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Hyperspectral imaging for predicting the allicin and soluble solid content of garlic with variable selection algorithms and chemometric models.

Anisur RahmanMohammad A FaqeerzadaByoung-Kwan Cho
Published in: Journal of the science of food and agriculture (2018)
The present study clearly demonstrates that hyperspectral imaging combined with an appropriate chemometrics method can potentially be employed as a fast, non-invasive method to predict the allicin and SSC in garlic. © 2018 Society of Chemical Industry.
Keyphrases
  • high resolution
  • machine learning
  • deep learning