Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils

Abstract

The potential of near infrared (NIR) reflectance spectroscopy to predict various physical, chemical and biochemical properties in Mediterranean soils from SE Spain was evaluated. Soil samples (n=393) were obtained by sampling thirteen locations during three years (2003-2005 period). These samples had a wide range of soil characteristics due to variations in land use, vegetation cover and specific climatic conditions. Biochemical properties also included microbial biomarkers based on phospholipid fatty acids (PLFA). Partial least squares (PLS) regression with cross validation was used to establish relationships between the NIR spectra and the reference data from physical, chemical and biochemical analyses. Based on the values of coefficient of determination (r2) and the ratio of standard deviation of validation set to root mean square error of cross validation (RPD), predicted results were evaluated as excellent (r2>0.90 and RPD>3) for soil organic carbon, Kjeldahl nitrogen, soil moisture, cation exchange capacity, microbial biomass carbon, basal soil respiration, acid phosphatase activity, β-glucosidase activity and PLFA biomarkers for total bacteria, Gram positive bacteria, actinomycetes, vesicular-arbuscular mycorrhizal fungi and total PLFA biomass. Good predictions (0.81<r2<0.90 and 2.5<RPD<3) were obtained for exchangeable calcium and magnesium, water soluble carbon, water holding capacity and urease activity. Resultant models for protozoa and fungi were not accurate enough to satisfactorily estimate these variables, only permitting approximate predictions (0.66<r2<0.80 and 2.0<RPD<2.5). Electrical conductivity, pH, exchangeable phosphorus and sodium, metabolic quotient and Gram negative bacteria were poorly predicted (r2<0.66 and RPD<2). Thus, the results obtained in this study reflect that NIR reflectance spectroscopy could be used as a rapid, inexpensive and non-destructive technique to predict some physical, chemical and biochemical soil properties for Mediterranean soils, including variables related to the composition of the soil microbial community composition.

On-line measurement of soil properties without direct spectral response in near infrared spectral range

“…Comparing with other studies reported in the literature under laboratory measurement condition (Shepherd and Walsh, 2002;Cohen et al, 2005;Viscarra Rossel and Behrens, 2010), the model performance for pH in the prediction set is among the best models (r 2 = 0.50- (Cozzolino and Moron, 2003;Groenigen et al, 2003;Udelhoven et al, 2003;Wetterlind et al, 2010). Almost the same results as those achieved in this study were reported by Dunn et al (2002) , 2006;Zornoza et al, 2008) and CEC (r 2 = 0.13-0.90; RMSEP = 1.22-10.43 cmol kg À1 ; RPD = 0.60-2.7) (e.g. Ben-Dor and Banin, 1995;Chang et al, 2001;Awiti et al, 2008).…”

“…literature, sodium (Na ex ) and potassium (K ex ) are among the most difficult properties to be measured with the NIR spectroscopy (Malley et al, 1999;Chang et al, 2001;Zornoza et al, 2008;Pirie et al, 2005;Dunn et al, 2002;Shepherd & Walsh, 2002;Islam et al, 2003;Volkan et al, 2010;. For the same soil property, laboratory vis-NIR methods achieved higher accuracy as compared to measurement under field soil conditions, particularly with on-line vis-NIR sensors Kuang et al, 2012).…”

The Effects of Drying Temperature on Nitrogen Concentration Detection in Calcium Soil Studied by NIR Spectroscopy

“…Figure 1f shows the spectra after 1st-Der processing, and the spectral resolution is increased. There is a large fluctuation around 1650 nm and a similar result can be found in Dalal's research [5].…”

Effect of the Continuum Removal in Predicting Soil Organic Carbon with Near Infrared Spectroscopy (NIRS) in the Senegal Sahelian Soils

“…Also, with the global warming, the promotion of management strategies which allow the storage of carbon in the soil and reduce emissions of carbon dioxide in the atmosphere is required [9]. In the international context, mathematical and statistical methods of prediction are increasingly tested in the soil properties analysis protocols in relation to spectroscopy data [10]- [15]. The possibility offered by spectroscopy to generate reflectance and luminance spectra in different wavelengths 250 -400 nm (ultraviolet; UV), 400 -700 nm (visible; VIS), 700 -2500 nm (near infrared; NIR), 2500 -25,000 nm (med infrared, MIR) allows an extraction of useful information about soil components at lower cost [16] [17].…”