A Baseline Study on the Quality and Safety of Consumption of a Pest Species (Sarotherodon melanotheron) in Bataan, Philippines: Basis for Its Productive Utilization in the Fisheries Sector

The baseline study profiled Black-chin Tilapia (Sarotherodon.melanotheron), a fish farm pest species in Bataan, Philippines, in terms ofyield (processing and fillet), proximate composition (moisture, ash, crudefat, and crude protein), heavy metal load (cadmium [Cd], lead [Pb], arsenic[As], and mercury [Hg]), and microbial count (aerobic plate, Escherichiacoli, and Staphylococcus aureus counts). The purpose was to establish thespecies’ safety and quality for consumption and potential utilization inthe processing of higher value fishery products. A completely randomizedexperiment using two factors, fish size (standard and small sizes) andcollection season (dry and wet seasons), was employed. The collected datawere also compared against food consumption and processing standardsand/or previous reports on more valuable species. The results showed thatthe species has a comparable yield and mineral load with the more popularfarmed Nile Tilapia (Oreochromis niloticus). It has high moisture andprotein compositions. It is a lean fish that can serve as a cheaper functionalraw material for processed fishery products. Moreover, the results showedthat the species have no As, Cd, and Pb contamination, although traces ofHg, far below the permissible limits, were detected. The Hg load variesacross collection season and fish maturity suggesting its manageability.For the microbial contents, the species’ aerobic plate, Escherichia coli, andStaphylococcus aureus counts were far below the standard limits, althoughbest post-capture practices are still suggested due to the kind of microbialparameters measured. It was concluded that the Sarotherodon melanotheroninfesting Bataan farm ponds can be consumed safely and has the qualityof potential raw material for processed fishery products. However, furtherinformation is still needed to establish the best post-capture handling on thespecies. Also, more studies must be done to determine the impact of storageand processing on its stability

The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making

The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Hindawi Publishing Corporation. The published article can be found at: http://www.hindawi.com/journals/ijpg/