Mid-infrared spectroscopy for rapid assessment of soil properties after land use change from pastures to Eucalyptus globulus plantations
Madhavan, DB and Kitching, M and Mendham, DS and Weston, CJ and Baker, TG, Mid-infrared spectroscopy for rapid assessment of soil properties after land use change from pastures to Eucalyptus globulus plantations, Journal of Environmental Management, 175 pp. 67-75. ISSN 0301-4797 (2016) [Refereed Article]
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 (R2) exceeding 0.91 and minimum root-mean-square error (RMSE) of calibration [TOC (R2 = 0.95, RMSE = 0.36), Total N (R2 = 0.96, RMSE = 0.10), C/N ratio (R2 = 0.92, RMSE = 0.14) and Total P (R2 = 0.91, RMSE = 0.06)]. The calibration models had reasonable predictions for MBC (R2 = 0.66, RMSE = 0.07) and MBN (R2 = 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 (R2 = 0.92, RMSE = 0.40) and Total N (R2 = 0.91, RMSE = 0.12), but less so for C/N ratio (R2 = 0.80, RMSE = 0.35), MBC (R2 = 0.70, RMSE = 0.08) and Total P (R2 = 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.
partial least squares regression, total organic carbon, soil nitrogen, microbial biomass, calibration model, forest plantation