Combining Knowledge- and Data-Driven Fuzzy Approach to Evaluate Shelf-Life of Various Seafood Products

Abstract Due to the complexity of deterioration process seafood products, relying on one indicator is not adequate determine quality such products. Usually, shelf-life was estimated based various indicators complicating decision-making process. Decision Support Systems are considered as a good solution. The current study aims establish simple and novel fuzzy model combination knowledge- data-driven approaches define index (FQDI) in products (rainbow trout, threadfin bream, white shrimp samples) during cold storage. Total volatile basic nitrogen (TVB-N) psychrotrophic microorganisms counts (PMCs) were determined traditional methods. sensory analysis performed by approach. Overall, rainbow trout fillet be 8 days, all freshness parameters. However, Japanese bream 5–7 days according microbial chemical parameters, respectively. This time for samples 6–8 using score TVB-N contents. results approach showed properties ‘Important’–‘Very Important’ (defuzzification >75). PMCs most weakest (defuzzified-values: 84.64 78.75, respectively). Based FQDI, 8, 5, 7 method able successfully provide comprehensive evaluating shelf-life. Such total can output (y variable) predict rapid nondestructive method.