Assessing the quality of sardine based on biogenic amines using a fuzzy logic model
There is an increasing concern about the quality and quality assessment procedures of seafood. In the present study, a model to assess fish quality based on biogenic amine contents using fuzzy logic model (FLM) is proposed. The fish used was sardine (Sardinella sp.) where the production of eight bio...
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2017
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my.upm.eprints.609392019-03-22T03:28:18Z http://psasir.upm.edu.my/id/eprint/60939/ Assessing the quality of sardine based on biogenic amines using a fuzzy logic model Zare, Davood Mohd Ghazali, Hasanah There is an increasing concern about the quality and quality assessment procedures of seafood. In the present study, a model to assess fish quality based on biogenic amine contents using fuzzy logic model (FLM) is proposed. The fish used was sardine (Sardinella sp.) where the production of eight biogenic amines was monitored over fifteen days of storage at 0, 3 and 10°C. Based on the results, histamine, putrescine and cadaverine were selected as input variables and twelve quality grades were considered for quality of fish as output variables for the FLM. Input data were processed by rules established in the model and were then defuzzified according to defined output variables. Finally, the quality of fish was evaluated using the designed model and Pearson correlation between storage times with quality of fish showed r=0.97, 0.95 and 1 for fish stored at 0, 3 and 10°C, respectively. Elsevier 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/60939/1/Assessing%20the%20quality%20of%20sardine%20based%20on%20biogenic%20amines%20using%20a%20fuzzy%20logic%20model.pdf Zare, Davood and Mohd Ghazali, Hasanah (2017) Assessing the quality of sardine based on biogenic amines using a fuzzy logic model. Food Chemistry, 221. pp. 936-943. ISSN 0308-8146; ESSN: 1873-7072 https://reader.elsevier.com/reader/sd/pii/S0308814616319203?token=D2F1D81D2A1A64AFD61D958C881BA3D51491D8E5003871FC4BC191092FB2E4847C6B673EC629E192394FAD7E31892AF6 10.1016/j.foodchem.2016.11.071 |
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There is an increasing concern about the quality and quality assessment procedures of seafood. In the present study, a model to assess fish quality based on biogenic amine contents using fuzzy logic model (FLM) is proposed. The fish used was sardine (Sardinella sp.) where the production of eight biogenic amines was monitored over fifteen days of storage at 0, 3 and 10°C. Based on the results, histamine, putrescine and cadaverine were selected as input variables and twelve quality grades were considered for quality of fish as output variables for the FLM. Input data were processed by rules established in the model and were then defuzzified according to defined output variables. Finally, the quality of fish was evaluated using the designed model and Pearson correlation between storage times with quality of fish showed r=0.97, 0.95 and 1 for fish stored at 0, 3 and 10°C, respectively. |
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Zare, Davood Mohd Ghazali, Hasanah |
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Zare, Davood Mohd Ghazali, Hasanah Assessing the quality of sardine based on biogenic amines using a fuzzy logic model |
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Zare, Davood Mohd Ghazali, Hasanah |
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Zare, Davood |
title |
Assessing the quality of sardine based on biogenic amines using a fuzzy logic model |
title_short |
Assessing the quality of sardine based on biogenic amines using a fuzzy logic model |
title_full |
Assessing the quality of sardine based on biogenic amines using a fuzzy logic model |
title_fullStr |
Assessing the quality of sardine based on biogenic amines using a fuzzy logic model |
title_full_unstemmed |
Assessing the quality of sardine based on biogenic amines using a fuzzy logic model |
title_sort |
assessing the quality of sardine based on biogenic amines using a fuzzy logic model |
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Elsevier |
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2017 |
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http://psasir.upm.edu.my/id/eprint/60939/1/Assessing%20the%20quality%20of%20sardine%20based%20on%20biogenic%20amines%20using%20a%20fuzzy%20logic%20model.pdf http://psasir.upm.edu.my/id/eprint/60939/ https://reader.elsevier.com/reader/sd/pii/S0308814616319203?token=D2F1D81D2A1A64AFD61D958C881BA3D51491D8E5003871FC4BC191092FB2E4847C6B673EC629E192394FAD7E31892AF6 |
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