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Proceedings Paper

Imaging spectroscopy for estimating sugarcane leaf nitrogen concentration
Author(s): Elfatih M. Abdel-Rahman; Fethi B. Ahmed; Maurits van den Berg
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Paper Abstract

Imaging spectroscopy can provide real-time high throughput information on growing crops. The spectroscopic data can be obtained from space-borne, air-borne and handheld sensors. Such data have been used for assessing the nutritional status of some field crops (maize, rice, barely, potato etc.). In this study a handheld FieldSpec 3 spectroradiometer in the 350 - 2500 nm range of the electromagnetic spectrum was evaluated for its use to estimate sugarcane leaf nitrogen concentrations. Sugarcane leaf samples from one variety viz., N19 of two age groups (4-5 and 6-7 months) were subjected to spectral and chemical measurements. Leaf reflectance data were collected under controlled conditions and leaf nitrogen concentration was obtained using an automated combustion technique (Leco TruSpec N). The potential of spectroscopic data for estimating sugarcane leaf nitrogen status was evaluated using univariate correlation and regression analyses methods with the first-order reflectance across the spectral range from 400 to 2500 nm. The variables that presented high correlation with nitrogen concentration were used to develop simple indices combining reflectances of 2-wavelengths. Simple linear regression was then used to select a model that yielded the highest R2. These were the R744 / R2142 index for the 4-5 months old cane crop and the (R2200 - R2025) / (R2200 + R2025) index for the 6-7 months old cane crop, with R2 of 0.74 and 0.87, respectively.

Paper Details

Date Published: 2 October 2008
PDF: 12 pages
Proc. SPIE 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X, 71040V (2 October 2008); doi: 10.1117/12.800221
Show Author Affiliations
Elfatih M. Abdel-Rahman, Univ. of KwaZulu-Natal (South Africa)
Fethi B. Ahmed, Univ. of KwaZulu-Natal (South Africa)
Maurits van den Berg, South African Sugarcane Research Institute (South Africa)


Published in SPIE Proceedings Vol. 7104:
Remote Sensing for Agriculture, Ecosystems, and Hydrology X
Christopher M. U. Neale; Manfred Owe; Guido D'Urso, Editor(s)

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