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 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.