首页> 外文期刊>International Journal on Smart Sensing and Intelligent Systems >A MACHINE VISION SYSTEM FOR ESTIMATION OF THEAFLAVINS AND THEARUBIGINS IN ORTHODOX BLACK TEA
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A MACHINE VISION SYSTEM FOR ESTIMATION OF THEAFLAVINS AND THEARUBIGINS IN ORTHODOX BLACK TEA

机译:一种机器视觉系统,用于估计正畸黑茶中的茶黄素和茶黄素

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Orthodox black tea quality depends upon the amount of certain organic compounds present and out of these, theaflavins (TF) and thearubigins (TR) are the most important ones While TF is responsible for attractive golden colour, increased brightness and astringency in tea liquor, TR is reddish brown, reduces the brightness of tea liquor and contribute mostly for the ashy taste of the liquor with minor improvement in astringency. The rapid estimation of TF and TR thus may resolve the problem of certain uncertainty or ambiguity that may arise during quality assessment of tea by the tea tasters. In this paper, a new method for rapid measurement of concentration of TF and TR is described using a machine vision system taking images of tea liquor and employing artificial neural networks (ANN). The results show good correlation of estimated values of TF and TR with the actual concentrations obtained using ultraviolet-visible spectrophotometer (UV-VIS).
机译:正统红茶的质量取决于存在的某些有机化合物的量,其中茶黄素(TF)和茶红素(TR)是最重要的,而TF则可带来诱人的金色,茶液中白度和涩味的增加,TR呈棕红色,降低了茶液的亮度,并在不涩味略有改善的情况下,为茶液的粗糙味道做出了很大贡献。因此,TF和TR的快速估计可以解决茶品尝者在茶质量评估过程中可能出现的某些不确定性或歧义性问题。在本文中,描述了一种使用机器视觉系统拍摄茶液图像并使用人工神经网络(ANN)快速测量TF和TR浓度的新方法。结果表明,TF和TR的估计值与使用紫外可见分光光度计(UV-VIS)获得的实际浓度有很好的相关性。

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