傅里叶变换红外光谱在葡萄酒品质劣变检测中的应用

摘要

In the present work ,fresh and spoiled wine samples from three wines produced by different companies were studied u-sing Fourier transform infrared (FTIR) spectroscopy .We analyzed the physicochemical property change in the process of spoil-age ,and then ,gave out the attribution of some main FTIR absorption peaks .A novel determination method was explored based on the comparisons of some absorbance ratios at different wavebands although the absorbance ratios in this method were relative . Through the compare of the wine spectra before and after spoiled ,the authors found that they were informative at the bands of 3 020~2 790 ,1 760~1 620 and 1 550~800 cm -1 .In order to find the relation between these informative spectral bands and the wine deterioration and achieve the discriminant analysis ,chemometrics methods were introduced .Principal compounds analysis (PCA) and soft independent modeling of class analogy (SIMCA) were used for classifying different-quality wines .And partial least squares discriminant analysis (PLS-DA) was applied to identify spoiled wines and good wines .Results showed that FTIR technique combined with chemometrics methods could effectively distinguish spoiled wines from fresh samples .The effect of classification at the wave band of 1 550~800 cm-1 was the best .The recognition rate of SIMCA and PLS-DA were respectively 94% and 100% .This study demonstrates that Fourier transform infrared spectroscopy is an effective tool for monitoring red wine’s spoilage and provides theoretical support for developing early-warning equipments .%葡萄酒如果贮存方法不当极易发生劣变，失去原有的风味和质感，影响品质，因此对葡萄酒劣变进行检测，具有重要意义。在红葡萄酒劣变过程中，主要发生了酸败现象，产生了过量的有机酸类物质，致使葡萄酒原有性状发生变化。利用傅里叶变换红外光谱技术研究红葡萄酒特征光谱及其品质劣变的判别方法。对劣变过程的理化特性进行了分析，并对葡萄酒的FTIR光谱的主要吸收峰进行了解析。在劣变判别过程中，创新性的采用了比较多个吸收峰之间的吸光度比值之间大小关系的方法实现对劣变的判定，但此方法具有一定的相对性。通过对变质红葡萄酒与未变质红葡萄酒的FT IR光谱数据进行对比分析，发现在3020～2790，1760～1620以及1550～800 cm -1三个波段内，在光谱特征上具有一定的差异，为了能够将这些光谱差异与葡萄酒的劣变情况建立联系并能够实现判别分析，引入了化学计量学方法。采用主成分分析（PCA）结合软独立建模聚类分析法（SIMCA）分别对以上三个特征波段内光谱数据进行了分类，最后利用偏最小二乘判别分析（PLS-DA ）对验证集数据在这三个波段进行了判别，结果表明FT IR结合化学计量学方法能够成功区分开变质和未变质的红葡萄酒样本，且具有很好的识别率，其中利用1550～800 cm -1波段来建模分析效果最好，SIMCA和PLS-DA识别率分别为94％和100％。