Mid-infrared spectroscopy for rapid assessment of soil properties after land use change from pastures to Eucalyptus globulus plantations

Abstract

There is an increasing demand for rapid and cost effective techniques to accurately measure the effects of land use change on soil properties. This study evaluated the ability of mid-infrared spectroscopy (MIRS) coupled with partial least squares regression (PLSR) to rapidly predict soil properties affected by land use change from agriculture (mainly pasture) to Eucalyptus globulus plantations in south-western Australia. We measured total organic carbon (TOC), total nitrogen (Total N), TOC/Total N (C/N ratio), microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and total phosphorus (Total P). The PLSR calibration models were developed using mid-infrared (MIR) spectra (4000 to 450 cm(-1)) and square root transformed measured soil data (n = 180) from 23 paired pasture and E. globulus plantation sites representing the soils and climate of E. globulus plantation estates in south-western Australia. The calibration models for TOC, Total N, C/N ratio and Total P showed excellent correlations between measured and predicted data with coefficient of determination (R(2)) exceeding 0.91 and minimum root-mean-square error (RMSE) of calibration [TOC (R(2) = 0.95, RMSE = 0.36), Total N (R(2) = 0.96, RMSE = 0.10), C/N ratio (R(2) = 0.92, RMSE = 0.14) and Total P (R(2) = 0.91, RMSE = 0.06)]. The calibration models had reasonable predictions for MBC (R(2) = 0.66, RMSE = 0.07) and MBN (R(2) = 0.63, RMSE = 0.06). The calibrated models were validated using soils from 8 independent paired pasture and E. globulus sites (n = 64). The validated predictions were excellent for TOC (R(2) = 0.92, RMSE = 0.40) and Total N (R(2) = 0.91, RMSE = 0.12), but less so for C/N ratio (R(2) = 0.80, RMSE = 0.35), MBC (R(2) = 0.70, RMSE = 0.08) and Total P (R(2) = 0.75, RMSE = 0.12). The results demonstrate the potential of MIRS-PLSR to rapidly, accurately and simultaneously determine several properties in land use change affected soils.

Keywords: Calibration model; Forest plantation; Microbial biomass; Partial least squares regression; Soil nitrogen; Total organic carbon.