An Advanced Colour Calibration Method for Fish Freshness Assessment: a Comparison Between Standard and Passive Refrigeration Modalities
Freshness represents a pivotal aspect in fish product for both security and quality. Its evaluation still represents the key factor driving the consumer’ choices. Fish appearance is affected by many different factors that demand the contribution of different disciplines to be understood: from the ph...
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Veröffentlicht in: | Food and bioprocess technology 2013-08, Vol.6 (8), p.2190-2195 |
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creator | Costa, Corrado Antonucci, Francesca Menesatti, Paolo Pallottino, Federico Boglione, Clara Cataudella, Stefano |
description | Freshness represents a pivotal aspect in fish product for both security and quality. Its evaluation still represents the key factor driving the consumer’ choices. Fish appearance is affected by many different factors that demand the contribution of different disciplines to be understood: from the physical and optical properties to the slaughtering and post-slaughtering conditions. An innovative preservation system is represented by the Passive Refrigeration PRS™ developed for the preservation and transport of perishable food products. Scientific methods for product freshness evaluation may be conveniently divided into two categories: sensorial and instrumental. In this study, an instrumental method of colour calibration and discrimination is proposed at pilot scale for automatic evaluation of gilthead seabream (
Sparus aurata
) freshness. We propose a non-destructive method based on the colorimetric imaging of the whole external body of seabreams to evaluate through multivariate partial least squares which approach the differences in the freshness preservation under four refrigeration modalities. The matrix of the independent variables is represented by RGB values for each pixel belonging to an extracted region of interest (129,633 values). The dependent variable is composed by two dummy variable corresponding to fresh (T
0
) or non-fresh (T
2
) individuals. T
1
individuals were used as external test. The results quantified significant colorimetric differences between fresh and non-fresh fish. All fish used to create the model (T
0
and T
2
) were correctly classified as fresh or non-fresh, while external test individuals (T
1
) were all classified as fresh. The proposed imaging method merges different image analysis techniques: (a) colorimetric calibration, (b) morphometric superimposition and (c) partial least square discriminant analysis modelling. This innovative and non-destructive approach allows the automatic assessment of fish freshness. |
doi_str_mv | 10.1007/s11947-011-0773-6 |
format | Article |
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Sparus aurata
) freshness. We propose a non-destructive method based on the colorimetric imaging of the whole external body of seabreams to evaluate through multivariate partial least squares which approach the differences in the freshness preservation under four refrigeration modalities. The matrix of the independent variables is represented by RGB values for each pixel belonging to an extracted region of interest (129,633 values). The dependent variable is composed by two dummy variable corresponding to fresh (T
0
) or non-fresh (T
2
) individuals. T
1
individuals were used as external test. The results quantified significant colorimetric differences between fresh and non-fresh fish. All fish used to create the model (T
0
and T
2
) were correctly classified as fresh or non-fresh, while external test individuals (T
1
) were all classified as fresh. The proposed imaging method merges different image analysis techniques: (a) colorimetric calibration, (b) morphometric superimposition and (c) partial least square discriminant analysis modelling. This innovative and non-destructive approach allows the automatic assessment of fish freshness.</description><identifier>ISSN: 1935-5130</identifier><identifier>EISSN: 1935-5149</identifier><identifier>DOI: 10.1007/s11947-011-0773-6</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Agriculture ; Automatic pilots ; Biotechnology ; Calibration ; Chemistry ; Chemistry and Materials Science ; Chemistry/Food Science ; Color ; Colorimetry ; Communication ; Dependent variables ; Discriminant analysis ; Evaluation ; Fish ; Fishery products ; Food Science ; Freshness ; Image analysis ; Image processing ; Independent variables ; Least squares ; Marine ; Nondestructive testing ; Optical properties ; Perishable foods ; Preservation ; Refrigeration ; Slaughter ; Sparus aurata</subject><ispartof>Food and bioprocess technology, 2013-08, Vol.6 (8), p.2190-2195</ispartof><rights>Springer Science+Business Media, LLC 2012</rights><rights>Springer Science+Business Media, LLC 2012.