Centro Trasferimento Tecnologico, Fondazione E. Mach, via E. Mach 1, San Michele all'Adige, TN 38010, Italy.
Centro Trasferimento Tecnologico, Fondazione E. Mach, via E. Mach 1, San Michele all'Adige, TN 38010, Italy.
Food Chem. 2018 Nov 30;267:204-209. doi: 10.1016/j.foodchem.2017.06.131. Epub 2017 Jun 23.
Different approaches to analysing the botanical origin of tannins have been proposed in the last fifteen years, but are generally time consuming and require the use of advanced instrumentation. This study aims to suggest an effective, easy, rapid and cheap method based on the acquisition of FT-IR spectra of 3g/L hydroalcoholic tannin solutions, overcoming possible disadvantages due to sample or particle size inhomogeneity. 114 commercial powder tannins from 7 different botanical sources (oak, chestnut, gall, quebracho, tea, grape skin and grape seed) were collected and the FT-IR spectra were acquired in the region 926-5011cm. Partial Least Squares regression, Discriminant Analysis and Artificial Neural Networks were applied to FT-IR spectra to investigate the possibility of differentiating the 7 botanical origins. The best results were obtained using Discriminant Analysis, with 95% correct re-classification, and 97% grouping of grape skin and seed in a single source.
在过去的十五年中，已经提出了不同的方法来分析单宁的植物来源，但这些方法通常耗时且需要使用先进的仪器。本研究旨在提出一种基于获取 3g/L 水醇单宁溶液的 FT-IR 光谱的有效、简单、快速且廉价的方法，克服了由于样品或颗粒大小不均匀可能带来的缺点。收集了来自 7 种不同植物来源（橡木、栗子、栎、奎拉乔、茶、葡萄皮和葡萄籽）的 114 种商业粉末单宁，并在 926-5011cm 区域获取了 FT-IR 光谱。偏最小二乘回归、判别分析和人工神经网络被应用于 FT-IR 光谱，以研究区分 7 种植物来源的可能性。使用判别分析获得了最好的结果，正确分类率为 95%，葡萄皮和籽分组在一个单一的来源中为 97%。
