Detection method of aflatoxin B₁ in moldy maize based on hyperspectral feature selection

In order to investigate the feasibility of detecting aflatoxin B₁ in moldy maize using hyperspectral technique, 5 kinds of maize with different moldy degrees were selected as materials. Then the hyperspectral data of the 250 samples were obtained by the hyperspectral image acquisition system, which were preprocessed by multiplicative scatter correction (MSC). The characteristic wavelengths were selected by partial least squares regression (PLSR) coefficients, and 7 characteristic wavelengths were selected. And then Fisher discriminant analysis (FDA) was used to identify the moldy maize samples under full band and characteristic wavelength conditions, respectively. The result showed that the accuracy rate of the 5 kinds of moldy maize samples at the full band was between 85% and 88%, while the accuracy rates of the FDA at these characteristic wavelengths were higher than 98%. This indicated that the different moldy degrees of maize can be characterized by these characteristic wavelengths. The BP model was better than that of PLSR, and correlation coefficient and the root mean square error of the predictive set based on the BP model were 0.9999 and 0.1809, respectively. Therefore, it was feasible to detect aflatoxin B1 content from maize samples with different moldy degree by hyperspectral technology. And an important theoretical reference was also provided for other agricultural products. (authors)