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  • Title: Microscopic recognition and identification of fish meal in compound feeds.
    Author: van Raamsdonk LWD, Prins TW, van de Rhee N, Vliege JJM, Pinckaers VGZ.
    Journal: Food Addit Contam Part A Chem Anal Control Expo Risk Assess; 2017 Aug; 34(8):1364-1376. PubMed ID: 28277174.
    Abstract:
    Fish meal is an accepted ingredient in compound feed. Unauthorised application is primarily enforced by visual inspection, i.e., microscopy. In order to document the visually available diversity, fragments of bones and scales of 17 teleost fish species belonging to seven different orders were investigated for their diversity in the presence of structural elements: lacunae and canaliculae in bone fragments and type of growth rings and teeth of scale fragments. Despite the classical division into cellular bones and acellular bones of teleost fish, i.e., whether or not possessing osteocytes, the current examinations revealed patterns of lacunae, in some types accompanied with canaliculae, in all 17 species investigated. In total seven types of bone structures were defined, and six types of scale structures. Profiles with the relative frequency of each bone type per species were established. The share of acellular bone fragments appeared to be related to the evolutionary position of the species. Results of proficiency tests for the detection of fish meal reveal that in most cases the sensitivity and specificity for the detection of fish meal ranges from sufficient to perfect. Only some specified circumstances can hamper proper recognition and identification, most notably salmon bone fragments mimicking bone fragments from terrestrial animals, and pieces of hydrolysed proteins or minerals mimicking acellular fish bone fragments. The expertise gained in this study would help to improve the distinction between fish meal and terrestrial animal material in compound feed, and it supports the application of the species-to-species ban with respect to the valorisation of by-products from fish farms in aquafeed. In a broader perspective, the current expertise might be helpful to detect fraud throughout the feed/food production chain. The matrix of characteristics versus species is implemented in a data model running in the expert system 'Determinator' for facilitating identification.
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