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Proceedings Paper

Study on the change law of hyperspectral data and pigments for rice in mature process
Author(s): Jingfeng Huang; Yanlin Tang; Renchao Wang
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Paper Abstract

The hyperspectral reflectances of the canopy, the sword leaf, the third unfolding leaf from the top and ear of the main stem of two varieties of rice are measured by a ASD FieldSpec Pro FR in field and indoor under 3 nitrogen support levels in mature process. The concentrations of chlorophyll and carotenoid of leaves and ears corresponding to the spectra were determined by biochemical method. The spectral differences are significant for the canopy and leaves of rice under differet nitrogen support level, and the concentrations of chlorophyll and carotenoid of leaves increase with the increasing of nitrogen applying. There exist significant differences for the pigment concentrations of the leaves of rice under different nitrogen levels. The spectral reflectances of the canopy are gradually getting bigger in the visible region and smaller in the near infrared region as the growth stage goes on. 'Blue shift' phenomena for the spectra red edge position of the canopy, leaves and ears were proved. The concentrations of chlorophyll and carotenoid of leaves and ears are very significantly correlative to the spectral vegetation indices VI1(= R990/R553), VI2(=R1200/R553), VI3(=R750/R553), VI4(=R670/R440), VI5(= R553/R670), PRVI(=R800/R553), PSSRa, PSNDa and λred (the red edge position). The results show that these VIs can be used to estimate the concentrations of chlorophyll and carotenoid of leaves and ears of rice.

Paper Details

Date Published: 22 December 2003
PDF: 10 pages
Proc. SPIE 5153, Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture, (22 December 2003); doi: 10.1117/12.504699
Show Author Affiliations
Jingfeng Huang, Zhejiang Univ. (China)
Yanlin Tang, Zhejiang Univ. (China)
Renchao Wang, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 5153:
Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture
Wei Gao; David R. Shaw, Editor(s)

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