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Elemental profile and oxygen isotope ratio ( δ 18 O) for verifying the geographical origin of Chinese wines

机译:元素轮廓和氧同位素比(δ18 O),用于验证中国葡萄酒的地理起源

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The elemental profile and oxygen isotope ratio ( δ 18O) of 188 wine samples collected from the Changji, Mile, and Changli regions in China were analyzed by inductively coupled plasma mass spectrometry (ICP-MS), inductively coupled plasma optical emission spectroscopy (ICP-OES) and isotope ratio mass spectrometry (IRMS), respectively. By combining the data of δ 18O and the concentration data of 52 elements, the analysis of variance (ANOVA) technique was firstly applied to obtain the important descriptors for the discrimination of the three geographical origins. Ca, Al, Mg, B, Fe, K, Rb, Mn, Na, P, Co, Ga, As, Sr, and δ 18O were identified as the key explanatory factors. In the second step, the key elements were employed as input variables for the subsequent partial least squares discrimination analysis (PLS-DA) and support vector machine (SVM) analyses. Then, cross validation and random data splitting (training set: test set?=?70:30, %) were performed to avoid the over-fitting problem. The average correct classification rates of the PLS-DA and SVM models for the training set were both 98%, while for the test set, these values were 95%, 97%, respectively. Thus, it was suggested that the combination of oxygen isotope ratio ( δ 18O) and elemental profile with multi-step multivariate analysis is a promising approach for the verification of the considered three geographical origins of Chinese wines.
机译:通过电感耦合等离子体质谱法(ICP-MS),电感耦合等离子体发射光谱法(ICP-MS)分析了中国昌吉,迈勒和昌黎地区的188个葡萄酒样品的元素谱和氧同位素比(δ18O)。 OES)和同位素比质谱(IRMS)。通过将δ18O数据和52个元素的浓度数据相结合,首先应用方差分析(ANOVA)技术获得区分三个地理起源的重要描述子。 Ca,Al,Mg,B,Fe,K,Rb,Mn,Na,P,Co,Ga,As,Sr和δ18O被确定为关键解释因素。在第二步中,关键要素被用作随后的局部最小二乘判别分析(PLS-DA)和支持向量机(SVM)分析的输入变量。然后,进行交叉验证和随机数据分割(训练集:测试集?=?70:30,%)以避免过度拟合问题。训练集的PLS-DA和SVM模型的平均正确分类率均为98%,而测试集的这些值分别为95%和97%。因此,建议将氧同位素比(δ18O)和元素特征与多步多元分析相结合是验证中国葡萄酒的三种地理起源的有前途的方法。

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