Artificial neural network-facilitated V2C MNs-based colorimetric/fluorescence dual-channel biosensor for highly sensitive detection of AFB1 in peanut

In this work, V 2 C Mxene nano-enzyme materials (V 2 C MNs) with excellent peroxidase-like activity and fluorescence quenching performance were prepared, and it was modified using 6-carboxyfluorescein-labelled aptamers (ssDNA-FAM) to construct a novel dual-mode sensor V 2 C@ssDNA-FAM, with detection limits of 0.0477 ng mL −1 and 0.2789 ng mL −1 of fluorescence (linear range of 0.1–550 ng mL −1 ) and colorimetric (linear range of 1–1000 ng mL −1 ) modes, respectively. Meanwhile, an ANN intelligent detection platform has been constructed, which could automatically track and analyze the fluorescence and colorimetric signal of the detection system through machine learning and immediately obtain the AFB 1 concentration, and the detection limits of the fluorescence (linear range of 0.1–500 ng mL −1 ) and colorimetric (linear range of 1–800 ng mL −1 ) channels of it were 0.0905 ng mL −1 and 0.6845 ng mL −1 , respectively. The recovery rates of fluorescence, colorimetric sensing detection and ANN-assisted fluorescence and colorimetric sensing detection of real samples ranged from 95.40% to 101.76%. The method constructed in this work was superior to most existing literature reports and had great potential for application in the field of food quality testing.