simple method based on image processing to estimate primary pigment levels of Sichuan Dark Tea during post-fermentation
A new method quantifying the primary pigments of Sichuan Dark Tea (SDT) rapidly based on the image processing was established. The correlations between the color parameters obtained from SDT images by employing the scanner and Photoshop software and the primary pigment levels were analyzed, and the...
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| Veröffentlicht in: | European food research & technology 2014-08, Vol.239 (2), p.357-363 |
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| creator | Zou, Yao Qi, Guinian Chen, Shengxiang Tan, Liqiang Li, Wei Liu, Tingting |
| description | A new method quantifying the primary pigments of Sichuan Dark Tea (SDT) rapidly based on the image processing was established. The correlations between the color parameters obtained from SDT images by employing the scanner and Photoshop software and the primary pigment levels were analyzed, and the regression models based on these color parameters were established as well. The results showed that the contents of theaflavin, thearubigins and theabrownin significantly correlated with the parameters of RGB and CMYK modes. The contents of chlorophyll (Chl) Chl-a and Chl-b had high correlation with the parameters of RGB and HSB modes. All the regression models established had the best goodness of fit, in the 95 % confidence intervals, the prediction error of them varied from −3.12 to 2.05 %. Thus, the primary pigments of SDT during post-fermentation could be excellently quantified by the image processing methods developed here. |
| doi_str_mv | 10.1007/s00217-014-2219-7 |
| format | Article |
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The correlations between the color parameters obtained from SDT images by employing the scanner and Photoshop software and the primary pigment levels were analyzed, and the regression models based on these color parameters were established as well. The results showed that the contents of theaflavin, thearubigins and theabrownin significantly correlated with the parameters of RGB and CMYK modes. The contents of chlorophyll (Chl) Chl-a and Chl-b had high correlation with the parameters of RGB and HSB modes. All the regression models established had the best goodness of fit, in the 95 % confidence intervals, the prediction error of them varied from −3.12 to 2.05 %. Thus, the primary pigments of SDT during post-fermentation could be excellently quantified by the image processing methods developed here.</description><identifier>ISSN: 1438-2377</identifier><identifier>EISSN: 1438-2385</identifier><identifier>DOI: 10.1007/s00217-014-2219-7</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Agriculture ; Analytical Chemistry ; Biotechnology ; Chemistry ; Chemistry and Materials Science ; Chlorophyll ; color ; computer software ; confidence interval ; Correlation analysis ; Fermentation ; Food ; Food Science ; Forestry ; image analysis ; Image processing systems ; Methods ; new methods ; Pigments ; prediction ; processing technology ; regression analysis ; Scanners ; Short Communication ; Software ; Studies ; Tea</subject><ispartof>European food research & technology, 2014-08, Vol.239 (2), p.357-363</ispartof><rights>Springer-Verlag Berlin Heidelberg 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c373t-be5f99d86c25c963ec84b8b8b57abfd74130a7cef41f6d159fc6f17ce3843f093</citedby><cites>FETCH-LOGICAL-c373t-be5f99d86c25c963ec84b8b8b57abfd74130a7cef41f6d159fc6f17ce3843f093</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/s00217-014-2219-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00217-014-2219-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Zou, Yao</creatorcontrib><creatorcontrib>Qi, Guinian</creatorcontrib><creatorcontrib>Chen, Shengxiang</creatorcontrib><creatorcontrib>Tan, Liqiang</creatorcontrib><creatorcontrib>Li, Wei</creatorcontrib><creatorcontrib>Liu, Tingting</creatorcontrib><title>simple method based on image processing to estimate primary pigment levels of Sichuan Dark Tea during post-fermentation</title><title>European food research & technology</title><addtitle>Eur Food Res Technol</addtitle><description>A new method quantifying the primary pigments of Sichuan Dark Tea (SDT) rapidly based on the image processing was established. The correlations between the color parameters obtained from SDT images by employing the scanner and Photoshop software and the primary pigment levels were analyzed, and the regression models based on these color parameters were established as well. The results showed that the contents of theaflavin, thearubigins and theabrownin significantly correlated with the parameters of RGB and CMYK modes. The contents of chlorophyll (Chl) Chl-a and Chl-b had high correlation with the parameters of RGB and HSB modes. All the regression models established had the best goodness of fit, in the 95 % confidence intervals, the prediction error of them varied from −3.12 to 2.05 %. 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Dark Tea during post-fermentation</atitle><jtitle>European food research & technology</jtitle><stitle>Eur Food Res Technol</stitle><date>2014-08-01</date><risdate>2014</risdate><volume>239</volume><issue>2</issue><spage>357</spage><epage>363</epage><pages>357-363</pages><issn>1438-2377</issn><eissn>1438-2385</eissn><abstract>A new method quantifying the primary pigments of Sichuan Dark Tea (SDT) rapidly based on the image processing was established. The correlations between the color parameters obtained from SDT images by employing the scanner and Photoshop software and the primary pigment levels were analyzed, and the regression models based on these color parameters were established as well. The results showed that the contents of theaflavin, thearubigins and theabrownin significantly correlated with the parameters of RGB and CMYK modes. The contents of chlorophyll (Chl) Chl-a and Chl-b had high correlation with the parameters of RGB and HSB modes. All the regression models established had the best goodness of fit, in the 95 % confidence intervals, the prediction error of them varied from −3.12 to 2.05 %. Thus, the primary pigments of SDT during post-fermentation could be excellently quantified by the image processing methods developed here.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s00217-014-2219-7</doi><tpages>7</tpages></addata></record> |
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| source | Springer Nature - Complete Springer Journals |
| subjects | Agriculture Analytical Chemistry Biotechnology Chemistry Chemistry and Materials Science Chlorophyll color computer software confidence interval Correlation analysis Fermentation Food Food Science Forestry image analysis Image processing systems Methods new methods Pigments prediction processing technology regression analysis Scanners Short Communication Software Studies Tea |
| title | simple method based on image processing to estimate primary pigment levels of Sichuan Dark Tea during post-fermentation |
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