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

Seongsoo Jeong; Daun Seol; Hyang Kim; Yonghoon Lee; Sang-Ho Nam; Jae-Min An; Hoeil Chung

doi:10.1016/j.foodchem.2022.133956

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

Food Chem. 2023 Jan 15:399:133956. doi: 10.1016/j.foodchem.2022.133956. Epub 2022 Aug 17.

Authors

Seongsoo Jeong¹, Daun Seol¹, Hyang Kim², Yonghoon Lee³, Sang-Ho Nam⁴, Jae-Min An⁵, Hoeil Chung⁶

Affiliations

¹ Department of Chemistry and Research Institute for Convergence of Basic Science, Hanyang University, Seoul 04763, Republic of Korea.
² Plasma Spectroscopy Analysis Center, Mokpo National University, Jeonnam 58554, Republic of Korea.
³ Department of Chemistry, Mokpo National University, Jeonnam 58554, Republic of Korea; Plasma Spectroscopy Analysis Center, Mokpo National University, Jeonnam 58554, Republic of Korea.
⁴ Department of Chemistry, Mokpo National University, Jeonnam 58554, Republic of Korea; Plasma Spectroscopy Analysis Center, Mokpo National University, Jeonnam 58554, Republic of Korea. Electronic address: shnam@mokpo.ac.kr.
⁵ Division of Origin Identification, Experiment & Research Institute, National Agricultural Products Quality Management Service, Gimcheon 39660, Republic of Korea.
⁶ Department of Chemistry and Research Institute for Convergence of Basic Science, Hanyang University, Seoul 04763, Republic of Korea. Electronic address: hoeil@hanyang.ac.kr.

PMID: 36027807
DOI: 10.1016/j.foodchem.2022.133956

Abstract

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-dimensional (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%.

Keywords: Geographical origin; Laser-induced breakdown spectroscopy; Near-infrared spectroscopy; Soybean paste; Two-trace two-dimensional correlation analysis.

MeSH terms

Discriminant Analysis
Fabaceae*
Geography
Glycine max*
Principal Component Analysis
Spectroscopy, Near-Infrared / methods