Wine aging in wooden barrels can alter a wine's sensory features through the extraction of wood phenols such as lignins, volatile phenols and hydrolysable tannins. Among the hydrolysable tannins, ellagitannins have been found not only to modify a wine's sensory character but also to generate new products with compounds already present in wines. For this reason, their quantification is of high importance. However, ellagitannin analysis requires the use of sophisticated equipment and many preparative steps, making their quantification in wines cost effective and laborious. In this study, the feasibility of FT-IR spectroscopy coupled with chemometrics for the quantification of ellagitannin concentration in wines was examined for the first time. Partial Least Squares regression was used to construct calibration models, using the fingerprint region of the spectrum, 1821-950 cm⁻¹ (first derivative in range). The correlation coefficient (R²) was found 0.93, the Root-Mean-Square Error of Calibration RMSEC was 1.17 and the Root-Mean-Square Error of Prediction, RMSEP was 1.57. The results indicate that FT-IR could be used for a quick, non destructive and economical estimation of a wine's total ellagitannin content.

木桶中的葡萄酒陈酿会通过提取木质酚（如木质素，挥发性酚和可水解单宁酸）来改变葡萄酒的感官特征。在可水解的单宁中，鞣花单宁不仅可以改变葡萄酒的感官特征，还可以用葡萄酒中已经存在的化合物生产新产品。由于这个原因，它们的量化非常重要。但是，鞣花单宁的分析需要使用复杂的设备和许多制备步骤，这使得在葡萄酒中进行定量分析既经济又费力。在这项研究中，首次研究了FT-IR光谱结合化学计量学对葡萄酒中鞣花单宁浓度进行定量的可行性。使用偏最小二乘回归构建校正模型，^-1（范围内的一阶导数）。相关系数（R ²）为0.93，校准RMSEC的均方根误差为1.17，预测均方根误差RMSEP为1.57。结果表明，FT-IR可用于快速，无损且经济地估算葡萄酒的总鞣花单宁含量。