探讨沙棘果酒低温发酵过程中发酵动力学、抗氧化性等指标的变化情况。测定沙棘果酒发酵过程中不同时间酵母菌数量、酒精度和还原糖量的变化,首先应用DoseResp模型、Boltzmann模型、SGompertz模型和Logistic模型进行非线性拟合;其次对不同发酵时间果酒的总多酚含量、总黄酮含量、Vc含量和DPPH清除率以及总抗氧化能力进行测定。结果表明,酵母菌生长期数量的变化应用SGompertz模型的拟合度最高,R2=0.956 2;酒精生成数据应用Boltzmann模型的拟合度最高,R2=0.995 1;还原糖消耗数据应用DoseResp模型及Boltzmann模型的拟合度最高,R2=0.979 6,上述模型均能很好地描述发酵动力学特征;沙棘果酒的总多酚含量、总黄酮含量、Vc含量、DPPH清除率和总抗氧化能力均呈先上升后降低的趋势,其最大值分别达到了146.01、12.60、27.47 mg/100 mL、76.12%和145.53 U/mL。所选模型拟合沙棘果酒发酵过程是可行的,沙棘果酒发酵过程中抗氧化活性呈峰型变化,为沙棘果酒发酵提供了理论基础。
This study investigated the changes in fermentation kinetics and antioxidant activity of sea buckthorn wine during low temperature fermentation. The yeast count, alcohol content and reducing sugar content at different fermentation time were nonlinearly fitted by DoseResp model, Boltzmann model, SGompertz model and Logistic model. It was found that the SGompertz model, Boltzmann model, DoseResp model and Boltezmann model fitted the best for changes in yeast number during growth period (R2=0.956 2), alcohol formation data (R2=0.995 1), and reducing sugar consumption data (R2=0.979 6), respectively. Moreover, the contents of total polyphenol, total flavonoid and Vc, as well as DPPH· scavenging rate and total antioxidant capacity of the wine all increased first and then decreased, and their maximums were 146.01 mg/100 mL, 12.60 mg/100 mL, 27.47 mg/100 mL, 76.12% and 145.53 U/mL, respectively. In conclusion, it is feasible to use abovementioned models to simulate the fermentation process of sea buckthorn wine, which provides a theoretical basis for fermenting sea buckthorn wine.
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