作者: Misun Kang
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摘要: New, rapid techniques to quantify the different pools of soil organic matter (SOM) are needed improve our understanding dynamics and spatio-temporal variability SOM in terrestrial ecosystems. In this study, total carbon (TOC) oxidizable (OCWB) fraction were calibrated predicted by mid- near-DRIFT spectroscopy combination with partial least squares (PLS) regression method. PLS is a multivariate calibration method that can decompose spectral data (X) property (Y) into new smaller set latent variables their scores best describe all variance data. Oxidizable content was measured modified Walkley-Black method, analyzer. The floodplain Blackland Prairie soils Texas used for prediction TOC OCWB using spectroscopy. Floodplain mainly composed quartz kaolinite, whereas contain high concentrations smectitic clays low carbonate minerals. 68 samples from two sites varied between 0.19 4.36 wt.% C, 26 range 0.05 1.33 C. successfully correlation mid-IR spectra (r = 0.96, RMSEV 0.32 calibration; r 0.93, RMSEP 0.44 prediction) about same as near-IR result 0.95, 0.37; 0.42). Therefore, we also use mid-infrared region quantification soils. PLS1 model 0.92) more accurate than PLS2 0.90). models showed better univariate square method(r 0.83) This study shows (PLS1) mid-and neat be predict both fast routine quantitative