Cooperative combination of LIBS-based elemental analysis and near-infrared molecular fingerprinting for enhanced discrimination of geographical origin of soybean paste. (15th January 2023)

• Record Type: Journal Article
• Authors: Jeong, Seongsoo; Seol, Daun; Kim, Hyang; Lee, Yonghoon; Nam, Sang-Ho; An, Jae-Min; Chung, Hoeil
• Is Part Of: Food chemistry. Volume 399(2023)
• Publication Date: 2023-01-15
• Subjects: Soybean paste -- Geographical origin -- Laser-induced breakdown spectroscopy -- Near-infrared spectroscopy -- Two-trace two-dimensional correlation analysis; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2022.133956
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: A strategy able to enhance discrimination of geographical origin of soybean paste was demonstrated. So, LIBS-based elemental analysis and NIR molecular fingerprinting were cooperatively combined. When the areas of C and Ca LIBS peaks were used as the inputs for LDA, the accuracy was 95.4%. When the PC scores of NIR 2T2D slice spectra were adopted, the accuracy was 92.5%. When the ratios of C/Ca peaks and the PC scores were combined, the accuracy became superior, 99.6%. 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 (AC ) and Ca (ACa ) 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 ACa /AC and the 2nd PC scores of the samples were combined together, the accuracy improved to 99.6%.