|
|
|
| Rapid Identification of Pure and Adulterated Meat by Wide Area Illumination Raman Scheme Coupled with Soft Independent Modeling of Class Analogy |
| XU Jige, HAN Ying, XIN Xin, SHI Xiju |
| 1. CSEPAT (Beijing) Technology Co. Ltd., Beijing 100029, China; 2. Beijing Customs District P. R. China, Beijing 100026, China |
|
|
|
|
Abstract Qualitative recognition models were established by using wide area illumination (WAI) Raman scheme and soft independent modeling of class analogy (SIMCA) for rapid identification of duck, lamb, pork and adulterated meat. The spectra of all samples were pre-processed by multiplicative scatter correction (MSC) and spectrometer noise reduction and wavelength calibration (SNRWC) method and then principal component analysis was implemented to observe the clustering trend. It turned out that most of the duck, lamb and pork samples as well as most of the lamb samples and adulterations were well separated. Finally, the qualitative classification models were established by using SIMCA. All validation samples were identified by the SIMCA model with an accuracy of 100%, including 37 meat samples from different species and geographical origins, as well as four adulterated and five unadulterated lamb samples. Therefore, the WAI Raman scheme coupled with chemometrics could distinguish among lamp, duck, and pork and adulterated lamb, and it proved to be more fast, convenient, without the need for any sample pretreatment compared with the routine method.
|
|
|
|
|
|
|
|
|
|
|
2020, Vol. 34 
