Bilge, GoncaEseller, Kemal EfeBerberoglu, HalilSezer, BanuTamer, UgurBoyaci, Ismail HakkiDepartment of Electrical & Electronics Engineering2024-07-052024-07-05202151990-257310.1186/s41476-021-00164-92-s2.0-85114029870https://doi.org/10.1186/s41476-021-00164-9https://hdl.handle.net/20.500.14411/1708Berberoglu, Halil/0000-0002-2435-3631; Tamer, Ugur/0000-0001-9989-6123; ESELLER, KEMAL Efe/0000-0002-9758-4852; SEZER, Banu/0000-0002-0743-3453Laser induced breakdown spectroscopy (LIBS) is a rapid optical spectroscopy technique for elemental determination, which has been used for quantitative analysis in many fields. However, the calibration involving atomic emission intensity and sample concentration, is still a challenge due to physical-chemical matrix effect of samples and fluctuations of experimental parameters. To overcome these problems, various chemometric data analysis techniques have been combined with LIBS technique. In this study, LIBS was used to show its potential as a routine analysis for Na measurements in bakery products. A series of standard bread samples containing various concentrations of NaCl (0.025%-3.5%) was prepared to compare different calibration techniques. Standard calibration curve (SCC), artificial neural network (ANN) and partial least square (PLS) techniques were used as calibration strategies. Among them, PLS was found to be more efficient for predicting the Na concentrations in bakery products with an increase in coefficient of determination value from 0.961 to 0.999 for standard bread samples and from 0.788 to 0.943 for commercial products.eninfo:eu-repo/semantics/openAccessLaser induced breakdown spectroscopyArtificial neural networkPartial least squareBakery productsSodiumArticleQ4171WOS:000693260400001