title: 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.
authors.affiliation: School of Ecosystem and Forest Sciences, The University of Melbourne, 500 Yarra Boulevard, Richmond, VIC 3121, Australia. Electronic address: dineshbm@unimelb.edu.au.
authors.forename: Dinesh B
authors.initials: DB
authors.lastname: Madhavan
authors.affiliation: Agriculture Research Division, Department of Economic Development, Jobs, Transport and Resources, Terrace 4, Ernest Jones Drive, Macleod 3085, Australia.
authors.forename: Matt
authors.initials: M
authors.lastname: Kitching
authors.affiliation: CSIRO Land and Water, 15 College Road, Sandy Bay, TAS 7005, Australia.
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Mendham
authors.affiliation: School of Ecosystem and Forest Sciences, The University of Melbourne, 4 Water Street, Creswick, VIC 3363, Australia.
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Weston
authors.affiliation: School of Ecosystem and Forest Sciences, The University of Melbourne, 500 Yarra Boulevard, Richmond, VIC 3121, Australia.
authors.forename: Thomas G
authors.initials: TG
authors.lastname: Baker
mesh_terms: D000383:Agriculture; D001315:Australia; D018533:Biomass; D002138:Calibration; D002244:Carbon / Q000032:analysis; D004784:Environmental Monitoring / Q000379:methods*; D005052:Eucalyptus; D016018:Least-Squares Analysis; D009584:Nitrogen / Q000032:analysis; D010758:Phosphorus / Q000032:analysis; D012987:Soil / Q000737:chemistry*; D013055:Spectrophotometry, Infrared
chemical_list: D012987:Soil; D010758:Phosphorus; D002244:Carbon; D009584:Nitrogen
keywords: Calibration model; Forest plantation; Microbial biomass; Partial least squares regression; Soil nitrogen; Total organic carbon