Comparison of the Laser Backscattering and Digital Imaging Techniques on Detection of α-Solanine in Potatoes
The overall objective of this research is to check the abilities of two non-destructive techniques, the digital imaging (DI) and laser light backscattering imaging (LLBI), on detection of α-solanine toxicant in potatoes. Potato samples were classified in healthy and toxic categories based on the amo...
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Autores principales: | , , , |
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Formato: | article |
Lenguaje: | EN FA |
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Ferdowsi University of Mashhad
2020
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Materias: | |
Acceso en línea: | https://doaj.org/article/52277c4d065f4d89a14facceb8805e9c |
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Sumario: | The overall objective of this research is to check the abilities of two non-destructive techniques, the digital imaging (DI) and laser light backscattering imaging (LLBI), on detection of α-solanine toxicant in potatoes. Potato samples were classified in healthy and toxic categories based on the amount of α-solanine. For quantifying α-solanine in potato tubers, high-performance liquid chromatography (HPLC) has been used. The results of classification showed that single layer perceptron neural networks can classify potatoes with the accuracies of 94.28% and 98.66% by DI and LLBI systems (Donald cultivar), respectively. It can be said that LLBI systems might take precedent over DI systems due to their high accuracy, rapidity, and industrial capability. |
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