Journal of Chemometrics

An important issue in adulteration and/or authentication of food products as well as other products using classification is optimization of the myriad of decisions needed for accurate assessments

2006

Scholarcy highlights

  • An important issue in adulteration and/or authentication of food products as well as other products using classification is optimization of the myriad of decisions needed for accurate assessments
  • A recently developed fusion approach that removes these decision issues is overviewed as applied to several food datasets based on spectral measurements
  • Highlighted are three datasets with two composed of midinfrared spectra, and the third was measured by inductively coupled plasma mass spectroscopy
  • A validation of a global deep learning model based on near-infrared spectroscopy for dry matter prediction in mango fruit is presented
  • It is recommended that PLS-DA is considered as a single algorithmic step of an overall classification strategy

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