Rapid Determination of Aflatoxin B1 Contamination in Peanut Oil by Fourier Transform Near-Infrared Spectroscopy

Abstract

Aflatoxin B1 (AFB1) contamination in peanut oil brings about a significant threat to human health. A method based on Fourier transform near-infrared (FT-NIR) spectroscopy was developed for qualitative and quantitative analysis of AFB1 contamination in peanut oil. A total of 94 samples were collected in the transmission mode and processed by a derivative and smoothing filter. Principal component analysis (PCA), discriminant analysis (DA), and partial least squares regression (PLS) were applied to establish the qualitative and quantitative analysis models. It was demonstrated that the qualitative model could distinguish effectively between the positive and negative samples with identification accuracy up to 100%. The correlation coefficient (R2), the root mean square error of calibration (RMSCE), and the relative percent deviation (RPD) for the quantitative model were 0.951, 3.87%, and 4.52, respectively. There was a good linear relationship between the predicted and reference concentrations of the samples with a significant correlation coefficient of 0.981. The qualitative and quantitative analysis models developed in this work may provide reference for researchers engaged in nondestructive testing of food and agricultural products.