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首页> 外文期刊>International journal of food properties >Quality evaluation of Hanyuan Zanthoxylum bungeanum Maxim. Using computer vision system combined with artificial neural network: A novel method
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Quality evaluation of Hanyuan Zanthoxylum bungeanum Maxim. Using computer vision system combined with artificial neural network: A novel method

机译:汉源Zanthoxylum Bungeanum Maxim的质量评价。使用计算机视觉系统与人工神经网络相结合:一种新方法

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A novel technology based on computer vision system (CVS) and artificial neural network (ANN) was developed for the quality evaluation of Hanyuan Zanthoxylum bungeanum Maxim (HZB). The quality evaluation of HZB mainly depended on its colour, odour substances, and impurities. In this study, the contents of volatile oil (VOC), total alkylamides (TALC) and impurities (IMC) were determined and used as indices for quality control of HZB. Furthermore, CVS was also performed to determine the colour parameters (RGB values) and further transforms to CIE L*, a~(*,) and b*. Then, ANN was carried out to analyse the correlations between colour values obtained by CVS and quality parameters of HZB (VOC, TALC, and IMC). Higher performance and stability were presented by using CVS for determining the coloristic values of HZB. In addition, the present results also showed that the established method based on ANN could be used to predict the VOC, TALC, and IMC of HZB with the R~(2) values of 0.9991, 0.9995, and 0.9998, respectively. This novel technology based on CVS combined with ANN could be used for the rapid, non-destructive, and effective evaluation of the quality of HZB.
机译:基于计算机视觉系统(CVS)和人工神经网络(ANN)的新技术为汉源 Zanthoxylum Bungeanum Maxim(HZB)的质量评估。 HZB的质量评价主要取决于其颜色,气味物质和杂质。在该研究中,测定挥发性油(VOC),总烷基酰胺(滑石)和杂质(IMC)的含量,并用作HZB的质量控制的指标。此外,还执行CV以确定颜色参数(RGB值)并进一步转换为CIE L *,A〜(*,)和B *。然后,进行了ANN,以分析通过HZB(VOC,滑石和IMC)的CVS和质量参数获得的颜色值之间的相关性。通过使用CVS来确定HZB的着色值来呈现更高的性能和稳定性。此外,本结果还表明,基于ANN的已建立的方法可用于预测HZB的VOC,滑石和IMC,R〜(2)值分别为0.9991,0.995和0.9998。基于CVS的这种新型技术与ANN结合使用,可用于快速,无损性和有效评估HZB的质量。

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