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红葡萄酒CIELAB参数与花色素的主成分多元线性回归分析
引用本文:郭耀东,王飞,董少杰,王圣仪,张昂.红葡萄酒CIELAB参数与花色素的主成分多元线性回归分析[J].食品科学,2019,40(18):210-215.
作者姓名:郭耀东  王飞  董少杰  王圣仪  张昂
作者单位:(1.商洛学院健康管理学院,陕西?商洛 726000;2.秦皇岛出入境检验检疫局检验检疫技术中心,河北?秦皇岛 066004;3.商洛学院生物医药与食品工程学院,陕西?商洛 726000)
基金项目:“十三五”国家重点研发计划重点专项(2017YFC1601703);河北省科技计划项目(16275519); 国家质检总局科研项目(2014QK134)
摘    要:采用CIELAB色空间体系对119种市售红葡萄酒颜色参数进行分析,并利用超高效液相色谱-串联质谱法、pH示差法分析测定红葡萄酒样品中16种单体花色素含量、总花色素含量,使用主成分分析、相关性分析和多元线性回归分析法对上述变量因子进行分析,研究红葡萄酒CIELAB体系中L*、a*值和b*值与单体花色素、总花色素含量、pH值之间的关系。结果表明,通过主成分分析得到对红葡萄酒颜色贡献程度较大的3种主成分,累计贡献率达到84.11%。CIELAB色空间体系的颜色参数分别受不同单体花色素含量影响,对L*、a*值影响最大的单体花色素为矢车菊素-3-O-葡萄糖苷,对b*值影响最大的单体花色素为锦葵色素,总花色素含量对L*、a*、b*值均有极显著影响,L*值与a*值呈极显著负相关。

关 键 词:CIELAB色空间  花色素  相关性分析  主成分分析  多元线性回归分析  

Principal Component Analysis and Multiple Linear Regression Analysis of CIELAB Parameters and Anthocyanins in Red Wine
GUO Yaodong,WANG Fei,DONG Shaojie,WANG Shengyi,ZHANG Ang.Principal Component Analysis and Multiple Linear Regression Analysis of CIELAB Parameters and Anthocyanins in Red Wine[J].Food Science,2019,40(18):210-215.
Authors:GUO Yaodong  WANG Fei  DONG Shaojie  WANG Shengyi  ZHANG Ang
Affiliation:(1. College of Health Management, Shangluo University, Shangluo 726000, China;2. Inspection and Quarantine Technique Centre, Qinhuangdao Entry-Exit Inspection and Quarantine Bureau, Qinhuangdao 066004, China;3. College of Biology Pharmacy and Food Engineering, Shangluo University, Shangluo 726000, China)
Abstract:A total of 119 red wine samples were analyzed for color parameters by using CIELAB color space, the contents of 16 different anthocyanin monomers by ultra-high performance liquid chromatography tandem mass spectrometry, and total anthocyanins content by the pH differential method. Principal component analysis, correlation analysis and multiple linear regression analysis were conducted to study the relationship between CIELAB color parameters (L*, a* and b* values) and the contents of total anthocyanins and anthocyanin monomers and pH in red wine. Three principal component factors reflecting the color in red wine samples were selected, which cumulatively accounted for 84.11% of the total variability. The color parameters were affected by different anthocyanin monomers. Among the 16 anthocyanin monomers, cyanidin-3-glucoside content had the?greatest?impact?on?L* and a* values, while malvidin content had the?greatest?impact on b* value. The content of total anthocyanins had a very significant effect on all color parameters. A significant negative correlation occurred between L* and?a* values.
Keywords:CIELAB color space  anthocyanin  correlation analysis  principal component analysis  multiple linear regression analysis  
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