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-9ab56361b2ff431ad930ed1899d8eb8475c748f5c39969e6b17a70471ba20a6d3</citedby><cites>FETCH-LOGICAL-c392t-9ab56361b2ff431ad930ed1899d8eb8475c748f5c39969e6b17a70471ba20a6d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11947-011-0773-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11947-011-0773-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Costa, Corrado</creatorcontrib><creatorcontrib>Antonucci, Francesca</creatorcontrib><creatorcontrib>Menesatti, Paolo</creatorcontrib><creatorcontrib>Pallottino, Federico</creatorcontrib><creatorcontrib>Boglione, Clara</creatorcontrib><creatorcontrib>Cataudella, Stefano</creatorcontrib><title>An Advanced Colour Calibration Method for Fish Freshness Assessment: a Comparison Between Standard and Passive Refrigeration Modalities</title><title>Food and bioprocess technology</title><addtitle>Food Bioprocess Technol</addtitle><description>Freshness represents a pivotal aspect in fish product for both security and quality. Its evaluation still represents the key factor driving the consumer’ choices. Fish appearance is affected by many different factors that demand the contribution of different disciplines to be understood: from the physical and optical properties to the slaughtering and post-slaughtering conditions. An innovative preservation system is represented by the Passive Refrigeration PRS™ developed for the preservation and transport of perishable food products. Scientific methods for product freshness evaluation may be conveniently divided into two categories: sensorial and instrumental. In this study, an instrumental method of colour calibration and discrimination is proposed at pilot scale for automatic evaluation of gilthead seabream (
Sparus aurata
) freshness. We propose a non-destructive method based on the colorimetric imaging of the whole external body of seabreams to evaluate through multivariate partial least squares which approach the differences in the freshness preservation under four refrigeration modalities. The matrix of the independent variables is represented by RGB values for each pixel belonging to an extracted region of interest (129,633 values). The dependent variable is composed by two dummy variable corresponding to fresh (T
0
) or non-fresh (T
2
) individuals. T
1
individuals were used as external test. The results quantified significant colorimetric differences between fresh and non-fresh fish. All fish used to create the model (T
0
and T
2
) were correctly classified as fresh or non-fresh, while external test individuals (T
1
) were all classified as fresh. The proposed imaging method merges different image analysis techniques: (a) colorimetric calibration, (b) morphometric superimposition and (c) partial least square discriminant analysis modelling. This innovative and non-destructive approach allows the automatic assessment of fish freshness.</description><subject>Agriculture</subject><subject>Automatic pilots</subject><subject>Biotechnology</subject><subject>Calibration</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Chemistry/Food Science</subject><subject>Color</subject><subject>Colorimetry</subject><subject>Communication</subject><subject>Dependent variables</subject><subject>Discriminant analysis</subject><subject>Evaluation</subject><subject>Fish</subject><subject>Fishery products</subject><subject>Food Science</subject><subject>Freshness</subject><subject>Image analysis</subject><subject>Image processing</subject><subject>Independent variables</subject><subject>Least squares</subject><subject>Marine</subject><subject>Nondestructive testing</subject><subject>Optical properties</subject><subject>Perishable foods</subject><subject>Preservation</subject><subject>Refrigeration</subject><subject>Slaughter</subject><subject>Sparus aurata</subject><issn>1935-5130</issn><issn>1935-5149</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp1kc1O3DAUhaMKpPL3AN1Z6oZNwDd24ri76YgplUAgWtaWE990jDL21DcD4gl47Xo0hUqVWJ27-M6xdU5RfAJ-BpyrcwLQUpUcoORKibL5UByAFnVZg9R7b7fgH4tDogfOGy5BHBQvs8Bm7tGGHh2bxzFuEpvb0XfJTj4Gdo3TMjo2xMQWnpZskZCWAYnYjCjLCsP0hdlsXa1t8pQtX3F6Qgzsx2SDs8mxLOzWEvlHZHc4JP8LX9Ojy29NHum42B_sSHjyV4-K-8XFz_lleXXz7ft8dlX2QldTqW1XN6KBrhoGKcA6LTg6aLV2LXatVHWvZDvUmdaNxqYDZRWXCjpbcds4cVSc7nLXKf7eIE1m5anHcbQB44YMyLqtZa2gyejn_9CH3E7IvzOVBN7mroXMFOyoPkWihINZJ7-y6dkAN9tpzG4ak3GzncZsk6udhzIbchv_kt83_QHbc5G-</recordid><startdate>20130801</startdate><enddate>20130801</enddate><creator>Costa, Corrado</creator><creator>Antonucci, Francesca</creator><creator>Menesatti, Paolo</creator><creator>Pallottino, Federico</creator><creator>Boglione, Clara</creator><creator>Cataudella, Stefano</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M0K</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>F1W</scope><scope>H95</scope><scope>L.G</scope></search><sort><creationdate>20130801</creationdate><title>An Advanced Colour Calibration Method for Fish Freshness Assessment: a Comparison Between Standard and Passive Refrigeration Modalities</title><author>Costa, Corrado ; Antonucci, Francesca ; Menesatti, Paolo ; Pallottino, Federico ; Boglione, Clara ; Cataudella, Stefano</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-9ab56361b2ff431ad930ed1899d8eb8475c748f5c39969e6b17a70471ba20a6d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Agriculture</topic><topic>Automatic pilots</topic><topic>Biotechnology</topic><topic>Calibration</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Chemistry/Food Science</topic><topic>Color</topic><topic>Colorimetry</topic><topic>Communication</topic><topic>Dependent variables</topic><topic>Discriminant analysis</topic><topic>Evaluation</topic><topic>Fish</topic><topic>Fishery products</topic><topic>Food Science</topic><topic>Freshness</topic><topic>Image analysis</topic><topic>Image processing</topic><topic>Independent variables</topic><topic>Least squares</topic><topic>Marine</topic><topic>Nondestructive testing</topic><topic>Optical properties</topic><topic>Perishable foods</topic><topic>Preservation</topic><topic>Refrigeration</topic><topic>Slaughter</topic><topic>Sparus aurata</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Costa, Corrado</creatorcontrib><creatorcontrib>Antonucci, Francesca</creatorcontrib><creatorcontrib>Menesatti, Paolo</creatorcontrib><creatorcontrib>Pallottino, Federico</creatorcontrib><creatorcontrib>Boglione, Clara</creatorcontrib><creatorcontrib>Cataudella, Stefano</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Agricultural Science Database</collection><collection>Engineering Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Food and bioprocess technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Costa, Corrado</au><au>Antonucci, Francesca</au><au>Menesatti, Paolo</au><au>Pallottino, Federico</au><au>Boglione, Clara</au><au>Cataudella, Stefano</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Advanced Colour Calibration Method for Fish Freshness Assessment: a Comparison Between Standard and Passive Refrigeration Modalities</atitle><jtitle>Food and bioprocess technology</jtitle><stitle>Food Bioprocess Technol</stitle><date>2013-08-01</date><risdate>2013</risdate><volume>6</volume><issue>8</issue><spage>2190</spage><epage>2195</epage><pages>2190-2195</pages><issn>1935-5130</issn><eissn>1935-5149</eissn><abstract>Freshness represents a pivotal aspect in fish product for both security and quality. Its evaluation still represents the key factor driving the consumer’ choices. Fish appearance is affected by many different factors that demand the contribution of different disciplines to be understood: from the physical and optical properties to the slaughtering and post-slaughtering conditions. An innovative preservation system is represented by the Passive Refrigeration PRS™ developed for the preservation and transport of perishable food products. Scientific methods for product freshness evaluation may be conveniently divided into two categories: sensorial and instrumental. In this study, an instrumental method of colour calibration and discrimination is proposed at pilot scale for automatic evaluation of gilthead seabream (
Sparus aurata
) freshness. We propose a non-destructive method based on the colorimetric imaging of the whole external body of seabreams to evaluate through multivariate partial least squares which approach the differences in the freshness preservation under four refrigeration modalities. The matrix of the independent variables is represented by RGB values for each pixel belonging to an extracted region of interest (129,633 values). The dependent variable is composed by two dummy variable corresponding to fresh (T
0
) or non-fresh (T
2
) individuals. T
1
individuals were used as external test. The results quantified significant colorimetric differences between fresh and non-fresh fish. All fish used to create the model (T
0
and T
2
) were correctly classified as fresh or non-fresh, while external test individuals (T
1
) were all classified as fresh. The proposed imaging method merges different image analysis techniques: (a) colorimetric calibration, (b) morphometric superimposition and (c) partial least square discriminant analysis modelling. This innovative and non-destructive approach allows the automatic assessment of fish freshness.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s11947-011-0773-6</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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source | SpringerLink Journals - AutoHoldings |
subjects | Agriculture Automatic pilots Biotechnology Calibration Chemistry Chemistry and Materials Science Chemistry/Food Science Color Colorimetry Communication Dependent variables Discriminant analysis Evaluation Fish Fishery products Food Science Freshness Image analysis Image processing Independent variables Least squares Marine Nondestructive testing Optical properties Perishable foods Preservation Refrigeration Slaughter Sparus aurata |
title | An Advanced Colour Calibration Method for Fish Freshness Assessment: a Comparison Between Standard and Passive Refrigeration Modalities |
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