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首页> 外文期刊>Modern Chemistry & Applications >The Use of Fourier Transform Infrared (FTIR) Spectroscopy and Artificial Neural Networks (ANNs) to Assess Wine Quality
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The Use of Fourier Transform Infrared (FTIR) Spectroscopy and Artificial Neural Networks (ANNs) to Assess Wine Quality

机译：使用傅立叶变换红外（FTIR）光谱和人工神经网络（ANN）评估葡萄酒质量

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The aim of this study was to develop a simple method to assess wine quality from its Fourier Transform Infrared Spectroscopy (FTIR) spectrum with minimal or no sample preparation. FTIR spectral data of selected wine samples, grape variety, wine barrel type, wine type and production year were correlated with total phenolic content, total and volatile acidity and alcohol content using Artificial Neural Networks (ANNs). A total of 20 (2 whites and 18 reds) different wines used in this study came from three different states across Australia; New South Wales, Victoria and South Australia. FTIR spectroscopy proved to be a promising technique that provides a rapid and accurate method in the quality assessment of wine. A plot of the values predicted by the validated ANN models showed excellent correlation with the experimentally measured values for acetic acid concentration, alcohol content, total phenols, and total acidity (r=0.898- 0.942).
机译：这项研究的目的是开发一种简单的方法，以最少的样品制备或无需样品制备就可通过其傅立叶变换红外光谱（FTIR）光谱评估葡萄酒质量。使用人工神经网络（ANN）将选定葡萄酒样品，葡萄品种，葡萄酒桶类型，葡萄酒类型和生产年份的FTIR光谱数据与总酚含量，总和挥发性酸度和酒精含量相关联。这项研究中使用的总共20种（2种白葡萄酒和18种红葡萄酒）来自澳大利亚的三个不同州。新南威尔士州，维多利亚州和南澳大利亚州。 FTIR光谱学被证明是一种有前途的技术，它为葡萄酒的质量评估提供了一种快速而准确的方法。经验证的ANN模型预测的值图显示了与乙酸浓度，酒精含量，总酚和总酸度的实验测量值极好的相关性（r = 0.898-0.942）。

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