In order to obtain a high-protein-content supplement for aquaculture feeds, rich in healthy microorganisms, in this study, Saccharomyces cerevisiae American Type Culture Collection (ATCC) 4126 and Lactobacillus reuteri ATCC 53608 strains were used as starters for fermenting fish waste supplemented with lemon peel as a prebiotic source and filler. Fermentation tests were carried out for 120 h until no further growth of the selected microorganisms was observed and the pH value became stable. All the samples were tested for proteins, crude lipids, and ash determination, and submitted for fatty acid analysis. Moreover, microbiological analyses for coliform bacteria identification were carried out. At the end of the fermentation period, the substrate reached a concentration in protein and in crude lipids of 48.55 ± 1.15% and 15.25 ± 0.80%, respectively, representing adequate levels for the resulting aquafeed, whereas the ash percentage was 0.66 ± 0.03. The main fatty acids detected were palmitic, oleic, and linoleic acids. Saturated fatty acids concentration was not affected by the fermentation process, whereas monounsaturated and polyunsaturated ones showed an opposite trend, increasing and decreasing, respectively, during the process. Coliform bacteria were not detected in the media at the end of the fermentation, whereas the amount of S. cerevisiae and L. reuteri were around 10¹¹ and 10¹² cells per g, respectively.

The coronavirus disease 2019 (COVID-19) has brought a global socio-economic crisis to almost all sectors including the fishery. To limit the infection, governments adopted several containment measures. In Italy, Croatia, and Slovenia, a lockdown period was imposed from March to May 2020, during which many activities, including restaurants had to close or limit their business. All of this caused a strong reduction in seafood requests and consequently, a decrease in fishing activities. The aim of this study is to investigate the effects of the COVID-19 in the Northern and Central Adriatic fleet, by comparing the fishing activities in three periods (before, during, and after the lockdown) of 2019 and 2020. The use of the Automatic Identification System (AIS) data allowed us to highlight the redistribution of the fishing grounds of the trawlers, mainly located near the coasts during the 2020 lockdown period, as well as a reduction of about 50% of fishing effort. This reduction resulted higher for the Chioggia trawlers (−80%) and, in terms of fishing effort decrease, the large bottom otter trawl was the fishing segment mainly affected by the COVID-19 event. Moreover, by analysing the landings of the Chioggia fleet and the Venice lagoon fleets, it was possible to point out a strong reduction both in landings and profits ranging from −30%, for the small-scale fishery operating at sea, to −85%, for the small bottom otter trawl.

In this paper we model spatio-temporal data describing the fishing activities in the Northern Adriatic Sea over four years. We build, implement and analyze a database based on the fusion of two complementary data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed) and fish catch reports (i.e., the quantity and type of fish caught) of the main fishing market of the area. We present all the phases of the database creation, starting from the raw data and proceeding through data exploration, data cleaning, trajectory reconstruction and semantic enrichment. We implement the database by using MobilityDB, an open source geospatial trajectory data management and analysis platform. Subsequently, we perform various analyses on the resulting spatio-temporal database, with the goal of mapping the fishing activities on some key species, highlighting all the interesting information and inferring new knowledge that will be useful for fishery management. Furthermore, we investigate the use of machine learning methods for predicting the Catch Per Unit Effort (CPUE), an indicator of the fishing resources exploitation in order to drive specific policy design. A variety of prediction methods, taking as input the data in the database and environmental factors such as sea temperature, waves height and Clorophill-a, are put at work in order to assess their prediction ability in this field. To the best of our knowledge, our work represents the first attempt to integrate fishing ships trajectories derived from AIS data, environmental data and catch data for spatio-temporal prediction of CPUE – a challenging task.

This paper reviews several scientific articles regarding levels of organic and inorganic contaminants in a variety of marine species coming from two Sicilian protected areas: the Strait of Messina and Cape Peloro lakes (Ganzirri and Faro). Moreover, different analytical techniques for the determinations of organic and inorganic contaminants, and the procedures adopted for the analyses, are summarized. Quantitative and qualitative determination of organic pollutants was performed by High Resolution Gas Chromatography-Electron Capture Detection and confirmed by Gas Chromatography-Mass Spectrometry. The concentrations of inorganic elements were determined by Atomic Absorption Spectrophotometry, derivative Stripping Chronopotentiometry, Inductively Coupled Plasma-Optical Emission Spectrometry and Inductively Coupled Plasma -Mass Spectrometry. Results provide evidence that organic and inorganic residues found in some of the examined samples were mostly below the Maximum Residue Levels (MRLs). In conclusion, species analyzed in these studies were safe for human consumption and, consequently the investigated environments were estimated as free from toxicological risk.