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Ageing status characterization of Chinese rice wines using chemical descriptors combined with multivariate data analysis.

机译:使用化学描述符与多元数据分析相结合来表征中国黄酒的陈酿状态。

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摘要

Wine ageing status identification is of great commercial and scientific interest, as wine quality and value are closely related to the organoleptic characteristics developed during the ageing process. In this study, Chinese rice wines from three well-known wineries ("Guyuelongshan", "Kuaijishan" and "Pagoda") were analyzed for 21 chemical parameters, including six conventional parameters, five sugars, lactic acid and nine macro-elements. Then the experimental data were subjected to multivariate statistical analysis to predict and classify samples of different ageing status (3, 9, 15, 21, and 33 months). Systematic differences between samples were revealed by a two-way analysis of variance (ANOVA) and principal component analysis (PCA). Discrimination model built by forward stepwise linear discriminant analysis (LDA) based on the 16 selected parameters achieved 88.5% accuracy in leave-one-out (LOO) cross-validation. The most five discriminant variables were Zn, Mn, alcohol, Cu and Al, respectively. When the discrimination was performed on the samples from each winery, the classification accuracy in LOO cross-validation was 97.7%, 91.1% and 78.0%, respectively. The results demonstrated that these chemical parameters have the potential to enable the authentication of ageing status of rice wine. All rights reserved, Elsevier.
机译:葡萄酒的陈酿状态识别具有重要的商业和科学意义,因为葡萄酒的质量和价值与陈酿过程中产生的感官特性密切相关。在这项研究中,分析了来自三个著名酿酒厂(“古越龙山”,“奎伊吉山”和“宝塔”)的中国黄酒的21个化学参数,包括六个常规参数,五个糖,乳酸和九个宏观元素。然后对实验数据进行多元统计分析,以预测和分类具有不同老化状态(3、9、15、21和33个月)的样品。通过方差的双向分析(ANOVA)和主成分分析(PCA)揭示了样本之间的系统差异。通过基于16个选定参数的正向逐步线性判别分析(LDA)建立的判别模型,在留一法(LOO)交叉验证中实现了88.5%的准确性。判别最多的五个变量分别是Zn,Mn,醇,Cu和Al。当对每个酿酒厂的样品进行区分时,LOO交叉验证的分类准确性分别为97.7%,91.1%和78.0%。结果表明,这些化学参数具有验证黄酒陈酿状态的潜力。保留所有权利,Elsevier。

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