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利用傅里叶变换红外光谱法和偏最小二乘回归法同时测定葡萄酒中的乙醇和甲醇

Simultaneous Determination of Ethanol and Methanol in Wines Using FTIR and PLS Regression.

作者信息

Thanasi Vasiliki, Caldeira Ilda, Santos Luís, Ricardo-da-Silva Jorge M, Catarino Sofia

机构信息

LEAF-Linking Landscape, Environment, Agriculture and Food-Research Center, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisboa, Portugal.

Associate Laboratory TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisboa, Portugal.

出版信息

Foods. 2024 Sep 19;13(18):2975. doi: 10.3390/foods13182975.

Abstract

Accurate quantification of ethanol and methanol is essential for regulatory compliance and product quality assurance. Fourier Transform Infrared Spectroscopy (FTIR) offers rapid, non-destructive analysis with minimal sample preparation, making it a promising tool for wine analysis. In this exploratory study, the use of FTIR and PLS regression for the simultaneous quantification of ethanol and methanol in wine samples of 11 different Portuguese mono-varietal wines and different vintages deriving from the same winery in Lisbon was investigated. A model was developed, demonstrating the feasibility of FTIR and PLS regression for the simultaneous quantification of ethanol and methanol in wine samples through dedicated models; it showed good prediction capacity for ethanol determination but poorer performance for methanol quantification. The model could be reliable enough for quality control in wine production, but to improve its performance should be enhanced in the future with more samples from different origins, wine types, and a wider concentration range in the case of methanol.

摘要

准确量化乙醇和甲醇对于符合监管要求和保证产品质量至关重要。傅里叶变换红外光谱法(FTIR)提供快速、无损分析,且样品制备最少,使其成为葡萄酒分析的一种有前景的工具。在这项探索性研究中,研究了使用FTIR和偏最小二乘回归(PLS)同时量化来自里斯本同一酒庄的11种不同葡萄牙单一品种葡萄酒和不同年份葡萄酒样品中的乙醇和甲醇。开发了一个模型,通过专用模型证明了FTIR和PLS回归同时量化葡萄酒样品中乙醇和甲醇的可行性;该模型对乙醇测定显示出良好的预测能力,但对甲醇量化的性能较差。该模型对于葡萄酒生产中的质量控制可能足够可靠,但未来应通过更多来自不同产地、葡萄酒类型的样品以及在甲醇情况下更宽的浓度范围来提高其性能,以改善其性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8874/11431096/2ea6baa0351a/foods-13-02975-g001.jpg

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