Paper
5 March 2018 Determination of the carmine content based on spectrum fluorescence spectral and PSO-SVM
Shu-tao Wang, Tao Peng, Qi Cheng, Gui-chuan Wang, De-ming Kong, Yu-tian Wang
Author Affiliations +
Proceedings Volume 10710, Young Scientists Forum 2017; 107101N (2018) https://doi.org/10.1117/12.2317529
Event: Young Scientists Forum 2017, 2017, Shanghai, China
Abstract
Carmine is a widely used food pigment in various food and beverage additives. Excessive consumption of synthetic pigment shall do harm to body seriously. The food is generally associated with a variety of colors. Under the simulation context of various food pigments’ coexistence, we adopted the technology of fluorescence spectroscopy, together with the PSO-SVM algorithm, so that to establish a method for the determination of carmine content in mixed solution. After analyzing the prediction results of PSO-SVM, we collected a bunch of data: the carmine average recovery rate was 100.84%, the root mean square error of prediction (RMSEP) for 1.03e-04, 0.999 for the correlation coefficient between the model output and the real value of the forecast. Compared with the prediction results of reverse transmission, the correlation coefficient of PSO-SVM was 2.7% higher, the average recovery rate for 0.6%, and the root mean square error was nearly one order of magnitude lower. According to the analysis results, it can effectively avoid the interference caused by pigment with the combination of the fluorescence spectrum technique and PSO-SVM, accurately determining the content of carmine in mixed solution with an effect better than that of BP.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shu-tao Wang, Tao Peng, Qi Cheng, Gui-chuan Wang, De-ming Kong, and Yu-tian Wang "Determination of the carmine content based on spectrum fluorescence spectral and PSO-SVM", Proc. SPIE 10710, Young Scientists Forum 2017, 107101N (5 March 2018); https://doi.org/10.1117/12.2317529
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Luminescence

Particle swarm optimization

Fluorescence spectroscopy

Error analysis

Detection and tracking algorithms

Statistical modeling

Evolutionary algorithms

Back to Top