Assessment of paprika geographical origin fraud by high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprinting

This study investigates the use of high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprinting as a robust method for authenticating the geographical origin of paprika and detecting potential fraud. The research addresses the economic incentive for adulteration due to the higher retail prices of paprika with Protected Designation of Origin (PDO). The methodology involved analyzing HPLC-FLD fingerprints, which are closely associated with phenolic acid and polyphenolic compounds, from paprika samples sourced from five distinct European regions, including three Spanish PDOs, Hungary, and the Czech Republic. These chromatographic fingerprints were then subjected to chemometric analysis using a classification decision tree built upon partial least squares regression-discriminant analysis (PLS-DA) models. The developed classification model demonstrated exceptional performance, achieving an external validation accuracy of 97.9%, indicating its high reliability in distinguishing paprika origins. Furthermore, the study extended its application to detect and quantify two different scenarios of paprika geographical origin blending using partial least squares (PLS) regression. This quantitative approach yielded low external validation and prediction errors, specifically below 1.6% and 10.7% respectively, highlighting the method's precision in identifying and quantifying adulteration. The findings underscore the potential of HPLC-FLD fingerprinting combined with chemometrics as a powerful tool for ensuring food authenticity and combating food fraud in the paprika industry.

This study investigates the use of high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprinting as a robust method for authenticating the geographical origin of paprika and detecting potential fraud. The research addresses the economic incentive for adulteration due to the higher retail prices of paprika with Protected Designation of Origin (PDO). The methodology involved analyzing HPLC-FLD fingerprints, which are closely associated with phenolic acid and polyphenolic compounds, from paprika samples sourced from five distinct European regions, including three Spanish PDOs, Hungary, and the Czech Republic. These chromatographic fingerprints were then subjected to chemometric analysis using a classification decision tree built upon partial least squares regression-discriminant analysis (PLS-DA) models. The developed classification model demonstrated exceptional performance, achieving an external validation accuracy of 97.9%, indicating its high reliability in distinguishing paprika origins. Furthermore, the study extended its application to detect and quantify two different scenarios of paprika geographical origin blending using partial least squares (PLS) regression. This quantitative approach yielded low external validation and prediction errors, specifically below 1.6% and 10.7% respectively, highlighting the method's precision in identifying and quantifying adulteration. The findings underscore the potential of HPLC-FLD fingerprinting combined with chemometrics as a powerful tool for ensuring food authenticity and combating food fraud in the paprika industry. Research Background and Significance The authentication of food products, particularly those with Protected Designation of Origin (PDO), is of paramount importance to ensure consum