Infrared spectroscopy has the potential to rapidly analyse soil water-dissolved carbon and amino sugars. In this study, mid-infrared (MIR) and near-infrared (NIR) spectra collected from soil water extracts or from bulk soils were analysed with partial least squares regression (PLSr) to estimate the concentrations of water-dissolved carbon and amino sugars in diverse agricultural soils collected from five field sites in two western and two eastern Canadian provinces. The MIR-PLSr models developed from soil water extract spectra estimated hot-water (100 °C) dissolved carbon (HWDC) [R² = 0.97–0.70, ratio of prediction to deviation (RPDp) = 6.13–1.83] well, but the MIR-PLSr models did not estimate cold-water (21 °C) dissolved carbon (CWDC) well (R² = 0.82–0.50, RPDp = 2.35–1.42). The model estimates of HWDC at the multisite scale (all samples together) and for the two western Canada sites (R² = 0.97–0.93, RPDp = 6.13–3.68) surpass the modal estimates for the three eastern Canadian sites (R² = 0.81–0.70, RPDp = 2.28–1.83). The MIR- and NIR-PLSr models derived from bulk soil spectra both estimated HWDC well at the multisite scale (R² = 0.91–0.88, RPDp = 3.32–2.90) and for the western Canada sites (R² = 0.90–0.87, RPDp = 3.18–2.96). Models developed from hot-water extract spectra and bulk soil spectra resulted in poor estimates of soil amino sugars (R² = 0.74–0.21, RPDp = 1.99–1.12), except for the approximate quantitative estimation of muramic acid by models based on soil spectra at the western and the multisite scale (R² = 0.82–0.80, RPDp = 2.33–2.21). We concluded that MIR and NIR models at regional and multisite scales can be used as a tool to monitor HWDC but that additional research is required for estimating soil amino sugars.