基于嗅觉可视技术的醋醅理化指标分析
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江苏省自然科学基金资助项目(BK2012286)和中国博士后科学基金特别资助项目(2013T60509)


Analysis of Physicochemical Index of Vinegar Substrate Based on Olfactory Visualization Technique
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    摘要:

    通过分析56个不同发酵池种子醋醅乙醇脱氢酶(ADH)的活性与56个对应接种池的不挥发酸和总酸的关系,得出将种子ADH活性控制在600~700U/mL时,被接种池的醋醅品质较高。利用嗅觉可视化技术结合误差反向传播人工神经网络(BP-ANN)模型,快速检测种子ADH活性和预测被接种池不挥发酸及总酸质量分数。结果表明,BP-ANN模型预测ADH、不挥发酸、总酸的相关系数分别为0.7816、0.8447和0.9463。因此,嗅觉可视化技术结合BP-ANN可有效预测醋酸发酵过程中的理化指标。

    Abstract:

    Solid state fermentation is a distinctive technology for vinegarmaking. In general, the vinegar quality was evaluated by the contents of nonvolatile acid and total acid. The relationships between the contents of alcohol dehydrogenase (ADH) activity from 56 different fermentation seed tanks and the contents of nonvolatile acid and total acid from 56 different vaccination fermentation tanks were analyzed. The result showed that, when ADH activity values were controlled in 600~700U/mL, the vinegar substrate would showa good performance in quality. Whats more, the olfactory visualization sensor combined with backpropagation artificial neural network (BP-ANN) was used to test the ADH activity and predict nonvolatile acid and total acid. The result showed that the value of correlation coefficient of ADH activity, nonvolatile acid and total acid were 0.7816, 0.8447 and 0.9463, respectively. Therefore, the olfactory visualization sensor combined with BP-ANN could be well used in the prediction of physicochemical index for vinegar substrate.

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管彬彬,赵杰文,金鸿娟,林 颢.基于嗅觉可视技术的醋醅理化指标分析[J].农业机械学报,2015,46(9):223-227.

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  • 收稿日期:2015-03-10
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  • 在线发布日期: 2015-09-10
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