A comprehensive review on unethical honey: Validation by emerging techniques. (March 2023)

• Record Type: Journal Article
• Authors: Brar, Dilpreet Singh; Pant, Kirty; Krishnan, Reshma; Kaur, Sawinder; Rasane, Prasad; Nanda, Vikas; Saxena, Sudhanshu; Gautam, Satyendra
• Is Part Of: Food control. Volume 145(2023)
• Publication Date: 2023-03
• Subjects: Honey -- Adulteration -- Authenticity -- Analytical tools -- Chemometric -- Syrup; 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.2022.109482
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Globally, honey is consumed as natural functional food, featuring high economic value, related to its authenticity and purity. Due to the high demand for honey, it has been wildly targeted for food adulteration with substandard honey or low-price syrups, and emerging absorbent resin technology has also affected the honey market. Researchers worldwide have been working persistently to invent and innovate advanced technologies for detecting honey adulteration and assuring its authenticity. The compositional intricacy of pure and unauthentic honey could be easily detangled by a combined approach of chemometrics and instrument. In this palimpsest, various detection methods like ISCIRA, NMR, AT-FTIR, Sensors, PCR based assay united with an appropriate Multivariate approach that provides accurate and acceptable results for the determination of honey authentication and adulteration were described. The botanical origin authentication of honey was determined with the application of δ13C-EA-IRMS and δ13C-LC-IRMS coupled SVM, which discriminate samples based on specific markers. LIBS, NMR, HPTLC, UHPLC, GC, and real-time PCR, generated data and processed with LDA, OPLS, PCA, ANN, CNN etc. The generated data discriminate adulterated honey from pure, as NMR clubbed with PCA can detect 1% of adulterants in honey. Hence, various methodologies in chemometrics have manifested their proficiency during ground application. Perhaps, there is a long way to go in this field to develop a universal technology for honey authentication and adulteration detection. Graphical abstract: Image 1