Risk-based scoring and genetic identification for anisakids in frozen fish products from Atlantic FAO areas

• Published in: BMC Veterinary Research
• Main Authors: Smaldone, Giorgio, Abollo, Elvira, Marrone, Raffaele, Bernardi, Cristian E M, Chirollo, Claudia, Anastasio, Aniello, Del Hierro, Santiago P
• Other Authors: G. Smaldone, E. Abollo, R. Marrone, C.E.M. Bernardi, C. Chirollo, A. Anastasio, S.P. Del Hierro
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2020
• Subjects: Anisaki; food safety; risk ranking tool; zoonotic risk; fish inspection; Settore VET/04 - Ispezione degli Alimenti di Origine Animale; Molva dypterygia
• Online Access: http://hdl.handle.net/2434/716528; https://doi.org/10.1186/s12917-020-02286-7

Background The presence of Anisakis larvae in fish represents a major public health concern. Effective risk management procedures should be applied to prevent heavily infected products from reaching the market. The aim of the study is to provide preliminary data on parasite exposure and risk classification in frozen fish products by applying a risk categorization scheme (site, abundance, density and epidemiology - SADE) and Fish Parasite Rating (FPR) method. Fish and cephalopods samples (N = 771) from 5 different FAO Atlantic areas were examined and categorized after an accurate visual inspection and a chloro-peptic digestion. Results In 25 out of 33 fish species parasite larvae were found. 10897 anisakids larvae were collected and identified to genus level. Molva dypterygia, Conger conger, Zeus faber and Aphanopus carbo were shown to be the most highly infected species. SADE and FPR scores were 1 and poor, respectively, for the referred species, because of the disseminated Anisakis infection and commercial rejection. Conclusion SADE/FPR method showed high specificity and accuracy. The information provided in this work could be used in early warning systems for the detection of parasites in fishery products and might help fishing industries in establishing management strategies for infected stocks in terms of cost saving decisions.