Application of agglomerative hierarchical clustering to identify consumer tomato preferences: influence of physicochemical and sensory characteristics on consumer response
A multiple regression model was developed to predict the acceptability of the four tomato varieties studied (Aranka, Cherry, Beef and Pitenza). Agglomerative hierarchical clustering showed the presence of four consumer clusters. One cluster preferred small tomatoes (Aranka and Cherry) and another cl...
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Veröffentlicht in: | Journal of the science of food and agriculture 2006-03, Vol.86 (4), p.493-499 |
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description | A multiple regression model was developed to predict the acceptability of the four tomato varieties studied (Aranka, Cherry, Beef and Pitenza). Agglomerative hierarchical clustering showed the presence of four consumer clusters. One cluster preferred small tomatoes (Aranka and Cherry) and another cluster the larger tomatoes (Beef and Pitenza). In the sensorial analysis Aranka was the preferred variety, scoring more highly in taste, odour, acidity, sweetness and hardness. In the physicochemical analysis Aranka also obtained the highest values for titratable acidity (TA) and sugars (SSC), confirming that these parameters are important in tomato flavour. Lower values for both sets of parameters were reflected by lower consumer acceptability, with Beef and Pitenza receiving the lowest score for these flavours attributes (except odour). A significant correlation between the sensorial and physicochemical parameters was also observed: odour was positively correlated with calibre, while taste, acidity, hardness and acceptability were negatively correlated with calibre, pH and SSC/TA and positively correlated with SSC and TA. Copyright © 2005 Society of Chemical Industry |
doi_str_mv | 10.1002/jsfa.2392 |
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Agglomerative hierarchical clustering showed the presence of four consumer clusters. One cluster preferred small tomatoes (Aranka and Cherry) and another cluster the larger tomatoes (Beef and Pitenza). In the sensorial analysis Aranka was the preferred variety, scoring more highly in taste, odour, acidity, sweetness and hardness. In the physicochemical analysis Aranka also obtained the highest values for titratable acidity (TA) and sugars (SSC), confirming that these parameters are important in tomato flavour. Lower values for both sets of parameters were reflected by lower consumer acceptability, with Beef and Pitenza receiving the lowest score for these flavours attributes (except odour). A significant correlation between the sensorial and physicochemical parameters was also observed: odour was positively correlated with calibre, while taste, acidity, hardness and acceptability were negatively correlated with calibre, pH and SSC/TA and positively correlated with SSC and TA. Copyright © 2005 Society of Chemical Industry</description><identifier>ISSN: 0022-5142</identifier><identifier>EISSN: 1097-0010</identifier><identifier>DOI: 10.1002/jsfa.2392</identifier><identifier>CODEN: JSFAAE</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>acceptance ; agglomerative hierarchical clustering ; Biological and medical sciences ; Consumer attitudes ; Flavors ; flavour ; Food industries ; Food science ; Fruit and vegetable industries ; Fundamental and applied biological sciences. Psychology ; Lycopersicon esculentum ; Odors ; principal component analysis ; Prunus ; Regression analysis ; Tomatoes</subject><ispartof>Journal of the science of food and agriculture, 2006-03, Vol.86 (4), p.493-499</ispartof><rights>Copyright © 2005 Society of Chemical Industry</rights><rights>2006 INIST-CNRS</rights><rights>Copyright John Wiley and Sons, Limited Mar 2006</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4262-55cd98debdd7ff2ed72c97da4301a29a952bf681c454b073430eb7463092e9b23</citedby><cites>FETCH-LOGICAL-c4262-55cd98debdd7ff2ed72c97da4301a29a952bf681c454b073430eb7463092e9b23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjsfa.2392$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjsfa.2392$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17468863$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Serrano-Megías, Marta</creatorcontrib><creatorcontrib>López-Nicolás, Jose Manuel</creatorcontrib><title>Application of agglomerative hierarchical clustering to identify consumer tomato preferences: influence of physicochemical and sensory characteristics on consumer response</title><title>Journal of the science of food and agriculture</title><addtitle>J. Sci. Food Agric</addtitle><description>A multiple regression model was developed to predict the acceptability of the four tomato varieties studied (Aranka, Cherry, Beef and Pitenza). Agglomerative hierarchical clustering showed the presence of four consumer clusters. One cluster preferred small tomatoes (Aranka and Cherry) and another cluster the larger tomatoes (Beef and Pitenza). In the sensorial analysis Aranka was the preferred variety, scoring more highly in taste, odour, acidity, sweetness and hardness. In the physicochemical analysis Aranka also obtained the highest values for titratable acidity (TA) and sugars (SSC), confirming that these parameters are important in tomato flavour. Lower values for both sets of parameters were