Chemometric data analysis application to Sparus aurata samples from two offshore farming plants along the Apulian (Italy) coastline.

The levels of polychlorodibenzo-p-dioxins (PCDDs), polychlorodibenzofurans (PCDFs), dioxin-like polychlorobiphenyls (DL-PCBs), non-dioxin-like polychlorobiphenyls (NDL-PCBs), and polybromodiphenyl ethers (PBDEs) in fish collected from two marine offshore farming plants were determined. Each sample was constituted by specimens of the same size collected at the same time in four different seasons along the farming year. The feeds given were of industrial origin and the plants were positioned in two different sites respectively exposed to different environmental characteristics. A chemometric approach was applied to interpret the subtle differences observed in fish body burdens across the three chemical groups taken into consideration. The approach consisted in a stepwise multivariate process including a hierarchical cluster analysis (CA) and a linear discriminant analysis (DA). The two main clusters determined by CA were subjected to the canonical DA, backward and forward selection procedures to select the best discriminative functions. A clear temporal and spatial discrimination was found among the samples. Across the three chemical groups, the monthly separation seemed to depend on the growth process and the main exposure was due to the feed. In addition, the two plants differed significantly from the environmental point of view and the most important discriminating group of chemicals were the NDL-PCBs. The approach resulted really effective in discriminating the subtle differences and in individuating suggestions to improve the quality of culturing conditions.
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