The aim of this research was to assess the contents of mineral elements in oat flour using laser-induced breakdown spectroscopy (LIBS) that was integrated with iterative discrete wavelet transform (IDWT) algorithm. By using LIBS in the IDWT domain, the effects of low-frequency baseline and high-frequency noise on LIBS signals were greatly suppressed. The IDWT-LIBS is thus capable of accurately quantifying mineral elements in the presence of an uncontrolled matrix of oat flour. To validate the IDWT-LIBS ­method, oat samples with various Ca, Mg, and K concentrations were measured, and their characteristic signals were linearly dependent on their concentrations, with an R2 being above 0.98. The limits of detection of these elements were determined as 20 ppm. The results obtained by LIBS were in reasonable agreement with those obtained by inductively coupled plasma optical emission spectroscopy (ICP-OES), indicating that IDWT-LIBS is a promising tool for the real-time quantification of mineral elements in oat flour samples.