Publication date: 15 February 2017
Source:Geoderma, Volume 288
Author(s): K.R.M. Adeline, C. Gomez, N. Gorretta, J.-M. Roger
Laboratory Visible-Near Infrared (Vis-NIR) spectroscopy is a good alternative to costly physical and chemical soil analysis to estimate a wide range of soil properties. Various statistical methods relate soil Vis-NIR spectra to soil properties including partial least-squares regression (PLSR), the most common multivariate statistical technique in soil science. Most efforts are generally dedicated to the comparison of methodologies and their optimization for the estimation of soil properties. Instead, the focus of this paper is to assess the prediction of soil properties from laboratory Vis-NIR spectroscopy data in regards to spectral degradation. Consecutively, both spectra quality and PLSR models quality are analyzed across the definition of different spectral configurations, each one characterized by three parameters: the number of spectral bands, the spectral resolution and the spectral sampling interval. The originality of this work is to perform this study on four soil properties with different spectral absorption features due to their various physico-chemical interactions with soil substrate, namely: clay, free iron oxides, calcium carbonate (CaCO3 ) and pH. The initial database is composed of 1961 spectral bands, spectral resolutions of 3 and 103 , from 0.66 to 0.58 for pH and remained constant at 0.78 for iron), (2) the prediction performances decreased, but remained acceptable for clay, iron oxides and CaCO3 at spectral resolutions between 60 and 200
Source:Geoderma, Volume 288
Author(s): K.R.M. Adeline, C. Gomez, N. Gorretta, J.-M. Roger