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利用不同的红外光谱技术对发酵样品和葡萄酒中的酚类化合物进行化学计量组合分析。

Chemometric compositional analysis of phenolic compounds in fermenting samples and wines using different infrared spectroscopy techniques.

机构信息

Departamento de Tecnologia de Alimentos, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022 Valencia, España; Department of Viticulture and Oenology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa.

Institute for Wine Biotechnology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa.

出版信息

Talanta. 2018 Jan 1;176:526-536. doi: 10.1016/j.talanta.2017.08.065. Epub 2017 Aug 29.

Abstract

The wine industry requires reliable methods for the quantification of phenolic compounds during the winemaking process. Infrared spectroscopy appears as a suitable technique for process control and monitoring. The ability of Fourier transform near infrared (FT-NIR), attenuated total reflectance mid infrared (ATR-MIR) and Fourier transform infrared (FT-IR) spectroscopies to predict compositional phenolic levels during red wine fermentation and aging was investigated. Prediction models containing a large number of samples collected over two vintages from several industrial fermenting tanks as well as wine samples covering a varying number of vintages were validated. FT-NIR appeared as the most accurate technique to predict the phenolic content. Although slightly less accurate models were observed, ATR-MIR and FT-IR can also be used for the prediction of the majority of phenolic measurements. Additionally, the slope and intercept test indicated a systematic error for the three spectroscopies which seems to be slightly more pronounced for HPLC generated phenolics data than for the spectrophotometric parameters. However, the results also showed that the predictions made with the three instruments are statistically comparable. The robustness of the prediction models was also investigated and discussed.

摘要

葡萄酒行业需要可靠的方法来量化酿造过程中的酚类化合物。红外光谱似乎是一种适合过程控制和监测的技术。研究了傅里叶变换近红外(FT-NIR)、衰减全反射中红外(ATR-MIR)和傅里叶变换红外(FT-IR)光谱在红葡萄酒发酵和陈酿过程中预测组成酚类水平的能力。验证了包含两个年份从多个工业发酵罐收集的大量样本以及涵盖不同年份数量的葡萄酒样本的预测模型。FT-NIR 似乎是预测酚类含量最准确的技术。尽管观察到稍微不太准确的模型,但 ATR-MIR 和 FT-IR 也可用于预测大多数酚类测量值。此外,斜率和截距检验表明三种光谱法存在系统误差,对于 HPLC 生成的酚类数据而言,该误差似乎比分光光度参数更为明显。然而,结果还表明,三种仪器的预测在统计学上是可比的。还研究和讨论了预测模型的稳健性。

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