Rapid Food Authentication Using a Portable Laser-Induced Breakdown Spectroscopy System

被引:12
作者
Wu, Xi [1 ]
Shin, Sungho [1 ]
Gondhalekar, Carmen [1 ,2 ]
Patsekin, Valery [1 ]
Bae, Euiwon [3 ]
Robinson, J. Paul [1 ,2 ]
Rajwa, Bartek [4 ]
机构
[1] Purdue Univ, Dept Basic Med Sci, W Lafayette, IN 47907 USA
[2] Purdue Univ, Weldon Sch Biomed Engn, W Lafayette, IN 47907 USA
[3] Purdue Univ, Sch Mech Engn, W Lafayette, IN 47907 USA
[4] Purdue Univ, Bindley Biosci Ctr, W Lafayette, IN 47907 USA
关键词
authentication; LIBS; spectroscopy; food fraud; FRAUD VULNERABILITY; CLASSIFICATION; WHEAT; LIBS; BEEF; MEAT; IDENTIFICATION; ADULTERATION; CHEMOMETRICS; PESTICIDES;
D O I
10.3390/foods12020402
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Laser-induced breakdown spectroscopy (LIBS) is an atomic-emission spectroscopy technique that employs a focused laser beam to produce microplasma. Although LIBS was designed for applications in the field of materials science, it has lately been proposed as a method for the compositional analysis of agricultural goods. We deployed commercial handheld LIBS equipment to illustrate the performance of this promising optical technology in the context of food authentication, as the growing incidence of food fraud necessitates the development of novel portable methods for detection. We focused on regional agricultural commodities such as European Alpine-style cheeses, coffee, spices, balsamic vinegar, and vanilla extracts. Liquid examples, including seven balsamic vinegar products and six representatives of vanilla extract, were measured on a nitrocellulose membrane. No sample preparation was required for solid foods, which consisted of seven brands of coffee beans, sixteen varieties of Alpine-style cheeses, and eight different spices. The pre-processed and standardized LIBS spectra were used to train and test the elastic net-regularized multinomial classifier. The performance of the portable and benchtop LIBS systems was compared and described. The results indicate that field-deployable, portable LIBS devices provide a robust, accurate, and simple-to-use platform for agricultural product verification that requires minimal sample preparation, if any.
引用
收藏
页数:18
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