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Mathematical modelling of anthocyanin mass transfer to predict extraction in simulated red wine fermentation scenarios

机译:花青素大规模转移的数学建模预测模拟红葡萄酒发酵场景中的提取

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Anthocyanins are polyphenolic compounds present in grapes that are responsible for the initial colour of red wine and their incorporation into derived pigments leads to long term colour stability. The ability to predict the effect of process variables, either controlled by winemakers or that naturally change throughout fermentation, on the extraction of anthocyanins is vital to producing red wine of high quality. A 23 factorial experiment with additional points located at central factor conditions was used to determine the impact of temperature, sugar and ethanol concentrations on the mass transfer properties of anthocyanins from fresh Pinot noir grape solids. Factor conditions were chosen to replicate ethanol and sugar concentrations that would be found in a 14% red wine and its respective unfermented juice. A previously described mathematical model was applied to anthocyanin extraction curves to determine mass transfer coefficients and distribution constants for the generation of response surface models able to predict these mass transfer variables for dynamic fermentation scenarios. The coefficient of determination for the model solution exceeded 0.94 in all cases, demonstrating a good agreement between experimental and mathematically-derived anthocyanin concentrations. Following this, simulations of anthocyanin extraction under fermentation conditions were conducted using a previously developed wine fermentation model allowing for the prediction of extraction rates and anthocyanin concentrations under various winemaking scenarios. The extraction simulations predicted a previously observed but so far undescribed anthocyanin extraction pattern during fermentation.
机译:花青素是存在于葡萄中存在的多酚化合物,其负责红葡萄酒的初始颜色及其掺入衍生颜料的掺入导致长期色彩稳定性。预测过程变量的效果的能力,由酿酒厂控制或在整个发酵过程中自然地改变,对花青素的提取至关重要为生产高品质的红葡萄酒至关重要。使用位于中心因子条件下的额外点的23个派系实验用于确定温度,糖和乙醇浓度对来自新鲜比盂Noir葡萄固体的花青素的质量转移性能的影响。选择因子条件以复制乙醇和糖浓度,该乙醇浓度将在14%红葡萄酒及其各自未淘汰的果汁中找到。将先前描述的数学模型应用于花青素提取曲线,以确定能够预测动态发酵场景的这些传质变量的响应表面模型的传质系数和分布常数。在所有情况下,模型溶液的测定系数超过0.94,在实验和数学衍生的花青素浓度之间展示了良好的一致性。在此之后,使用先前发育的葡萄酒发酵模型进行发酵条件下的花青素提取的模拟,允许在各种酿酒场景下预测提取率和花青素浓度。提取模拟预测先前观察到的,但到目前为止在发酵过程中未描述的花青素提取图案。

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