以三种不同陈酿方式的96个干红葡萄酒样品为试验对象， 用傅里叶变换中红外光谱仪外加衰减全反射（attenuated total reflectance， ATR）附件扫描其光谱， 然后分别用定性偏最小二乘法和支持向量机法建立三种不同陈酿方式葡萄酒的判别模型， 10次随机划分建模集与预测集后建模， 不同模式识别方法所建模型的建模集、 预测集的判别准确率均高于90%。 结果表明， 采用中红外ATR光谱技术结合模式识别方法对不同陈酿方式红葡萄酒进行快速识别是可行的。

A total of 96 red wines aged with 3 kinds of methods were included in this study, including 44 wines aged in oak barrel, 26 wines aged in stainless steel tank added with oak chips and 26 wines aged in stainless steel tanks. The infrared spectra of the wines were scanned by Fourier transform infrared spectrometer with attenuated total reflection (ATR) accessories. To classify the 96 different aged wines, discriminant partial least squares (DPLS) method and support vector machine (SVM) method were used to establish models respectively. In order to examine the stability of the discriminant model, modeling was repeated 10 times with two-thirds of samples randomly selected as cross-validation. All the models had high discriminating power with the classification accuracy of the cross-validation and the validation all higher than 90%. These results suggest that the infrared ATR spectroscopy combined with pattern recognition method is a promising tool for discriminating different aging wines.