Laser-induced breakdown spectroscopy as a reliable analytical method for classifying commercial cheese samples based on their cooking/ stretching process

Sezer B., ÖZTÜRK M., AYVAZ H., Apaydin H., BOYACI İ. H.

FOOD CHEMISTRY, vol.390, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 390
  • Publication Date: 2022
  • Doi Number: 10.1016/j.foodchem.2022.132946
  • Journal Name: FOOD CHEMISTRY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, EMBASE, Food Science & Technology Abstracts, MEDLINE, Metadex, Veterinary Science Database, Civil Engineering Abstracts
  • Çanakkale Onsekiz Mart University Affiliated: Yes


The present work evaluates the possibility of using laser-induced breakdown spectroscopy (LIBS) coupled with chemometric methods to classify cheese samples (namely Kashar cheese and processed cheese) based on their cooking/stretching process. Chemometric analysis of the data provided by LIBS and ICP-OES/AAS analyses made it possible to discriminate between the two cheese types regarding their elemental profiles. The principal component analysis model was able to discriminate the Kashar cheese with an explained variance of 97.02%. Furthermore, the partial least squares discriminant analysis model perfectly classified the Kashar samples with a prediction ability of 100%. Furthermore, calibration and validation models for Mg, Ca, Na, P, Zn, and K elements for both Kashar and processed cheese samples were developed using partial least square regression yielding high correlation coefficients and low root mean square errors. Overall, this study indicates that LIBS with chemometrics can be an easy-to-use and rapid monitoring system for cheese classification.