4.7 Article

Fraud Detection in Batches of Sweet Almonds by Portable Near-Infrared Spectral Devices

期刊

FOODS
卷 10, 期 6, 页码 -

出版社

MDPI
DOI: 10.3390/foods10061221

关键词

almond batches; authentication; non-targeted fraud detection; non-destructive assessment; in situ NIR spectroscopy

资金

  1. Desarrollo y Aplicaciones Fitotecnicas, DAFISA [P-12018024]
  2. OFM-Food Machinery [P-12019086]

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This study evaluates the potential of near-infrared spectroscopy (NIRS) using portable instruments to detect the presence of bitter almonds in batches of sweet almonds. Results show that NIR spectroscopy can reliably and accurately detect the presence of bitter almonds in sweet almond batches with adulteration levels of up to 5%, and this technology can be easily used in the main steps of the production chain.
One of the key challenges for the almond industry is how to detect the presence of bitter almonds in commercial batches of sweet almonds. The main aim of this research is to assess the potential of near-infrared spectroscopy (NIRS) by means of using portable instruments in the industry to detect batches of sweet almonds which have been adulterated with bitter almonds. To achieve this, sweet almonds and non-sweet almonds (bitter almonds and mixtures of sweet almonds with different percentages (from 5% to 20%) of bitter almonds) were analysed using a new generation of portable spectrophotometers. Three strategies (only bitter almonds, bitter almonds and mixtures, and only mixtures) were used to optimise the construction of the non-sweet almond training set. Models developed using partial least squares-discriminant analysis (PLS-DA) correctly classified 86-100% of samples, depending on the instrument used and the strategy followed for constructing the non-sweet almond training set. These results confirm that NIR spectroscopy provides a reliable, accurate method for detecting the presence of bitter almonds in batches of sweet almonds, with up to 5% adulteration levels (lower levels should be tested in future studies), and that this technology can be readily used at the main steps of the production chain.

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