Honey Traceability and Authenticity. Review of Current Methods Most Used to Face this Problem

• Published in: Journal of Apicultural Science Vol. 66; no. 2; pp. 101 - 119
• Main Authors: Danieli, Pier Paolo, Lazzari, Filippo
• Format: Journal Article
• Language: English
• Published: Pulawy Sciendo 01.12.2022; De Gruyter Poland
• Subjects: Agriculture; Analytical methods; apiculture; Authenticity; Automation; Bees; Blockchain; chemometrics; Classification; Cryptography; Flowers & plants; genomics; geographical origin; Geography; Honey; Internet; Internet of Things; Machine learning; melissopalynology; Metabolomics; Palynology; Physical properties; Pollen; spectroscopy; Statistical methods; traceability; “omic” sciences
• ISSN: 2299-4831; 1643-4439; 2299-4831
• DOI: 10.2478/jas-2022-0012

In this review, we have focused on analytical methods for characterizing the geographical and botanical origin of honey. We evaluated works concerning the methods most used in the analysis of the geographical and botanical origin of honey, paying particular attention to what has been used in the last decade. We investigated starting from the most common methods used at the beginning of this century, such as melissopalynological analysis, the analysis of the mineral profile or chemico-physical parameters, to the current state-of-the-art technologies and methods including the metabolomic and genomic approaches, the blockchain or Internet of Things. For each methodology, several examples have been given, and advantages and limitations are explained. Whereas currently only one approach is rarely used, many methods are used in combination because a combined approach usually leads to greater accuracy, also thanks to the current possibilities that multivariate statistical methods or chemometric methods offers us.