Predictive performance of mobile vis-near infrared spectroscopy for key soil properties at different geographical scales by using spiking and data mining techniques

摘要: The development of accurate visible and near infrared (vis-NIR) spectroscopy calibration models for selected soil properties based on mobile measurements is essential for site specific soil management at fine sampling scale. The objective of the present study was to compare the mobile and laboratory prediction performance of vis-NIR spectroscopy for total nitrogen (TN), total carbon (TC) and soil moisture content (MC) of field soil samples based on single field (SFD), two-field dataset (TFD), UK national dataset (UND) and European continental dataset (ECD) calibration models developed with linear and nonlinear data mining techniques including spiking. Fresh soil samples collected from fields in the UK, Czech Republic, Germany, Denmark and the Netherlands were scanned with a fibre-type vis-NIR spectrophotometer (tec5 Technology for Spectroscopy, Germany), with a spectral range of 305–2200 nm. After …