Correction: A Bayesian belief data mining approach applied to rice and shrimp aquaculture.

[This corrects the article DOI: 10.1371/journal.pone.

Evaluating the Application of Portable Handheld X-ray Fluorescence (XRF) Scanner for Determining Seafood Provenance: A Case Study on .

Seafood elemental profiling (SEP) is the quantification of a range of elements in seafood products and may serve in addressing questions of seafood provenance and quality. Traditional methods for analyzing soft tissue present several limitations for the industry-level use of SEP. Portable handheld X-ray fluorescence (pXRF) analysis is a promising alternative to conventional methods; however, its application for biological analysis has not been fully established.

Developing a MySQL Database for the Provenance of Black Tiger Prawns ().

As the demand for seafood increases, so does the incidence of seafood fraud. Confirming provenance of seafood is important to combat fraudulent labelling but requires a database that contains the isotopic and elemental "fingerprints" of authentic seafood samples. Local isotopic and elemental databases can be scaled up or combined with other databases to increase the spatial and species coverage to create a larger database.

A Bayesian belief data mining approach applied to rice and shrimp aquaculture.

In many parts of the world, conditions for small scale agriculture are worsening, creating challenges in achieving consistent yields. The use of automated decision support tools, such as Bayesian Belief Networks (BBNs), can assist producers to respond to these factors. This paper describes a decision support system developed to assist farmers on the Mekong Delta, Vietnam, who grow both rice and shrimp crops in the same pond, based on an existing BBN.