Historically, our understanding of the soil and assessment of its quality and function has been gained through routine soil chemical and physical laboratory analysis. There is a global thrust towards the development of more time- and cost-efficient methodologies for soil analysis as there is a great demand for larger amounts of good quality, inexpensive soil data to be used in environmental monitoring, modelling and precision agriculture. Diffuse reflectance spectroscopy provides a good alternative that may be used to enhance or replace conventional methods of soil analysis, as it overcomes some of their limitations. Spectroscopy is rapid, timely, less expensive, non-destructive, straightforward and sometimes more accurate than conventional analysis. Furthermore, a single spectrum allows for simultaneous characterisation of various soil properties and the techniques are adaptable for ‘on-the-go’ field use. The aims of this paper are threefold: (i) compare the simultaneous predictions of a number of different soil properties in the visible (VIS) (400 – 700 nm), near infrared (NIR) (700 – 2500 nm), mid infrared (MIR) (2500 – 25000 nm) and the combined VIS-NIR-MIR to determine whether the combined information produces better predictions of soil properties than each of the individual regions; and (ii) deduce which of these regions may be best suited for simultaneous analysis of various soil properties and (iii.) use the spectral data for the assessment of the spatial variability of an agricultural field. In this instance we implemented partial least-squares regression (PLSR) to construct calibration models, which were independently validated for the prediction of various soil properties from the soil spectra. The soil properties looked at were soil pH_Ca, pH_w, lime requirement (LR), organic carbon (OC), clay, silt, sand, cation exchange capacity (CEC), exchangeable calcium (Ca), exchangeable aluminium (Al), nitrate-nitrogen (NO₃-N), available phosphorus (P_Col), exchangeable potassium (K) and electrical conductivity (EC). The accuracy of PLSR predictions in each of the spectral regions varied amongst properties, however, predictions using the MIR for pH, LR, OC, CEC, clay, silt and sand contents, P and EC were better. The NIR produced more accurate predictions for exchangeable Al and K than any of the ranges. There were only minor improvements in predictions of clay, silt and sand content.