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Separating in-shell pistachio nuts from kernels using impact vibration analysis

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Abstract

A sorting system has been developed for the separation of small in-shell pistachio nuts from kernels without shells on the basis of vibrations generated when moving samples strike a steel plate. Impacts between the steel plate and the hard shells, as measured using an accelerometer attached to the bottom of the plate, produce higher frequency signals than impacts between the plate and the kernels. Signal amplitudes, on the other hand, were highly variable and by themselves were not useful for the separation of samples. An algorithm was developed using both amplitude and frequency information to classify the signals. The algorithm activated an air nozzle to divert in-shell nuts away from the kernel stream. A prototype sorter was tested at throughput rates of 0.33, 10, 20, and 40 nuts per second using a mix of 10% in-shell and 90% kernels. At the lowest throughput rate, classification accuracies were 96% for in-shell nuts and 99% for kernels. For throughput rates between 10 and 40 nuts/s, correct classification ranged from 84 to 90% for in-shell nuts. For kernels, accuracy was 95% at 10 and 20 nuts/s and 89% at 40 nuts/s.

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Correspondence to Ron P. Haff.

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Haff, R.P., Pearson, T.C. Separating in-shell pistachio nuts from kernels using impact vibration analysis. Sens. & Instrumen. Food Qual. 1, 188–192 (2007). https://doi.org/10.1007/s11694-007-9020-2

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  • DOI: https://doi.org/10.1007/s11694-007-9020-2

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