Pre etched Ag nanocluster as SERS substrate for the rapid quantification of AFB1 in peanut oil via DFT coupled multivariate calibration.

Abstract

The current study extends the use of surface-enhanced Raman spectroscopy (SERS) combined with density functional theory (DFT) and multivariate calibration towards the rapid quantification of aflatoxin B1 (AFB1) in peanut oil samples. It reports the design of pre etched Ag nanocluster as an active SERS substrate for quantifying AFB1, after being impregnated on its surface. The SERS spectra of AFB1@pre etched Ag nanocluster was recorded and its respective theoretical spectrum was calculated by density functional theory (DFT) to assign the characteristic peaks. The baseline drift and rotation effects were masked by the first-order derivative preprocessing method followed by multivariate calibration. The BP-AdaBoost model exhibited optimum prediction (Rp=0.9283 and 0.9332) ability over the concentration range 5-100 and 100-1000 ngmL-1, respectively. The limit of detection calculated was 5.0 ngmL-1 and the obtained recoveries were in the range from 90.4% to 113.1% in spiked peanut oil samples. Additionally, precision analysis revealed an RSD ca. 5%, suggesting the applicability of the pre etched Ag nanocluster SERS substrate towards AFB1 detection. Thus, the proposed SERS platform exploiting DFT and BP-AdaBoost model was found reproducible for the quantification of AFB1 in peanut oil.