Prediction and assessment of retail hake (Merluccius merluccius) freshness during storage

1 póster.-- 29th EFFoST International Conference, 10-12 November 2015, Athens, Greece
Reduction of fish freshness during the supply chain results into severe losses both from the economic (drastic reductions on market price) and environmental (fish rejection) points of view. In this context, prediction techniques based on mathematical models emerge as useful tools for fish quality assessment. In this work we propose a methodology to forecast fish freshness during storage. In this regard, we found a strong correlation between fish freshness indicators commonly used in the industry, such as the Quality Sensory Method (QSM), and the growth of Specific Spoilage Organisms (SSO). The main idea is to develop a reliable mathematical model which, on the one hand, describes the growth of SSO during storage and, on the other hand, relates the QSM to SSO concentration. Issues such as storage conditions, fishing practices or gutting procedures are taken into account. Such model allows us to predict shelf-life and quality losses. In order to provide the model with reliable predictive capabilities, advanced model calibration techniques are employed. In this regard, optimal experimental design (OED) is used to generate sufficient nonisothermal informative experiments that allow us to reduce the uncertainty in the predictions. Also, the Monte Carlo sampling technique is exploited to detect the parameter confidence intervals and to calculate fish-to-fish variability in the predictions (core predictions). The approach is illustrated using hake (Merluccius merluccius) caught either by bottom-set net or long-line under different storage temperature conditions. Furthermore, the effect of gutting is also studied. This methodology is flexible enough to consider other fish species or stress variables such as atmosphere composition
This work has been funded by the LIFE EU program: project LIFE iSEAS (LIFE13 ENV/ES/000131); by the Spanish Ministry of Science and Innovation: projects ISFORQUALITY (AGL2012-39951-C02-01), RESISTANCE (DPI2014-54085-JIN); and by Xunta de Galicia: contrato programa 2015