ABSTRACT
The aim of this study was to assess the quality of the drinking water supply in the district of Avellino (Italy), by evaluating physico-chemical parameters and presence of contaminants. A multivariate approach was used to analyse data and to evaluate compliance to norms and standards. Study results indicate that statistical modeling is a powerful descriptive method to identify qualitative temporal trends in water quality and, if repeated in time, allows an evaluation of representativeness of the sampling points.
ABSTRACT
Monitoring food quality is a critical task for analytical chemistry and an important way to preserve human health. Fish is a valuable source of highly digestible proteins and contains large amounts of polyunsaturated fatty acids and fat-soluble vitamins. Since the world's wild fish stocks are limited, farmed fish is nowadays proposed as an alternative to consumers. It is now emerging that the fish muscle protein content is assuming great importance from an aquaculture perspective. Many data have been collected on the physiology and biochemistry of fish muscle, but few proteomic studies are available on farmed fish. Application of proteomics to aquaculture may play a key role in the development of new farming strategies. In this paper, a proteomic approach based on SDS-PAGE separation of proteins, in situ protein hydrolysis, de novo sequencing of peptides by MALDI and ESI MS(2), protein identification, and relative quantitation of protein by denaturing capillary electrophoresis was coupled with the determination of fatty acids and metal ions content by GM-MS and ICPMS in farmed and wild sea bass filet. Our results show that aquaculture could induce significant chemical and biochemical differences in fish muscle that may have an impact on food quality.
