Comparison between quantitative descriptive analysis and flash profile in profiling the sensory properties of commercial red sufu (Chinese fermented soybean curd)
BACKGROUND Red sufu is a type of sufu produced by solid‐state fermentation of soybean curd and coloration with red mold rice. The purposes of this study were: (i) to characterize commercial red sufu samples using the quantitative descriptive analysis (QDA) and flash profile (FP) by ten trained and t...
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| Veröffentlicht in: | Journal of the science of food and agriculture 2019-04, Vol.99 (6), p.3024-3033 |
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| creator | He, Wenmeng Chung, Hau Yin |
| description | BACKGROUND
Red sufu is a type of sufu produced by solid‐state fermentation of soybean curd and coloration with red mold rice. The purposes of this study were: (i) to characterize commercial red sufu samples using the quantitative descriptive analysis (QDA) and flash profile (FP) by ten trained and ten untrained panelists, respectively; (ii) to compare the differences in panel performance, descriptive abilities and sensory maps between the two methodologies; and (iii) to compare the efficiency between QDA and FP using red sufu as the matrix. Techniques in multivariate analysis were utilized to explore the data.
RESULTS
Results from generalized procrustes analysis (GPA) showed that panel performance by QDA was more repeatable and reached higher homogeneity than that by FP. Despite the confidence ellipse results of the 12 red sufus being better discriminated by QDA, the RV coefficient was high (RV = 0.852) between the configurations of the two‐dimensional model (F1 and F2) of the two methodologies, indicating that the two methods are similar and closely related. Overall, QDA provided more accurate and detailed information, while FP provided a similar sensory map on product location and descriptive results.
CONCLUSION
The FP technique appeared to be an efficient alternative approach to quickly evaluate sensory properties, including appearance, flavor, aroma and textural properties of an array of red sufu products. © 2018 Society of Chemical Industry |
| doi_str_mv | 10.1002/jsfa.9516 |
| format | Article |
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Red sufu is a type of sufu produced by solid‐state fermentation of soybean curd and coloration with red mold rice. The purposes of this study were: (i) to characterize commercial red sufu samples using the quantitative descriptive analysis (QDA) and flash profile (FP) by ten trained and ten untrained panelists, respectively; (ii) to compare the differences in panel performance, descriptive abilities and sensory maps between the two methodologies; and (iii) to compare the efficiency between QDA and FP using red sufu as the matrix. Techniques in multivariate analysis were utilized to explore the data.
RESULTS
Results from generalized procrustes analysis (GPA) showed that panel performance by QDA was more repeatable and reached higher homogeneity than that by FP. Despite the confidence ellipse results of the 12 red sufus being better discriminated by QDA, the RV coefficient was high (RV = 0.852) between the configurations of the two‐dimensional model (F1 and F2) of the two methodologies, indicating that the two methods are similar and closely related. Overall, QDA provided more accurate and detailed information, while FP provided a similar sensory map on product location and descriptive results.
CONCLUSION
The FP technique appeared to be an efficient alternative approach to quickly evaluate sensory properties, including appearance, flavor, aroma and textural properties of an array of red sufu products. © 2018 Society of Chemical Industry</description><identifier>ISSN: 0022-5142</identifier><identifier>EISSN: 1097-0010</identifier><identifier>DOI: 10.1002/jsfa.9516</identifier><identifier>PMID: 30488614</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>Adult ; Aroma ; Coloration ; confidence ellipse ; Female ; Fermentation ; Fermented food ; Fermented Foods - analysis ; Fermented Foods - economics ; flash profile ; Flavor ; generalized procrustes analysis ; Homogeneity ; Humans ; Male ; Multivariate analysis ; Organic chemistry ; principal component analysis ; quantitative descriptive analysis ; RV coefficient ; Sensory evaluation ; Sensory properties ; Solid state fermentation ; Soy Foods - analysis ; Soy Foods - economics ; Soybeans ; Taste ; Tofu ; Young Adult</subject><ispartof>Journal of the science of food and agriculture, 2019-04, Vol.99 (6), p.3024-3033</ispartof><rights>2018 Society of Chemical Industry</rights><rights>2018 Society of Chemical Industry.</rights><rights>2019 Society of Chemical Industry</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3536-f7fff5c55e057ecbac2dc150fe84c588c583ab3222cba375e35feceae794df263</citedby><cites>FETCH-LOGICAL-c3536-f7fff5c55e057ecbac2dc150fe84c588c583ab3222cba375e35feceae794df263</cites><orcidid>0000-0002-9054-484X ; 0000-0001-6776-8151</orcidid></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.9516$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjsfa.9516$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30488614$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>He, Wenmeng</creatorcontrib><creatorcontrib>Chung, Hau Yin</creatorcontrib><title>Comparison between quantitative descriptive analysis and flash profile in profiling the sensory properties of commercial red sufu (Chinese fermented soybean curd)</title><title>Journal of the science of food and agriculture</title><addtitle>J Sci Food Agric</addtitle><description>BACKGROUND
Red sufu is a type of sufu produced by solid‐state fermentation of soybean curd and coloration with red mold rice. The purposes of this study were: (i) to characterize commercial red sufu samples using the quantitative descriptive analysis (QDA) and flash profile (FP) by ten trained and ten untrained panelists, respectively; (ii) to compare the differences in panel performance, descriptive abilities and sensory maps between the two methodologies; and (iii) to compare the efficiency between QDA and FP using red sufu as the matrix. Techniques in multivariate analysis were utilized to explore the data.
