NIR-based Sudan I to IV and Para-Red food adulterants screening

ABSTRACT

Spices are added in order to enhance the organoleptic characteristics of food and culinary dishes, making them more attractive for consumers. The use of illicit cheap colourants might be profitable along the food supply chain, posing undue risks to human health. This work evaluates the feasibility of NIR spectroscopy with chemometrics as a rapid, simple, non-destructive and affordable screening tool to determine the presence of Sudan I, II, III, IV and Para-red dyes in paprika. The dataset comprised unadulterated and adulterated samples with the five studied dyes at different concentration levels. Several multivariate classification models were built with Linear Discriminant Analysis (LDA) and different machine learning techniques. Preliminary results show that a classifier based on only six wavenumbers is able to determine the presence of some of these dyes in food samples in levels that may represent risk to human health. Sensitivities and specificities above 90% were obtained in almost all cases. These results show the feasibility of inexpensive and portable devices that can be useful for screening out adulterated stock along the food chain supply.

Graphical Abstract

KEYWORDS:

• Paprika adulteration
• Sudan dyes
• NIR
• machine learning analysis
• screening methods
• few-variables sensing

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the National Council for Scientific and Technical Research (CONICET), the South National University (UNS, PGI 24/Q081 and PGI 24/K061) and the National Agency for Scientific and Technological Promotion (FONCyT).