西北地区干红葡萄酒质量相关理化指标的判别功能解析
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1.西北农林科技大学葡萄酒学院;2.西北农林科技大学葡萄酒学院 陕西杨凌;3.西北农林科技大学食品科学与工程学院;4.陕西省葡萄与葡萄酒工程技术研究中心 陕西杨凌;5.西北农林科技大学食品科学与工程学院 陕西杨凌

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新疆自治区科技重大专项(2017A01001-5),宁夏自治区科技重点研发计划(2018BBF02001),新疆生产建设兵团重点领域科技攻关计划(2019AB025)


Discriminant Functions of Physicochemical Indices Related to the quality of Dry Red Wines form Northwest China
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1.College of Enology, Northwest A F University;2.College of Enology,Northwest A F University;3.College of Food Science and Technology, Northwest A&F University;4.Shaanxi

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    摘要:

    研究旨在解析西北地区干红葡萄酒的质量相关理化指标的溯源判别功能。以新疆、宁夏和内蒙古乌海产区共27款干红葡萄酒为材料,基于分光光度法分析检测与色泽、味感和香气质量相关的花色苷、单宁、酒石酸酯等指标,且进行香气特征的感官量化分析。数据结果的统计分析表明,CIELab色空间和花色苷等指标中前两个主成分占总体方差71.08%,判别干红葡萄酒年份的效果明显,但对不同葡萄品种和产地的判别效果不佳。单宁等味感相关理化指标的前两个主成分占总体方差的65.93%,对干红葡萄酒产地和年份的判别效果较好,但不能有效判别品种。酒石酸酯、总酸和香气特征的前两个主成分占总体方差的83.10%,表现出较好的产地和品种的判别效果,而对年份的判别效果一般。色泽、味感和香气相关的总计20个理化指标数据在主成分分析中表现出更好的产地、品种和年份的判别效果,前两个主成分占总体方差的67.32%。聚类分析能将葡萄酒产地准确的分为3类,准确率超过90 %。基于分光光度法开发的色泽-风味理化指标的大数据具有判别我国西北地区干红葡萄酒产地、品种和年份的潜在应用前景。

    Abstract:

    The discriminant functions of physiochemical indices related to the quality of dry red wines from Northwest China were evaluated on origin, variety and vintage. In this study, 27 dry red wines from Xinjiang, Ningxia and Wuhai regions were sampled. Based on the spectrophotometric method to analyze physiochemical indices such as the anthocyanins, tannins, tartaric acid esters indices related to color, taste indices and aroma quality, and wine aroma attributes were also quantified by the trained panel. Statistical analysis of the data showed that the first two principal components (PC) of the color indices, like CIELab parameters and anthocyanins, accounted for 71.08% of the total variance in Principal Component Analysis (PCA). And the color indices had good discriminating effect on wine vintage, but bad effect on variety and region. The first two PCs of the taste indices, like tannin and polyphenols, accounted for 65.93% of the total variance, and they had good discriminating effect on region and vintage, but bad effect on variety. The first two PCs of aroma indices, like tartaric esters, acid and aroma attributes, accounted for 83.10% of the total variance, showing a good discriminant effect on region and variety, bad effect on vintage. A total of 20 physicochemical indices related to color, taste and aroma showed better discriminant effect on wine region, variety and vintage in PCA, the first PCs accounted for 67.32% of the total variance, and the Cluster analysis classified wine regions with an accuracy rate > 90%. Based on this, the big data of color-flavor physicochemical indices developed by spectrophotometry has potential application prospects for identifying the region, variety and vintage of dry red wine in Northwest China.

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  • 收稿日期:2019-11-25
  • 最后修改日期:2020-07-09
  • 录用日期:2019-12-05
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