RESULTS
Results from generalized procrustes analysis (GPA) showed that panel performance by QDA was more repeatable and reached higher homogeneity than that by FP. Despite the confidence ellipse results of the 12 red sufus being better discriminated by QDA, the RV coefficient was high (RV = 0.852) between the configurations of the two‐dimensional model (F1 and F2) of the two methodologies, indicating that the two methods are similar and closely related. Overall, QDA provided more accurate and detailed information, while FP provided a similar sensory map on product location and descriptive results.
CONCLUSION
The FP technique appeared to be an efficient alternative approach to quickly evaluate sensory properties, including appearance, flavor, aroma and textural properties of an array of red sufu products. © 2018 Society of Chemical Industry</description><subject>Adult</subject><subject>Aroma</subject><subject>Coloration</subject><subject>confidence ellipse</subject><subject>Female</subject><subject>Fermentation</subject><subject>Fermented food</subject><subject>Fermented Foods - analysis</subject><subject>Fermented Foods - economics</subject><subject>flash profile</subject><subject>Flavor</subject><subject>generalized procrustes analysis</subject><subject>Homogeneity</subject><subject>Humans</subject><subject>Male</subject><subject>Multivariate analysis</subject><subject>Organic chemistry</subject><subject>principal component analysis</subject><subject>quantitative descriptive analysis</subject><subject>RV coefficient</subject><subject>Sensory evaluation</subject><subject>Sensory properties</subject><subject>Solid state fermentation</subject><subject>Soy Foods - analysis</subject><subject>Soy Foods - economics</subject><subject>Soybeans</subject><subject>Taste</subject><subject>Tofu</subject><subject>Young Adult</subject><issn>0022-5142</issn><issn>1097-0010</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kc1q3TAQhUVpaW7TLvoCRdBNsnCiH8s_y3Bp2oZAFmnXRpZHvbrYkqOxE_w6fdLKubddBDog5jDzcRBzCPnI2QVnTFzu0eqLWvHiFdlwVpcZY5y9Jpu0E5niuTgh7xD3jLG6Loq35ESyvKoKnm_I720YRh0dBk9bmJ4APH2YtZ_cpCf3CLQDNNGNz1p73S_oMImO2l7jjo4xWNcDdf4onf9Fpx1QBI8hLut0hDg5QBosNWEYIBqnexqhozjbmZ5td84DArUQB_DTOg9LC9pTM8fu_D15Y3WP8OHYT8nP6y8_tt-y27uv37dXt5mRShaZLa21yigFTJVgWm1EZ7hiFqrcqKpKT-pWCiHSTpYKpLJgQENZ550VhTwlZwff9OWHGXBqBocG-l57CDM2gstaFWWqhH5-ge7DHNN1VqrmkgkpWaLOD5SJATGCbcboBh2XhrNmDa5Zg2vW4BL76eg4twN0_8i_SSXg8gA8pXMv_3dqbu6vr54t_wBAHadY</recordid><startdate>201904</startdate><enddate>201904</enddate><creator>He, Wenmeng</creator><creator>Chung, Hau Yin</creator><general>John Wiley & Sons, Ltd</general><general>John Wiley and Sons, Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</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><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-9054-484X</orcidid><orcidid>https://orcid.org/0000-0001-6776-8151</orcidid></search><sort><creationdate>201904</creationdate><title>Comparison between quantitative descriptive analysis and flash profile in profiling the sensory properties of commercial red sufu (Chinese fermented soybean curd)</title><author>He, Wenmeng ; Chung, Hau Yin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3536-f7fff5c55e057ecbac2dc150fe84c588c583ab3222cba375e35feceae794df263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adult</topic><topic>Aroma</topic><topic>Coloration</topic><topic>confidence ellipse</topic><topic>Female</topic><topic>Fermentation</topic><topic>Fermented food</topic><topic>Fermented Foods - analysis</topic><topic>Fermented Foods - economics</topic><topic>flash profile</topic><topic>Flavor</topic><topic>generalized procrustes analysis</topic><topic>Homogeneity</topic><topic>Humans</topic><topic>Male</topic><topic>Multivariate analysis</topic><topic>Organic chemistry</topic><topic>principal component