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Estimation of Total Phenols Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools

机译:振动光谱法和化学计量学工具估算葡萄籽中的总酚黄烷醇和酚类化合物的可萃取性

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摘要

Near infrared hyperspectral data were collected for 200 Syrah and Tempranillo grape seed samples. Next, a sample selection was carried out and the phenolic content of these samples was determined. Then, quantitative (modified partial least square regressions) and qualitative (K-means and lineal discriminant analyses) chemometric tools were applied to obtain the best models for predicting the reference parameters. Quantitative models developed for the prediction of total phenolic and flavanolic contents have been successfully developed with standard errors of prediction (SEP) in external validation similar to those previously reported. For these parameters, SEPs were respectively, 11.23 mg g−1 of grape seed, expressed as gallic acid equivalents and 4.85 mg g−1 of grape seed, expressed as catechin equivalents. The application of these models to the whole sample set (selected and non-selected samples) has allowed knowing the distributions of total phenolic and flavanolic contents in this set. Moreover, a discriminant function has been calculated and applied to know the phenolic extractability level of the samples. On average, this discrimination function has allowed a 76.92% of samples correctly classified according their extractability level. In this way, the bases for the control of grape seeds phenolic state from their near infrared spectra have been stablished.
机译:收集了200个Syrah和Tempranillo葡萄种子样品的近红外高光谱数据。接下来,进行样品选择并确定这些样品的酚含量。然后,应用定量(修改后的偏最小二乘回归)和定性(K均值和线性判别分析)化学计量工具,以获得用于预测参考参数的最佳模型。已开发出用于预测总酚和黄酮含量的定量模型,该模型在外部验证中具有标准预测误差(SEP),与先前报道的模型相似。对于这些参数,SEP分别为11.23 mg g -1 葡萄籽(以没食子酸当量表示)和4.85 mg g -1 葡萄籽(以儿茶素当量表示) 。将这些模型应用于整个样本集(选定和未选定的样本)可以知道该集中的总酚和黄酮含量的分布。此外,已经计算出判别函数并将其应用于了解样品的酚类可萃取性水平。平均而言,这种区分功能使76.92%的样品根据其可萃取性水平正确分类。这样,已经建立了从葡萄籽的近红外光谱控制葡萄籽酚状态的基础。

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