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    ARTICLE

    Hyperspectral Reflectance Imaging for Detecting Typical Defects of Durum Kernel Surface

    Feng-Nong Chena,b#, Pu-Lan Chenc#, Kai Fana, Fang Chengd

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 351-358, 2018, DOI:10.1080/10798587.2017.1293927

    Abstract In recent years, foodstuff quality has triggered tremendous interest and attention in our society as a series of food safety problems. The hyperspectral imaging techniques have been widely applied for foodstuff quality. In this study, we were undertaken to explore the possibility of unsound kernel detecting (Triticum durum Desf), which were defined as black germ kernels, moldy kernels and broken kernels, by selecting the best band in hyperspectral imaging system. The system possessed a wavelength in the range of 400 to 1,000  nm with neighboring bands 2.73  nm apart, acquiring images of bulk wheat samples… More >

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