A statistical model-based diagnostic scheme for cost-effective determination of freshness in fish industry

A statistical diagnostic scheme investing on the novel concept of freshness (instead of spoilage) determination in fish industry is presented. Drawing on fault diagnosis expertise, the scheme relies on cost-effective vibration-like testing of fish samples and accurate (under typical uncertainties) stochastic modeling of their response. Via the identified models, specific quantities related to the sample\´s texture (itself indicative of its freshness) are computed. Then, such quantities from test samples of unknown freshness are compared with the nominal "fresh-fish" values for determining the freshness degree. This comparison is based on custom-built statistical hypothesis tests, capable of issuing reliable decisions while taking into account the risk of the decision-making process. Tests involving 0-, 3- and 6-day-old fish samples show very promising results.