Differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis
Electronic nose devices are becoming a practical tool for the identification of differences among food products badsed on their origin, intrinsic quality and process conditions. The difficulty in using such instruments is to obtain, from the sensors response patterns, suitable parameters to identify...
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ftunibolognairis:oai:cris.unibo.it:11585/58285 2024-09-15T18:33:04+00:00 Differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis SADO KAMDEM, SYLVAIN LEROY NDAGIJIMANA, MAURICE VANNINI, LUCIA GUERZONI, MARIA ELISABETTA S. Sado Kamden M. Ndagijimana L. Vannini M.E. Guerzoni 2007 STAMPA http://hdl.handle.net/11585/58285 https://www.chiriottieditori.it/ojs/index.php/ijfs/issue/view/31/IJFS183-SLIM2006 eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000208675300072 volume:Special issue (SLIM 2006) firstpage:393 lastpage:399 numberofpages:7 journal:ITALIAN JOURNAL OF FOOD SCIENCE http://hdl.handle.net/11585/58285 https://www.chiriottieditori.it/ojs/index.php/ijfs/issue/view/31/IJFS183-SLIM2006 info:eu-repo/semantics/closedAccess ELECTRONIC NOSE FEATURE SELECTION SEAFOOD STORAGE TIME info:eu-repo/semantics/article 2007 ftunibolognairis 2024-07-01T14:08:30Z Electronic nose devices are becoming a practical tool for the identification of differences among food products badsed on their origin, intrinsic quality and process conditions. The difficulty in using such instruments is to obtain, from the sensors response patterns, suitable parameters to identify the differences among samples. In this work the electronic nose analyses, trymethilamine determination and panel test were performed on samples of three species of farmed fish []ecentrachus labrax, Sparatus aurata and Salmo salar]tored for 8 days both under ice and abuse temperature of 6°C. Data from electronic nose were analysed choosing a group of features, i.e. average of the last 5 points, maximum point, average of the whole points and average of the signal resposnse characterised by the highest variation. A polynomial regression was performed on the different features in order to identify the contribution of the sensors to the sample response patterns. The data from the best sensors were then used to create an optimum feature (mixed feature). A principal component analysis (PCA)was performed on the data of all the features and the degree of separation of the tridimensional scatterplots used as a selective tool. Based on the results obtained, the features "average of the last 5 points" and "mixed feature" gave a good discrimination of the samples, "mixed feature" being the best. The scatterplot from "mixed feature" data allowed the separation of the fish samples based on species, freshness and storage time. The evolution overtime of the scores of the PCA, accounting for the highest variation of the best two features, was correlated both with TMA content and the overall evaluation of the product given by panelists. Article in Journal/Newspaper Salmo salar IRIS Università degli Studi di Bologna (CRIS - Current Research Information System) |
institution |
Open Polar |
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IRIS Università degli Studi di Bologna (CRIS - Current Research Information System) |
op_collection_id |
ftunibolognairis |
language |
English |
topic |
ELECTRONIC NOSE FEATURE SELECTION SEAFOOD STORAGE TIME |
spellingShingle |
ELECTRONIC NOSE FEATURE SELECTION SEAFOOD STORAGE TIME SADO KAMDEM, SYLVAIN LEROY NDAGIJIMANA, MAURICE VANNINI, LUCIA GUERZONI, MARIA ELISABETTA Differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis |
topic_facet |
ELECTRONIC NOSE FEATURE SELECTION SEAFOOD STORAGE TIME |
description |
Electronic nose devices are becoming a practical tool for the identification of differences among food products badsed on their origin, intrinsic quality and process conditions. The difficulty in using such instruments is to obtain, from the sensors response patterns, suitable parameters to identify the differences among samples. In this work the electronic nose analyses, trymethilamine determination and panel test were performed on samples of three species of farmed fish []ecentrachus labrax, Sparatus aurata and Salmo salar]tored for 8 days both under ice and abuse temperature of 6°C. Data from electronic nose were analysed choosing a group of features, i.e. average of the last 5 points, maximum point, average of the whole points and average of the signal resposnse characterised by the highest variation. A polynomial regression was performed on the different features in order to identify the contribution of the sensors to the sample response patterns. The data from the best sensors were then used to create an optimum feature (mixed feature). A principal component analysis (PCA)was performed on the data of all the features and the degree of separation of the tridimensional scatterplots used as a selective tool. Based on the results obtained, the features "average of the last 5 points" and "mixed feature" gave a good discrimination of the samples, "mixed feature" being the best. The scatterplot from "mixed feature" data allowed the separation of the fish samples based on species, freshness and storage time. The evolution overtime of the scores of the PCA, accounting for the highest variation of the best two features, was correlated both with TMA content and the overall evaluation of the product given by panelists. |
author2 |
S. Sado Kamden M. Ndagijimana L. Vannini M.E. Guerzoni |
format |
Article in Journal/Newspaper |
author |
SADO KAMDEM, SYLVAIN LEROY NDAGIJIMANA, MAURICE VANNINI, LUCIA GUERZONI, MARIA ELISABETTA |
author_facet |
SADO KAMDEM, SYLVAIN LEROY NDAGIJIMANA, MAURICE VANNINI, LUCIA GUERZONI, MARIA ELISABETTA |
author_sort |
SADO KAMDEM, SYLVAIN LEROY |
title |
Differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis |
title_short |
Differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis |
title_full |
Differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis |
title_fullStr |
Differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis |
title_full_unstemmed |
Differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis |
title_sort |
differentiation of fresh seafood products and storage time using an electronic nose: features selection for data analysis |
publishDate |
2007 |
url |
http://hdl.handle.net/11585/58285 https://www.chiriottieditori.it/ojs/index.php/ijfs/issue/view/31/IJFS183-SLIM2006 |
genre |
Salmo salar |
genre_facet |
Salmo salar |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000208675300072 volume:Special issue (SLIM 2006) firstpage:393 lastpage:399 numberofpages:7 journal:ITALIAN JOURNAL OF FOOD SCIENCE http://hdl.handle.net/11585/58285 https://www.chiriottieditori.it/ojs/index.php/ijfs/issue/view/31/IJFS183-SLIM2006 |
op_rights |
info:eu-repo/semantics/closedAccess |
_version_ |
1810474821246517248 |