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Abstract Sampling density is a parameter that allows to identify the spatial variability of properties of interest in soils and is essential for precision agriculture practices, such as fertilizer application in variable rate. Soil sensors and spectroscopic techniques have been investigated and reported as promising tools, although showing some limitation in characterizing the chemical fertility of soils. One of the causes of the limitations is the way samples are prepared. Therefore, the aim of this work was to evaluate the effect of sieving and of drying temperature, on the determination of total nitrogen and phosphorus and potassium contents, by using Vis-NIR and Mid-Infrared spectroscopies. We found that Diffuse Reflectance Spectroscopy in the Visible and Near-Infrared region of the spectra shows better performance of the prediction models than of the Attenuated Total Reflectance Spectroscopy in the Mid-Infrared region. We did not identify significant influence of drying temperature neither of soil particle size on the predictive quality of the models generated via Vis-NIR spectroscopy; thus, the extra expenditure of time and cost for a more intense preparation of the soil samples would not be justifiable. In addition, we infer that the high prediction error may limit the applicability of spectroscopy for guiding the variable-rate application of fertilizers within the scope of precision agriculture. Highlights • Vis-NIR spectroscopy shows better performance than MIR spectroscopy. • Drying temperature does not influence the predictive quality of spectroscopic models. • Soil particles size shows minimal influence in the Vis-NIR model performance. • Prediction errors limit the applicability of spectroscopy on precision agriculture. [ABSTRACT FROM AUTHOR]