Abstract
Pet food industry has grown considerably in the last few years and it is expected to continue with this rate. Despite the economic impact of this sector and the consumer concerns for the increasing number of food and feed adulteration cases, few studies have been published on mislabelling in pet foods. We therefore investigated the capability of a next generation sequencing-based mini-barcoding approach to identify animal species in pet food products. In a preliminary analysis, a 127 bp fragment of the COI gene was tested on both individual specimens and ad hoc mixed fresh samples used as testers, to evaluate its discrimination power and primers effectiveness. Eighteen pet food products of different price categories and forms available on the market (i.e. kibbles, bites, pâté and strips) were analysed through an NGS approach in biological replicates. At least one of the species listed in the ingredients was not detected in half of the products, while seven products showed supplementary species in addition to those stated on the label. Due to the accuracy, sensitivity and specificity demonstrated, this method can be proposed as food genetic traceability system to evaluate both the feed and food quality timely along the supply chain.