Honey is a valuable food product that is often mislabeled as to its botanical composition, affecting both trade transparency and consumer safety. DNA metabarcoding is a promising method for authenticity verification, although the results are affected by the choice of molecular markers and primer pairs. This study selected 43 primer pairs from the literature covering several genes (chloroplast rbcL, matK, and trnL and nuclear ITS) and length of <600 bp. Performance of these primers was in silico assessed for all Streptophyta and a subset of them representing the honeybee foraging plants included in the European list. The results showed that rbcL primers provided the highest taxonomic coverage, which increased significantly when combined with ITS2, especially for key families, such as Asteraceae, Fabaceae, Lamiaceae, and Rosaceae. These results provide valuable insights for the design and chemical setup of molecular steps in metabarcoding experiments applied to honey authenticity also supporting the standardization of official control protocols.

Food authentication significantly impacts consumer health and the credibility of Food Business Operators (FBOs). As European regulations mandate the verification of food authenticity and supply chain integrity, competent authorities require access to innovative analytical methods to identify and prevent food fraud. This study utilizes the DNA metabarcoding approach on meat preparations, sampled during an official control activity. It assesses animal and plant composition by amplifying DNA fragments of the 12S rRNA and trnL (UAA) genes, respectively. The results not only confirmed the declared species but also revealed undeclared and unexpected taxa in products labelled as containing a single animal species and various unspecified plant species. Notable findings such as the presence of Murinae, Sus scrofa, Ovis aries, and Pisum sativum could raise public health concerns, compromise consumer choices made for ethical or religious reasons, and reflect the hygienic conditions of the processing plant. This study demonstrates that the DNA metabarcoding approach looks to be a promising support tool for official control authorities to ensure food authenticity and safety, and to develop risk profiles along the supply chain.

Given the recognized nutritional value of fish and shifting consumer lifestyles, processed seafood has become increasingly prevalent, comprising a significant portion of global food production. Although current European Union labeling regulations do not require species declaration for these products, food business operators often voluntarily provide this information on ingredient lists. Next Generation Sequencing (NGS) approaches are currently the most effective methods for verifying the accuracy of species declarations on processed seafood labels. This study examined the species composition of 20 processed seafood products, each labeled as containing a single species, using two DNA metabarcoding markers targeting the mitochondrial cytochrome c oxidase I (COI) and 16S rRNA genes. The combined use of these markers revealed that the majority of the products contained multiple species. Furthermore, two products were found to be mislabeled, as the declared species were not detected. These findings underscore that NGS is a robust technique that could be adopted to support routine food industry activities and official control programs, thereby enhancing the ‘From Boat to Plate’ strategy and combating fraudulent practices in the complex fisheries supply chain.