Non-targeted detection of grape molasses adulteration with sugar and apple molasses by mid-infrared spectroscopy coupled to independent components analysis

Abstract

In the light of the current food security crisis, food adulteration has resurfaced on the international scene, inflicting potential safety issues and leading more and more consumers into deception. This situation led food control actors to remobilise their potential to face this problem, particularly in terms of analytical chemistry competencies. Similar to honey, grape molasses may be considered very likely to be adulterated leading to quality and authenticity issues, especially in the Eastern Mediterranean, where it is widely consumed as a traditional sweetener. This work reports the use of attenuated total reflectance–mid-infrared spectroscopy (ATR–MIR) coupled to chemometrics, as an alternative to complex, expensive and time-consuming analytical techniques, in the aim of detecting fraudulent glucose, fructose, sucrose and apple molasses additions to pure grape molasses. After collecting a widespread unadulterated grape molasses database, spiked samples with increasing concentrations (w/w) of the selected adulterants were prepared. In order to establish a qualitative model, whose potential is to detect adulteration and discriminate between the different adulterants, samples underwent ATR–MIR analyses without any prior preparation, and the collected spectral data were subjected to independent components analysis (ICA), where Random_ICA was used to retrieve the optimal number of independent components (ICs). Thereupon, the extraction of seven ICs allowed the establishment of a qualitative model with a clear discrimination between molasses adulterated with fructose, sucrose and glucose syrup, relying on MIR specific signals and incorporated ratios of the different adulterants. However, it failed in detecting apple molasses adulteration, calling for the development of a different analytical approach. The developed model underwent a verification step using a control set recorded on a different spectrometer, proving its potential to provide reproducible discrimination and classification rates.