The use of mid-infrared attenuated total reflectance (ATR) spectroscopy enables direct measurement of nitrate concentration in soil pastes, but strong interfering absorbance bands due to water and soil constituents limit the accuracy of straightforward determination. Accurate subtraction of the water spectrum improves the correlation between nitrate concentration and its nu3 vibration band around 1350 cm(-1). However, this correlation is soil-dependent, due mostly to varying contents of carbonate, whose absorbance band overlaps the nitrate band. In the present work, a two-stage method is developed: First, the soil type is identified by comparing the "fingerprint" region of the spectrum (800-1200 cm(-1)) to a reference spectral library. In the second stage, nitrate concentration is estimated using the spectrum interval that includes the nitrate band, together with the soil type previously identified. Three methods are compared for estimating nitrate concentration: integration of the nitrate absorbance band, cross-correlation with a reference spectrum, and principal component analysis (PCA) followed by a neural network. When using simple band integration, the use of soil specific calibration curves leads to determination errors ranging from 5.5 to 24 mg[N]/kg[dry soil] for the mineral soils tested. The cross-correlation technique leads to similar results. The combination of soil identification with PCA and neural network modeling improves the predictions, especially for soils containing calcium carbonate. Typical prediction errors for light non-calcareous soils are about 4 mg[N]/kg[dry soil], whereas for soils containing calcium carbonate they range from 6 to 20 mg[N]/kg[dry soil], which is less than four percent of the concentration range investigated.