Comparison of the Laser Backscattering and Digital Imaging Techniques on Detection of α-Solanine in Potatoes

Journal Title: Journal of Agricultural Machinery - Year 2020, Vol 10, Issue 1

Abstract

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.

Authors and Affiliations

S. Babazadeh, P. Ahmadi Moghaddam, A. Sabatyan, F. Sharifian

Keywords

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  • EP ID EP717955
  • DOI https://doi.org/10.22067/jam.v10i1.79800
  • Views 53
  • Downloads 0

How To Cite

S. Babazadeh, P. Ahmadi Moghaddam, A. Sabatyan, F. Sharifian (2020). Comparison of the Laser Backscattering and Digital Imaging Techniques on Detection of α-Solanine in Potatoes. Journal of Agricultural Machinery, 10(1), -. https://europub.co.uk/articles/-A-717955