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Proceedings Paper

Spectral feature characterization and water content prediction in soil using different containers
Author(s): Haiyan Song; Yong He; Gang Qin
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Paper Abstract

Near infrared reflectance spectroscopy offers the potential for rapid and cost-effective soil analysis. Unfortunately, their prediction model is valid to their sampling pretreatment and the experiment proceedings, and this is believed to be due to the influence of the physical properties of the soil sample and the geometric conditions of the sampling accessory. The objective of this study was to evaluate the influence of the container to soil spectra in a given distance and angle of the spectra detector, and their ability to soil water content prediction. Six petri dishes with different diameters and heights (d12.5cm, h2.2cm; d14.7cm, h2.9cm; d15.7cm, h2.8cm; dl0.4cm, h1.7cm; d9.3cm, hl.5cm; d9.7cm, hl.9cm) were applied for the analysis. A total of 106 soil samples were obtained in Zhejiang, Hangzhou and their spectral features and the water content were analyzed. Principal component analysis (PCA) - artificial neural network (ANN) was used to build prediction models with a calibration data set of 81 randomly chosen samples. The remaining 25 soil samples were used to valithte the prediction model. Accurate water content prediction was obtained when the diameter of the soil container was 12.5 cm with r = 0.91. The results were consistent with the geometric analysis.

Paper Details

Date Published: 27 October 2006
PDF: 7 pages
Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 604728 (27 October 2006); doi: 10.1117/12.710933
Show Author Affiliations
Haiyan Song, Zhejiang Univ. (China)
Yong He, Zhejiang Univ. (China)
Gang Qin, Shanxi Agricultural Univ. (China)

Published in SPIE Proceedings Vol. 6047:
Fourth International Conference on Photonics and Imaging in Biology and Medicine
Kexin Xu; Qingming Luo; Da Xing; Alexander V. Priezzhev; Valery V. Tuchin, Editor(s)

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