Surfaces

1
Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
2
Faculty of Science, University of Technology Sydney, Sydney, NSW 2007, Australia
3
School of Geography and Environmental Science, University of Southampton, Highfield, Southampton, SO17 1BJ, UK
4
Agronomy College, Shenyang Agricultural University, Shenyang 110866, China
5
Ministry of Agriculture Key Laboratory of Plant Nutrition and Fertilizer, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Remote Sens. 2019, 11(18), 2148; https://doi.org/10.3390/rs11182148
Received: 16 August 2019 / Revised: 7 September 2019 / Accepted: 11 September 2019 / Published: 15 September 2019
(This article belongs to the Special Issue Hyperspectral Remote Sensing of Agriculture and Vegetation)
Relatively little research has assessed the impact of spectral differences among dorsiventral leaves caused by leaf structure on leaf chlorophyll content (LCC) retrieval. Based on reflectance measured from peanut adaxial and abaxial leaves and LCC measurements, this study proposed a dorsiventral leaf adjusted ratio index (DLARI) to adjust dorsiventral leaf structure and improve LCC retrieval accuracy. Moreover, the modified Datt (MDATT) index, which was insensitive to leaves structure, was optimized for peanut plants. All possible wavelength combinations for the DLARI and MDATT formulae were evaluated. When reflectance from both sides were considered, the optimal combination for the MDATT formula was ( R 723 R 738 ) / ( R 723 R 722 ) with a cross-validation R2cv of 0.91 and RMSEcv of 3.53 μg/cm2. The DLARI formula provided the best performing indices, which were ( R 735 R 753 ) / ( R 715 R 819 ) for estimating LCC from the adaxial surface (R2cv = 0.96, RMSEcv = 2.37 μg/cm2) and ( R 732 R 754 ) / ( R 724 R 773 ) for estimating LCC from reflectance of both sides (R2cv = 0.94, RMSEcv = 2.81 μg/cm2). A comparison with published vegetation indices demonstrated that the published indices yielded reliable estimates of LCC from the adaxial surface but performed worse than DLARIs when both leaf sides were considered. This paper concludes that the DLARI is the most promising approach to estimate peanut LCC. View Full-Text
Keywords: leaf chlorophyll content; DLARI; MDATT; adaxial; abaxial; spectral reflectance; peanut leaf chlorophyll content; DLARI; MDATT; adaxial; abaxial; spectral reflectance; peanut
Show Figures

Graphical abstract

MDPI and ACS Style

Xie, M.; Wang, Z.; Huete, A.; Brown, L.A.; Wang, H.; Xie, Q.; Xu, X.; Ding, Y. Estimating Peanut Leaf Chlorophyll Content with Dorsiventral Leaf Adjusted Indices: Minimizing the Impact of Spectral Differences between Adaxial and Abaxial Leaf Surfaces. Remote Sens. 2019, 11, 2148. https://doi.org/10.3390/rs11182148

AMA Style

Xie M, Wang Z, Huete A, Brown LA, Wang H, Xie Q, Xu X, Ding Y. Estimating Peanut Leaf Chlorophyll Content with Dorsiventral Leaf Adjusted Indices: Minimizing the Impact of Spectral Differences between Adaxial and Abaxial Leaf Surfaces. Remote Sensing. 2019; 11(18):2148. https://doi.org/10.3390/rs11182148

Chicago/Turabian Style

Xie, Mengmeng, Zhongqiang Wang, Alfredo Huete, Luke A. Brown, Heyu Wang, Qiaoyun Xie, Xinpeng Xu, and Yanling Ding. 2019. "Estimating Peanut Leaf Chlorophyll Content with Dorsiventral Leaf Adjusted Indices: Minimizing the Impact of Spectral Differences between Adaxial and Abaxial Leaf Surfaces" Remote Sensing 11, no. 18: 2148. https://doi.org/10.3390/rs11182148

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop