Discriminating the origin of basil seeds (Ocimum basilicum L.) using hyperspectral imaging analysis

Ji Young Choi, Suhyeon Heo, Suin Bae, Jiyoon Kim, Kwang Deog Moon

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Hyperspectral imaging was used to study basil seeds and discriminate their origins (Singapore, India, Pakistan, or Vietnam). Normalization was the most effective method of preprocessing. The dominant wavelengths that were useful in classifying the basil seeds were approximately 1449–1457 nm, 1242–1254 nm, 1380 nm and 1696 nm (associated with moisture content, crude lipid content, total phenolic compounds, and fatty acids). Colour values were very similar between seeds of different origins and did not provide a good basis for discrimination. However, the moisture content and crude lipid content values significantly differed between groups, with predicted R2 values of 0.9888 and 0.9753, respectively, from the partial least squares regression model. Therefore, it is possible to discriminate among basil seeds using hyperspectral imaging analysis. This approach can be applied to discrimination technology to identify other agricultural products in the future.

Original languageEnglish
Article number108715
JournalLWT
Volume118
DOIs
StatePublished - Jan 2020

Keywords

  • Basil (Ocimum basilicum L.)
  • Crude lipid content
  • Discrimination
  • Hyperspectral imaging

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