Laser-induced breakdown spectroscopy as a reliable analytical method for classifying commercial cheese samples based...

Area of Science:

• Analytical Chemistry
• Food Science

Background:

• Cheese classification relies on various factors, including processing methods.
• Elemental composition can serve as a distinguishing marker for different cheese types.

Purpose of the Study:

• To evaluate laser-induced breakdown spectroscopy (LIBS) combined with chemometrics for classifying Kashar and processed cheese.
• To determine if elemental profiles can differentiate cheese types based on their manufacturing process.

Main Methods:

• Laser-induced breakdown spectroscopy (LIBS) was employed for elemental analysis.
• Chemometric methods, including Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), were utilized for data analysis.
• Inductively Coupled Plasma - Optical Emission Spectrometry (ICP-OES) and Atomic Absorption Spectroscopy (AAS) were used for comparative analysis.

Main Results:

• LIBS and chemometric analysis successfully discriminated between Kashar and processed cheese based on elemental profiles.
• PCA model achieved 97.02% explained variance in discriminating Kashar cheese.
• PLS-DA model demonstrated 100% prediction ability for Kashar samples.
• Partial Least Squares Regression (PLSR) models for Mg, Ca, Na, P, Zn, and K showed high accuracy for both cheese types.

Conclusions:

• LIBS coupled with chemometrics provides a rapid and effective method for cheese classification.
• This approach can serve as an easy-to-use monitoring system for quality control in the dairy industry.