Food fraud is a major threat to the integrity of the nut supply chain. Strategies using a wide range of analytical techniques have been developed over the past few years to detect fraud and to assure the quality, safety, and authenticity of nut products. However, most of these techniques present the limitations of being slow and destructive and entailing a high cost per analysis. Nevertheless, near-infrared (NIR) spectroscopy and NIR imaging techniques represent a suitable non-destructive alternative to prevent fraud in the nut industry with the advantages of a high throughput and low cost per analysis. This review collects and includes all major findings of all of the published studies focused on the application of NIR spectroscopy and NIR imaging technologies to detect fraud in the nut supply chain from 2018 onwards. The results suggest that NIR spectroscopy and NIR imaging are suitable technologies to detect the main types of fraud in nuts.

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.