4.6 Article

Garlic adulteration detection using NIR and FTIR spectroscopy and chemometrics

期刊

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jfca.2020.103757

关键词

Garlic; Spice; Economically motivated adulteration; Fourier transform infrared; Near infrared; Chemometrics

资金

  1. Herb and Spice Consortium
  2. McCormick
  3. Bart
  4. Waitrose
  5. Sainsbury's
  6. Morrisons
  7. Asda
  8. MS
  9. Tesco
  10. British Pepper Spice

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The study developed an adulteration detection method using NIR and FTIR technologies, successfully differentiating garlic from adulterants. Following validation, these methods showed high accuracy in detecting adulteration in unknown garlic samples, aiding in protecting the spice industry from fraud.
Garlic (A llium sativum) is used daily in a variety of cooking methods worldwide however, it is under threat from economic adulteration. Garlic and possible adulterants such as talc, maltodextrin, corn starch, cornflour, peanut butter powder, sodium caseinate, potato starch, rice flour, cassava and white maize meal were obtained for the development of an adulteration detection method. Near infrared (NIR) and Fourier transform infrared (FTIR) along with chemometrics were used for adulteration detection method development. Principal component analysis (PCA) models were created to establish if there was separation of garlic from the adulterants. Orthogonal partial least squares - discriminant analysis (OPLS-DA) models were then developed resulting in R2 and Q2 values of 0.985 and 0.914 respectively for NIR. The FTIR values were 0.994 (R2) and 0.964 (Q2). Following validation, the receiver operating curve (ROC) indicated highly accurate models with an area under the curve (AUC) of 0.997 for NIR and 1 for FTIR. The Youden index was calculated at 0.984 and 1 for NIR and FTIR respectively and used to determine the test cut-off value. These results indicate that the NIR and FTIR methods are capable of detecting adulteration in unknown garlic samples and can be used to help protect spice industry from fraud.

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