Abstract
Hazelnuts with damaged or cracked shells are more prone to infection with aflatoxin producing molds (Aspergillus flavus). These molds can cause cancer. In this study, we introduce a new approach that separates damaged/cracked hazelnut kernels from good ones by using time-frequency features obtained from impact acoustic signals. The proposed technique requires no prior knowledge of the relevant time and frequency locations. In an offline step, the algorithm adaptively segments impact signals from a training data set in time using local cosine packet analysis and a Kullback-Leibler criterion to assess the discrimination power of different segmentations. In each resulting time segment, the signal is further decomposed into subbands using an undecimated wavelet transform. The most discriminative subbands are selected according to the Euclidean distance between the cumulative probability distributions of the corresponding subband coefficients. The most discriminative subbands are fed into a linear discriminant analysis classifier. In the online classification step, the algorithm simply computes the learned features from the observed signal and feeds them to the linear discriminant analysis (LDA) classifier. The algorithm achieved a throughput rate of 45 nuts/s and a classification accuracy of 96% with the 30 most discriminative features, a higher rate than those provided with prior methods.
Highlights
Tree nuts are extensively used in the food industry
Each hazelnut is dropped on the metal plate and the resulting acoustic signal consisting of 768 time samples is recorded
The adaptation in time and frequency is achieved by combining local cosine packets and an undecimated wavelet transform
Summary
Tree nuts are extensively used in the food industry. Environmental conditions and processing procedures may decrease nut quality by causing cracks or damage to the shell. Nuts with shell damage should be separated from nuts with regular shells. This same problem affects many different types of tree nuts such as almonds, pecans, hazelnuts, pistachio nuts, and so on. Initial attempts at separation of fungal damaged food items from undamaged ones go back to the studies of Pearson [2]. Pearson showed that most the aflatoxin contaminated pistachios are either caused by bird damage or insects before harvesting or due to early split. After removing stained pistachio nuts from unstained ones, the aflatoxin contamination level of pistachio nut is reduced from 4.8–8.6 range to 0.04–2.5 ppb [4]
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