Identification of offal adulteration in beef by laser induced breakdown spectroscopy (LIBS)

• Published in: Meat science 2018-04, Vol.138, p.28-33
• Main Authors: Velioglu, Hasan Murat, Sezer, Banu, Bilge, Gonca, Baytur, Süleyman Efe, Boyaci, Ismail Hakki
• Format: Article
• Language: English
• Subjects: Animals; Beef; Cattle; Food Contamination - analysis; Lasers; Least-Squares Analysis; LIBS; Meat Products - analysis; Multivariate Analysis; Offal adulteration; PCA; PLS; Principal Component Analysis; Red Meat; Spectrum Analysis - methods; Spectrum Analysis - veterinary
• ISSN: 0309-1740; 1873-4138
• DOI: 10.1016/j.meatsci.2017.12.003

Minced meat is the major ingredient in sausages, beef burgers, and similar products; and thus it is the main product subjected to adulteration with meat offal. Determination of this kind of meat adulteration is crucial due to religious, economic and ethical concerns. The aim of the present study is to discriminate the beef meat and offal samples by using laser induced breakdown spectroscopy (LIBS). To this end, LIBS and multivariate data analysis were used to discriminate pure beef and offal samples qualitatively and to determine the offal mixture adulteration quantitatively. In this analysis, meat samples were frozen and LIBS analysis were performed. The results indicate that by using principal component analysis (PCA), discrimination of pure offal and offal mixture adulterated beef samples can be achieved successfully. Besides, adulteration ratio can be determined using partial least square analysis method (PLS) with 0.947 coefficient of determination (R2) and 3.8% of limit of detection (LOD) values for offal mixture adulterated beef samples. •Discrimination of offal from beef meat was successfully determined by using laser induced breakdown spectroscopy (LIBS).•Offal adulteration was quantified by using LIBS.•Partial Least Squares methods were used for analysis of the collected LIBS data.•Inductively Coupled Plasma Optical Emission Spectrometer was used as reference methods of elemental content analysis.