表面増強ラマン分光法と密度汎関数理論解析に基づく5つのB群ビタミン検出の迅速化

In this study, five B vitamins (vitamin B₁, vitamin B₂, vitamin B₆, nicotinamide and calcium pantothenate) were detected using surface-enhanced Raman spectroscopy (SERS) with colloidal gold nanoparticles, supported by density functional theory (DFT) analyses. The detection limits for the vitamins were determined as 0.028 (vitamin B₁), 0.31 (vitamin B₂), 1.71 (vitamin B₆), 0.102 (niacinamide) and 0.397 μg/mL (calcium pantothenate). For qualitative analysis, principal component analysis-linear discriminant analysis and orthogonal partial least squares (PLS)-discriminant analysis models were employed, achieving a prediction accuracy of 98%. Quantitative analysis was performed using sequential projection algorithm (SPA)-PLS and characteristic peak-PLS models. The results demonstrated that the SPA-PLS model provided superior accuracy for the quantitative analysis of vitamins B₁ and B₆, with prediction set correlation coefficients (Rp) of 0.959 and 0.962, and relative prediction deviations (RPDs) of 3.191 and 3.471, respectively. Meanwhile, the characteristic peak PLS model was more suitable for analyzing vitamin B₂ and calcium pantothenate, yielding Rp values of 0.953 and 0.974, and RPDs of 3.833 and 3.3667, respectively. A quantitative model for nicotinamide was established based on its characteristic peak at 1030 cm^-1, achieving an Rp of 0.943 and an RPD of 2.989. Using commercially available vitamin B₁ tablets as a case study, their vitamin B₁ content was detected via SERS technology. Our results indicated that the B₁ content of three different samples was 90% to 110% of the labeled values. In the spike recovery experiment, the recovery rate of vitamin B₁ ranged from 85% to 104%.