Authentication of commercial honeys based on Raman fingerprinting and pattern recognition analysis. (November 2020)

• Record Type: Journal Article
• Authors: Aykas, Didem P.; Shotts, Mei-Ling; Rodriguez-Saona, Luis E.
• Is Part Of: Food control. Volume 117(2020)
• Publication Date: 2020-11
• Subjects: Raman -- Honey -- Adulteration -- Fingerprinting -- Specificity -- Sensitivity; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2020.107346
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Our aim was to develop a rapid non-targeted approach to authenticate commercial honey combining Raman spectroscopy and pattern recognition analysis. Honey samples (n = 97) were collected from local and global grocery stores and online vendors. Spectra were collected by handheld and compact benchtop Raman systems equipped with a 1064 nm excitation laser and analyzed by pattern recognition techniques (Soft Independent Model of Class Analogies, SIMCA) to develop classification algorithms. High-performance liquid chromatography (HPLC-RI, AOAC#977.20) was used to verify the authenticity of honeys. Both Raman systems formed distinct SIMCA clusters for the samples associated with their unique sugar profile. Evaluation of store-bought commercial samples indicated adulteration in 16 samples (17%); all samples predicted by the Raman algorithms as non-authentic were confirmed by HPLC-RI. Raman technology provides analytical features for ingredient verification, offering the industry and regulatory agencies valuable resources to ensure accurate labeling of honey products. Highlights: SIMCA combined with Raman spectroscopy data confirmed the authenticity of commercial honeys. From the total evaluated 97 store bought honeys, 17% were determined as tainted. The type of Raman instrument (handheld or compact benchtop) did not compromise classification accuracies.