Onaran, I.Pearson, T. C.Yardimci, Y.Çetin, A. Enis2016-02-082016-02-0820062151-0032http://hdl.handle.net/11693/23683Shell-to-kernel weight ratio is a vital measurement of quality in hazelnuts as it helps to identify nuts that have underdeveloped kernels. Nuts containing underdeveloped kernels may contain mycotoxin-producing molds, which are linked to cancer and are heavily regulated in international trade. A prototype system was set up to detect underdeveloped hazelnuts by dropping them onto a steel plate and recording the acoustic signal that was generated when a kernel hit the plate. A feature vector comprising line spectral frequencies and time-domain maxima that describes both the time and frequency nature of the impact sound was extracted from each sound signal and used to classify each nut by a support-vector machine. Experimental studies demonstrated accuracies as high as 97% in classifying hazelnuts with underdeveloped kernels.EnglishAflatoxinClassificationDetectionNutSoundArticle10.13031/2013.222772151-0040