The feasibility of detecting Aflatoxin B-1 (AFB(1)) in single maize kernel inoculated with Aspergillus flavus conidia in the field, as well as its spatial distribution in the kernels, was assessed using near-infrared hyperspectral imaging (HSI) technique. Firstly, an image mask was applied to a pixel-based image mosaic to remove background and shading. Secondly, bad lines in spectra imaging caused by inherent defects of Mercury Cadmium Telluride (MCT) detector were removed through an interactive analysis based on principal component analysis (PCA). Then a PCA procedure was carried out again on the cleaned image, key wavelengths such as 1729 and 2344 nm were shown clearly from the loading line plot of the seventh principal component (PC7). And the pixel of AFB(1) extracted from the 5-dimensional scatter plot space formed by five principal components (PCs) from PC4 to PC8 (especially PC7 and PC5) were taken as the input of the spectral angle mapper (SAM) classifier, accuracies of the three varieties of kernels reached 96.15%, 80%, and 82.61% respectively if kernels containing either high (>= 100 ppb) or low (<10 ppb) levels of aflatoxin. A slightly better test result could be got if the kernels placed with different germ orientation. Finally, the repeatability was verified using the fourth variety of kernels. (C) 2015 Elsevier Ltd. All rights reserved.