Cooperative combination of LIBS-based elemental analysis and near-infrared molecular fingerprinting for enhanced discrimination of geographical origin of soybean paste

被引:18
作者
Jeong, Seongsoo [1 ]
Seol, Daun [1 ]
Kim, Hyang [3 ]
Lee, Yonghoon [2 ,3 ]
Nam, Sang-Ho [2 ,3 ,5 ,6 ]
An, Jae-Min [4 ]
Chung, Hoeil [1 ,5 ,6 ]
机构
[1] Hanyang Univ, Dept Chem, Seoul 04763, South Korea
[2] Mokpo Natl Univ, Dept Chem, Jeonnam 58554, South Korea
[3] Mokpo Natl Univ, Plasma Spect Anal Ctr, Jeonnam 58554, South Korea
[4] Expt & Res Inst, Natl Agr Prod Qual Management Serv, Div Origin Identificat, Gimcheon 39660, South Korea
[5] Hanyang Univ, Dept Chem, Seoul 04763, South Korea
[6] Mokpo Natl Univ, Dept Chem, Jeonnam 58554, South Korea
基金
新加坡国家研究基金会;
关键词
Soybean paste; Geographical origin; Laser-induced breakdown spectroscopy; Near-infrared spectroscopy; Two-trace two-dimensional correlation analysis; SPECTROSCOPY; IDENTIFICATION; DOENJANG; SAMPLES;
D O I
10.1016/j.foodchem.2022.133956
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Laser-induced breakdown spectroscopy (LIBS) and near-infrared (NIR) spectroscopy were combined to enhance discrimination of soybean paste samples according to geographical origin. Since element and organic component compositions of soybean pastes depend on soybean cultivation areas and fermentation conditions, utilization of two complementary spectroscopic signatures would be synergetic for the discrimination. When the areas of C (A(C)) and Ca (A(Ca)) peaks in the LIBS spectra were used as the inputs for linear discriminant analysis, the accuracy was 95.4%. The accuracy became 92.1%, when the principal component (PC) scores obtained by principal component analysis of the NIR spectra were employed. To enhance NIR discrimination, two-trace two-dimen-sional (2T2D) correlation analysis was adopted to recognize minute spectral differences. With using the 1st/2nd PC scores of 2T2D slice spectra, accuracy increased to 95.0%. When the ratios of A(Ca)/A(C) and the 2nd PC scores of the samples were combined together, the accuracy improved to 99.6%.
引用
收藏
页数:9
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