reflected by lower consumer acceptability, with Beef and Pitenza receiving the lowest score for these flavours attributes (except odour). A significant correlation between the sensorial and physicochemical parameters was also observed: odour was positively correlated with calibre, while taste, acidity, hardness and acceptability were negatively correlated with calibre, pH and SSC/TA and positively correlated with SSC and TA. Copyright © 2005 Society of Chemical Industry</description><subject>acceptance</subject><subject>agglomerative hierarchical clustering</subject><subject>Biological and medical sciences</subject><subject>Consumer attitudes</subject><subject>Flavors</subject><subject>flavour</subject><subject>Food industries</subject><subject>Food science</subject><subject>Fruit and vegetable industries</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Lycopersicon esculentum</subject><subject>Odors</subject><subject>principal component analysis</subject><subject>Prunus</subject><subject>Regression analysis</subject><subject>Tomatoes</subject><issn>0022-5142</issn><issn>1097-0010</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNqFkVGL1DAQgIsouJ4--A-KoOBD75I0bRrflsO7U-4UPEXxJaTpdJu1TXpJq7e_yT_p1F1OEMSnDDPffGRmkuQpJceUEHayja0-Zrlk95IVJVJkhFByP1lhjWUF5exh8ijGLSFEyrJcJT_X49hboyfrXerbVG82vR8gYOI7pJ3FKJgOgT41_RwnCNZt0smntgE32XaXGu_ijB2YHDQWxgAtBHAG4qvUurafl3hxj90uWuNNB8NvoXZNGsFFH9DS6aDNoo-TNTHF39yJA8QRY3icPGh1H-HJ4T1KPp29_nh6kV2-P39zur7MDGclTlmYRlYN1E0j2pZBI5iRotE8J1QzqWXB6rasqOEFr4nIMQ-14GVOJANZs_woebH3jsHfzBAnNdhooO-1Az9HxSQVlBfkvyAVpBSCSwSf_QVu_RwcDqEYY4KVsuAIvdxDJvgYcYtqDHbQYacoUctx1XJctRwX2ecHoY64yjZoZ2z804DjVFWZI3ey537YHnb_Fqq312frgznbd-Ah4PauQ4dvqhS5KNTnd-fq6mv15QO_ulZF_gvXtcfF</recordid><startdate>200603</startdate><enddate>200603</enddate><creator>Serrano-Megías, Marta</creator><creator>López-Nicolás, Jose Manuel</creator><general>John Wiley & Sons, Ltd</general><general>Wiley</general><general>John Wiley and Sons, Limited</general><scope>BSCLL</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QL</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7ST</scope><scope>7T5</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7TM</scope><scope>7U5</scope><scope>7U9</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>H94</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7N</scope><scope>P64</scope><scope>SOI</scope></search><sort><creationdate>200603</creationdate><title>Application of agglomerative hierarchical clustering to identify consumer tomato preferences: influence of physicochemical and sensory characteristics on consumer response</title><author>Serrano-Megías, Marta ; López-Nicolás, Jose Manuel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4262-55cd98debdd7ff2ed72c97da4301a29a952bf681c454b073430eb7463092e9b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>acceptance</topic><topic>agglomerative hierarchical clustering</topic><topic>Biological and medical sciences</topic><topic>Consumer attitudes</topic><topic>Flavors</topic><topic>flavour</topic><topic>Food industries</topic><topic>Food science</topic><topic>Fruit and vegetable industries</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Lycopersicon esculentum</topic><topic>Odors</topic><topic>principal component analysis</topic><topic>Prunus</topic><topic>Regression analysis</topic><topic>Tomatoes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Serrano-Megías, Marta</creatorcontrib><creatorcontrib>López-Nicolás, Jose Manuel</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Environment Abstracts</collection><collection>Immunology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Journal of the science of food and agriculture</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Serrano-Megías, Marta</au><au>López-Nicolás, Jose Manuel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of agglomerative hierarchical clustering to identify consumer tomato preferences: influence of physicochemical and sensory characteristics on consumer response</atitle><jtitle>Journal of the science of food and agriculture</jtitle><addtitle>J. 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Lower values for both sets of parameters were reflected by lower consumer acceptability, with Beef and Pitenza receiving the lowest score for these flavours attributes (except odour). A significant correlation between the sensorial and physicochemical parameters was also observed: odour was positively correlated with calibre, while taste, acidity, hardness and acceptability were negatively correlated with calibre, pH and SSC/TA and positively correlated with SSC and TA. Copyright © 2005 Society of Chemical Industry</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/jsfa.2392</doi><tpages>7</tpages></addata></record> |
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subjects | acceptance agglomerative hierarchical clustering Biological and medical sciences Consumer attitudes Flavors flavour Food industries Food science Fruit and vegetable industries Fundamental and applied biological sciences. Psychology Lycopersicon esculentum Odors principal component analysis Prunus Regression analysis Tomatoes |
title | Application of agglomerative hierarchical clustering to identify consumer tomato preferences: influence of physicochemical and sensory characteristics on consumer response |
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