Multivariate calibrations of concentrations of C, Mn, Si, Cr, Ni and Cu have been developed by the partial least squares method for 31 to 39 standard samples of low-alloy steels using low-resolution emission spectra (190-440 nm, resolution 0.4 nm, step 0.1 nm). Three methods of spectral variables selection are considered: a method of ranking spectral variables by their correlation coefficient with the value of the calibrated parameter, a successive projection algorithm and an original modification of searching combination moving windows. The partial least squares model with the spectral variables selection by the method of the searching combination moving windows for C is quantitative: the root mean square error is 0.004%, the residual predictive deviation in the test dataset is 23.4 in the concentration range 0.13 to 0.43%. Calibrations of Mn (0.04% and 5.2 in the range of 0.47-1.15%), Si (0.003% and 20.7 in the range of 0.15-0.33%), Cr (0.04% and 3.1 in the range of 0.09-0.43%) and Ni (0.01% and 4.8 in the range of 0.05-0.25%) are also quantitative. For Cu in the concentration range of 0.06-0.26%, calibration is qualitative (0.04% and 1.4). Keywords: laser induced breakdown spectroscopy, multivariate calibration, partial least squares, low-alloy steels