Non-destructive discrimination of Illicium verum from poisonous adulterant using Vis/NIR hyperspectral imaging combined with chemometrics

Abstract Poisonous Illicium lanceolatum A. C. Smith was found mixed with Illicium verum in the postharvest stage, which was difficult to separate the two species with naked eyes, especially broken samples and fallen follicles. A Vis/NIR hyperspectral imaging (HSI) system with wavelength range between 400 and 1000 nm was used as a non-destructive method to distinguish the two species with the purpose of safety control for Illicium verum. Firstly, spectral comparison and explanatory PCA was conducted to prove the discriminability between the two species in either face-up or back-up placement position, and a good clustering effect for I. lanceolatum samples was discovered. Then, linear partial least squares discriminant analysis (PLSDA) and nonlinear support vector machine (SVM) were developed to classify the two species based on full-wavelength, key wavelengths selected by successive projections algorithm (SPA) and regression coefficients (RC) and the most contributing principal components, in which SPA-PLSDA was selected as the most effective model (CCRc = 100%, CCRv = 96.88% and CCRcv = 98.44%). Furthermore, three forms (i.e., intact, broken and fallen follicle) of samples with different arrangements and two placements (face-up and back-up) were used to verify the applicability of the enhanced model. Correct classification rate (CCR) of the three independent tests were satisfactory (CCRset1 = 98.44%, CCRset2 = 100% and CCR set3 = 95.83%), and the sensitivity of I. verum (≥91.67%) and I. lanceolatum (100%) also proved that all I. lanceolatum could be identified using HSI technique, which establishes a theoretical and modelling foundation for the development of high-throughput online sorting equipment in future.

• Publication year

  2020

• Venue

  Infrared Physics & Technology

• Publication date

  2020-12-01

• Fields of study

  Mathematics, Chemistry, Environmental Science

• Identifiers
  DOI 10.1016/J.INFRARED.2020.103509
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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