Due to the complexity of the deterioration process of seafood products,relying on one indicator is not adequate to determine the quality of such products.Usually,shelf-life was estimated based on various indicators co...Due to the complexity of the deterioration process of seafood products,relying on one indicator is not adequate to determine the quality of such products.Usually,shelf-life was estimated based on various indicators complicating the decision-making process.Decision Support Systems are considered as a good solution.The current study aims to establish a simple and novel fuzzy model based on a combination of knowledge-and data-driven approaches to define a fuzzy quality deterioration index(FQDI)in various seafood products(rainbow trout,threadfin bream,and white shrimp samples)during cold storage.Total volatile basic nitrogen(TVB-N)and psychrotrophic microorganisms counts(PMCs)were determined based on traditional methods.The sensory analysis was performed by a data-driven fuzzy approach.Overall,the shelf-life of the rainbow trout fillet was estimated to be 8 d,based on all the freshness parameters.However,the shelf-life of the Japanese threadfin bream fillet was 5-7 d according to the microbial and chemical parameters,respectively.This time for shrimp samples was 6-8 d using sensory score and TVB-N contents.The results of data-driven fuzzy approach showed all of the quality properties were considered as the'Important'-'Very Important'(defuzzification score>75).The TVB-N and PMCs were the most and weakest freshness quality properties(defuzzified-values:84.64 and 78.75,respectively).Based on FQDI,the shelf-life of the rainbow trout,Japanese threadfin bream,and shrimp samples were estimated to be 8,5,and 7 d,respectively.This method was able to successfully provide a comprehensive deterioration index for evaluating the seafood shelf-life.Such a total index can be considered as a comprehensive output(y variable)to predict seafood freshness by rapid and nondestructive method.展开更多
基金financially supported by the Iran National Science Foundation(No.98013631).
文摘Due to the complexity of the deterioration process of seafood products,relying on one indicator is not adequate to determine the quality of such products.Usually,shelf-life was estimated based on various indicators complicating the decision-making process.Decision Support Systems are considered as a good solution.The current study aims to establish a simple and novel fuzzy model based on a combination of knowledge-and data-driven approaches to define a fuzzy quality deterioration index(FQDI)in various seafood products(rainbow trout,threadfin bream,and white shrimp samples)during cold storage.Total volatile basic nitrogen(TVB-N)and psychrotrophic microorganisms counts(PMCs)were determined based on traditional methods.The sensory analysis was performed by a data-driven fuzzy approach.Overall,the shelf-life of the rainbow trout fillet was estimated to be 8 d,based on all the freshness parameters.However,the shelf-life of the Japanese threadfin bream fillet was 5-7 d according to the microbial and chemical parameters,respectively.This time for shrimp samples was 6-8 d using sensory score and TVB-N contents.The results of data-driven fuzzy approach showed all of the quality properties were considered as the'Important'-'Very Important'(defuzzification score>75).The TVB-N and PMCs were the most and weakest freshness quality properties(defuzzified-values:84.64 and 78.75,respectively).Based on FQDI,the shelf-life of the rainbow trout,Japanese threadfin bream,and shrimp samples were estimated to be 8,5,and 7 d,respectively.This method was able to successfully provide a comprehensive deterioration index for evaluating the seafood shelf-life.Such a total index can be considered as a comprehensive output(y variable)to predict seafood freshness by rapid and nondestructive method.
