Prediction of soil TN and TC at a farm-scale using VIS-NIR spectroscopy

Building cost-effective models is of academic and practical value for fast measurement of soil properties, especially at a farm-scale. The aim of this study is to build quantitative models for soil total nitrogen (TN) and total carbon (TC) using visible and near infrared (VIS-NIR) spectroscopy. Dried samples (n=122) collected from an experimental farm, at Silsoe, Bedfordshire, United Kingdom, were scanned from 350 to 2500 nm at 1-nm intervals. Samples were divided into a calibration set (75%) and an independent validation set (25%). A partial least squares regression (PLSR) with leave-one-out cross validation was carried out based on different spectral ranges. Result shows that the best predictions (R>0.90 and RPD>3.3) are achieved for TN using the VIS range (400-700nm) and for TC using the VIS-NIR range (400-2500nm). It is concluded that VIS-NIR spectroscopy coupled with PLSR can be adopted for the prediction of soil TN and TC at a farm-scale.