analysis</topic><topic>quantitative descriptive analysis</topic><topic>RV coefficient</topic><topic>Sensory evaluation</topic><topic>Sensory properties</topic><topic>Solid state fermentation</topic><topic>Soy Foods - analysis</topic><topic>Soy Foods - economics</topic><topic>Soybeans</topic><topic>Taste</topic><topic>Tofu</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>He, Wenmeng</creatorcontrib><creatorcontrib>Chung, Hau Yin</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</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><collection>MEDLINE - Academic</collection><jtitle>Journal of the science of food and agriculture</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>He, Wenmeng</au><au>Chung, Hau Yin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison between quantitative descriptive analysis and flash profile in profiling the sensory properties of commercial red sufu (Chinese fermented soybean curd)</atitle><jtitle>Journal of the science of food and agriculture</jtitle><addtitle>J Sci Food Agric</addtitle><date>2019-04</date><risdate>2019</risdate><volume>99</volume><issue>6</issue><spage>3024</spage><epage>3033</epage><pages>3024-3033</pages><issn>0022-5142</issn><eissn>1097-0010</eissn><abstract>BACKGROUND
Red sufu is a type of sufu produced by solid‐state fermentation of soybean curd and coloration with red mold rice. The purposes of this study were: (i) to characterize commercial red sufu samples using the quantitative descriptive analysis (QDA) and flash profile (FP) by ten trained and ten untrained panelists, respectively; (ii) to compare the differences in panel performance, descriptive abilities and sensory maps between the two methodologies; and (iii) to compare the efficiency between QDA and FP using red sufu as the matrix. Techniques in multivariate analysis were utilized to explore the data.
RESULTS
Results from generalized procrustes analysis (GPA) showed that panel performance by QDA was more repeatable and reached higher homogeneity than that by FP. Despite the confidence ellipse results of the 12 red sufus being better discriminated by QDA, the RV coefficient was high (RV = 0.852) between the configurations of the two‐dimensional model (F1 and F2) of the two methodologies, indicating that the two methods are similar and closely related. Overall, QDA provided more accurate and detailed information, while FP provided a similar sensory map on product location and descriptive results.
CONCLUSION
The FP technique appeared to be an efficient alternative approach to quickly evaluate sensory properties, including appearance, flavor, aroma and textural properties of an array of red sufu products. © 2018 Society of Chemical Industry</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><pmid>30488614</pmid><doi>10.1002/jsfa.9516</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-9054-484X</orcidid><orcidid>https://orcid.org/0000-0001-6776-8151</orcidid></addata></record> |
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| ispartof | Journal of the science of food and agriculture, 2019-04, Vol.99 (6), p.3024-3033 |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Adult Aroma Coloration confidence ellipse Female Fermentation Fermented food Fermented Foods - analysis Fermented Foods - economics flash profile Flavor generalized procrustes analysis Homogeneity Humans Male Multivariate analysis Organic chemistry principal component analysis quantitative descriptive analysis RV coefficient Sensory evaluation Sensory properties Solid state fermentation Soy Foods - analysis Soy Foods - economics Soybeans Taste Tofu Young Adult |
| title | Comparison between quantitative descriptive analysis and flash profile in profiling the sensory properties of commercial red sufu (Chinese fermented soybean curd) |
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