Aflatoxin is a toxic metabolite widely existing in corn. In the present paper, the feasibility of detecting aflatoxin on corn kernel surface by hyperspectral imaging technology was verified. The corn called pioneer with the same shape is provided by Toxicology and Mycotoxin Research Unit. With methanol configuration, four different concentrations of aflatoxin solutions were prepared and dripped on every 30 corn kernels. Also other clean 30 kernels without aflatoxin dripped were prepared to be the control samples. Among the 150 kernel samples, 103 training samples and 47 validation samples were prepared randomly. Firstly, hyperspectral image in the range of 400 to 1 000 nm was collected .For eliminating the deviations in original spectrum, standard normal variate transformation (SNV) was adopted as pretreatment method. And then several optimum wavelengths were selected by the principle of minimum misdiagnosis rate. After that the selected optimum wavelengths were taken as the input of the Fisher discrimination analysis to discriminate the different concentrations of aflatoxin on the corn. Finally, the discrimination model based on four optimum wavelengths (812.42, 873.00, 900.36 and 965.00 nm) was built and the accuracy of the model was tested. Results indicate that the classification accuracy of calibration and validation set was 87.4% and 80.9% respectively. This method provides basis for designing the corresponding portable instrument and distinguishing aflatoxin produced by naturally metabolism in corn.